India’s $250 billion IT services sector, the world’s largest outsourcing destination, faces a growing challenge: its heavy dependence on the Americas. For most of the country’s top software exporters, North America accounts for around half of revenues, while Europe adds another third. 

That leaves little room for cushioning when shocks hit.

Indian IT companies have marginally reduced their exposure to the Americas in Q1 2026 compared to last year. However, the region continues to remain their largest and most critical revenue driver, underscoring sustained dependency despite diversification effort

Even as firms look to Asia-Pacific for growth, the Americas still account for over half of revenues for most players. This highlights both the opportunities and vulnerabilities tied to the US market.

Any adverse development in the North American region tends to impact Indian IT, said Ananya Roy, founder of Credibull Capital. “Take for instance, the collapse of small banks in the US. US BFSI’s IT spends crashed in the months which followed and Indian IT players concentrated on US BFSI had suffered as a result.”

Roy added that macro headwinds are compounding the problem. “The US GDP growth clocked 2.9% in 2023, it is expected to slow down to 1.7% in 2025. The Euro area is expected to post sub-1% growth. With geopolitical and economic uncertainty, the long-term prospects for these regions look uncertain as well. IT spends in these regions seem to have plateaued.”

A Gradual  Diversification

There are signs of change. “Over the years, Indian IT’s exposure to North America has declined,” Roy said, mentioning a reduction of about 10% in overall business coming from North America. 

“At the same time, exposure to other regions (including India itself) has increased. The numbers prove that Indian IT has been successfully diversifying into other regions. Considering the recent bout of policy uncertainty, I am sure the urgency towards diversifying would have increased further,” she added.

However, Chokkalingam G, founder of Equinomics Research, finds the diversification slow and uneven. “Combined GDP of Southeast Asian countries will not be even one-fourth or one-fifth of America. So the corporate world is much bigger in Europe and America. They only need IT. Southeast Asian economies cannot help to mitigate the risk coming from the developed world,” he opined. 

Alternatives are limited, according to Chokkalingam, who said that only amicable trade between India and the US can resolve this quagmire. He noted that annual growth in IT exports had slowed down to 2–4% in dollar terms, down from 50–60% in the 1990s. 

The AI Shake-up

Artificial intelligence (AI), once seen as an opportunity, has emerged as both a disruptor and a catalyst. “With GCCs and mid-tier IT players leveraging AI more extensively and passing on the cost-benefits to clients, clients have started asking even the larger players to step up,” Roy said. 

Chokkalingam agreed AI is reshaping the economics of the sector, but in ways that also threaten demand. “The purpose of AI is to cut down the human cost, which is happening now. It reduces the cost of the base level of IT services. That is also slowly emerging as a threat,” he said.

Capital Allocation Questions

At the same time, industry heavyweights have preferred buybacks to aggressive investment in innovation. Infosys and others have returned billions to shareholders.

“Financially, it is sustainable,” said Chokkalingam. “But it also shows that you are not deploying that money for CapEx and expanding the business or IT service business. When the IT service industry growth outlook is not very robust, they should use it for acquiring mid-sized IT companies… or diversification into IT-enabled services.”

Roy flagged the lack of research spending. “India Inc.’s R&D expenses as a percentage of revenues is less than 1%, and lags significantly behind other economies. Even more alarming is the fact that in India, IT does not feature among the sectors with the highest R&D spending. For a sector that is at a risk of being rendered irrelevant, innovation is critical.” 

Green Shoots

Still, some see opportunities ahead. 

Pareekh Jain, founder of EIIRTrend, an information platform focusing on engineering, IoT, Industry 4.0, and R&D, said Indian IT players are slowly aligning with the government’s broader push to diversify exports. 

“A few years back, we wrote this note on $50 billion IT services opportunities in Japan, France, Korea. This is even more relevant now,” he said in a Linkedin Post. “In the last couple of years, one IT service provider has had a 30% CAGR growth primarily due to Japan and South Korea.”

For Jain, the lesson is that while the Americas will remain the backbone, new geographies can fuel incremental growth. “The time has come for the Indian providers to strategise this opportunity,” he said.

For now, the chart tells the story: Indian IT’s fortunes remain tied to the Americas. Whether diversification and AI adoption can tilt that balance will decide how resilient the industry is in the years to come.

The post Indian IT Firms Confront Americas Reliance Amid Gradual Diversification appeared first on Analytics India Magazine.

Accenture, the US IT consulting giant, reported another record year with $69.7 billion in revenue, a 7% increase from last year. Yet, alongside the growth, the company signalled caution. It warned of slower momentum, announced job cuts and noted that the anticipated boom from Artificial Intelligence is not delivering to the hype.

Julie Sweet, Accenture’s chief executive, admitted as much in the post-earnings call. AI, she said, has taken the mind share of CEOs, the C-suite and boards faster than any technology development we’ve seen in the past few decades. 

But the returns so far have been underwhelming. “As reported widely, value realisation (of AI) has been underwhelming for many and enterprise adoption at scale is slow other than with digital natives,” Sweet said. 

Analysts see this as a red flag for the Indian IT, as they have already been jolted by the H-1B visa crisis following US President Donald Trump’s recent orders. This week, leading Indian IT companies, including TCS, Infosys, Wipro, HCL Technologies, and Tech Mahindra, collectively lost nearly ₹ 1.36 lakh crore in market value. 

Gaurav Vasu, founder and CEO of Unearth Insights, said the opportunity isn’t yet as mature for them, as their offerings don’t fully align with enterprise needs around AI readiness.

“Most Indian IT services firms are still in the early stages of their journey with Genai. They currently focus on AI-embedded services and have yet to announce large-scale, GenAI-specific deals,” he noted. TCS is an exception. It previously announced a $900 million GenAI deal pipeline.

Read: A Wake-Up Call for Cash Rich, Idea-Poor Indian IT

AI Job Cuts Declared

The company cut 11,000 jobs in the last quarter alone, bringing its headcount down to 779,000. Sweet said the company was working on tight timelines, and reskilling was not an option for the skills they require. 

“And, we’re continuously identifying areas of how we operate Accenture to drive more efficiencies, including through AI, in order to create more investment capacity,” Sweet said, admitting that AI is causing disruption in jobs. 

Over a period of six months, the company plans to spend $865 million on a business optimisation programme, including costs for severances due to employee reductions and rapid talent rotation. Accenture CFO Angie Park noted that this money is diverted from the deal cancellation of the two acquisitions that are no longer aligned with its strategic priorities.

AI is now both a problem and a solution. On the one hand, clients want it and  Accenture is booking contracts around it, but it’s not yielding results as expected. 

Vasu noted that the key reason remains that the foundational layers required for successful AI deployment— mature cloud infrastructure, strong data governance, and clean, accessible data — are often incomplete.

The IT giant reported $5.9 billion in generative AI bookings this year, taking the total tally since September 2023 to $8.9 billion. That’s 7.3% of all orders. Actual AI-related revenue came in at $2.7 billion, still a fraction of the whole.

Comparing that to Indian IT, firms like TCS and Infosys are still mostly presenting proof-of-concept pilots to investors. Accenture is the first to spell out its GenAI revenue in hard numbers. Earlier this year, it had reported $1.5 billion in AI bookings for a single quarter.

Read: Accenture’s $1.5 Billion AI Wake-Up Call for Indian IT

Market Mayhem 

But the market is unforgiving. Accenture shares fell 2.7% after the results on September 26, closing at their lowest level since November 2020. The company forecast revenue growth of just 2 to 5 percent for the new fiscal year, with a big caveat: US federal government cuts are expected to shave off at least one percentage point. 

Washington’s new Department of Government Efficiency, led in part by Elon Musk, has cancelled IT contracts and slowed procurement. The company has exposure to government contracts through its subsidiary Accenture Federal Services, which is likely to affect the company’s earnings in the long term. 

For the fourth quarter, revenue was $17.6 billion, remaining nearly stable compared to the third quarter. Generative AI added another $1.8 billion in new bookings. 

Sweet, though, is trying to show optimism. “In FY26, we expect to increase our headcount overall across our three markets, including in the US and Europe, reflecting the demand we see in our business,” she said. 

Accenture recently announced plans for a new campus in Visakhapatnam, which is expected to add 12,000 jobs in India, as reported by Reuters earlier. 

On the Indian IT front, TCS announced layoffs for 12,200 employees, mostly in middle and senior roles, citing “strategic initiatives” including deploying AI at scale. Meanwhile, Infosys has been more upbeat, insisting that its AI bets will pay off sooner than expected.

In Q1 FY26, Infosys CEO and MD Salil Parekh had said the company has seen good demand for AI agents and built 300 agents across business operations and IT areas. “These horizontal and vertical agents are helping clients drive faster decisions, improve customer experience, and enhance operational efficiency,” he said.

The post Accenture’s Underwhelming AI Reality Check Spells Trouble for Indian IT appeared first on Analytics India Magazine.

India’s small and mid-sized technology firms are facing one of their biggest challenges yet. Artificial intelligence (AI) is forcing them to dismantle decades-old business models that have relied on low-cost delivery and headcount scale. For many, survival now depends on reinvention.

Industry experts say the shift is unlike previous technology waves. “The Indian tech SME industry has weathered many technology waves,” said Irshad Syed, partner at consultancy Slingshot. “But this AI wave questions the very basis of the predominant business model, which is based on cost arbitrage. Hence, this warrants a first principles approach.”

According to a Nasscom report, SMEs are expected to contribute 6–7% of India’s technology sector revenues in FY25, roughly $280 billion. The segment employs more than 1.3 lakh digital services professionals, including AI specialists, and has grown at 12% annually since FY20. The US remains the largest market, though many firms have diversified to Japan, Australia, and Southeast Asia.

Yet the report found that most of these firms are at an early stage of AI monetisation. Adoption is “largely reactive”, with companies embedding AI incrementally into existing services. Unclear use cases, steep costs, and talent shortages are slowing progress, while fragmented funding makes scaling difficult.

“Any tech SME is a composition of multiple value layers,” said Parameswaran E K, principal at Slingshot. “The very motivation that drives the entity is one of them. Precise segmentation is another. Deliberate focus on the business impact delivered and prudent choice of the technology drivers are the others.”

This need to rethink fundamentals comes as clients, especially in the US, push for greater value at lower costs. Contracts are now being reshaped around outcomes rather than hours billed, a shift that many SMEs admit they are struggling to keep pace with. One southern SME founder, whose company provides software solutions to US enterprises, said client expectations had changed dramatically. Buyers, he explained, “are all concentrating on getting more for less due to the AI disruption. Most importantly, they are discussing outcomes.”

Early Movers Show the Way

Some SMEs, however, are already demonstrating how to turn AI disruption into opportunity. Chennai-based Archimedis Digital has built its strategy around the life sciences industry, embedding AI into every stage of the value chain. By moving beyond the linear model of growth, it delivers outcome-based intelligent IT solutions.

“This allows us to future-proof our position in the industry and create lasting value for our clients,” said CEO and founder Duraisamy Rajan Palani. The company has restructured delivery teams into AI-powered pods that concentrate on business outcomes rather than just deliverables. Even when billing is by the hour, it reports performance against client KPIs and OKRs.

Internally, Archimedis is investing heavily in upskilling. Its Agentic AI Ninjas programme prepares every engineer and domain expert to think in terms of agentic AI, use-case development, and consultative problem-solving. Alongside this, the company is selectively hiring AI specialists, data scientists, and hybrid professionals who combine domain and technology expertise. Partnerships are also helping strengthen its workforce, with the aim of building managed services as disciplined Centres of Excellence.

Inferenz, another tech SME, has also moved decisively away from competing on cost. The company builds custom agentic AI solutions for healthcare and hi-tech industries. “We’ve consciously moved away from competing purely on low-cost delivery or headcount scale,” said CEO and founder Gayatri Thakkar. “Instead, we’ve invested 10% of our revenue into R&D, built solution accelerators and platforms to reduce time-to-market, bring the value at optimum cost that directly ties to our customer’s business goals and KPIs.”

Inferenz positions itself as “small enough to care, large enough to scale”. It combines deep domain expertise with a strong partner ecosystem, including Snowflake, Databricks, AWS, and Microsoft. Its teams are trained and certified to design productised AI-driven solutions that integrate with enterprise systems, comply with regulations, and deliver measurable ROI.

“Our unique proposition is not just building AI solutions but ensuring they integrate with enterprise systems, comply with regulations, and deliver ROI,” Thakkar said. She added that this value proposition has helped the company retain over 95% of its global clients.

Inferenz now begins engagements by co-creating success metrics with clients. Internally, delivery is structured around accelerators, technology-led centres of excellence, and outcome-driven AI agents. “This allows us to confidently enter into outcome-based engagement models,” Thakkar explained.

AI at Work in Traditional Sectors

Vasista Enterprise Solutions Pvt Ltd has shown how AI can transform even traditional industries. The Hyderabad-based company, known for its ERP and mobile app development, worked with a dairy client facing severe inefficiencies. The client struggled with outdated systems, delayed deliveries, and wasted resources due to poor route planning.

Vasista deployed an AI-enabled route planner that generated comprehensive truck schedules by aligning vehicles with routes, delivery points, travel times, and stops. The impact was striking: operational costs fell by over Rs 2.3 lakh per day, manual effort decreased by 66%, and the client’s carbon footprint shrank by 95%. Environmental sustainability improved by 100%.

An Era of Methodical Reinvention

While examples like Archimedis, Inferenz, and Vasista highlight what is possible, they remain outliers. For the majority of SMEs, AI adoption is still incremental and defensive. High costs, unclear use cases, and talent shortages persist.

Yet experts argue that SMEs are better placed than they realise. AI reduces the primacy of cost, shifting the conversation towards value-based partnerships. For smaller firms, the challenge is to carve out niches and rebuild their business models around measurable outcomes.

“The game involves carving out a niche of one’s own,” Syed said. For many SMEs, this means disassembling their existing business identity, experimenting with new value combinations, and moving swiftly to capture AI-driven opportunities.The pressures are undeniable. But the reinvention, though methodical, is underway. For India’s smaller tech firms, AI is no longer a threat to sidestep but a fundamental force demanding transformation, one that could ultimately redefine their place in the global technology ecosystem.

The post AI Pushes Indian Tech SMEs to Rethink Survival Playbook appeared first on Analytics India Magazine.

As the Trump administration moved to exorbitantly hike H-1B visa fees to prioritise American jobs, many in the industry fear the move could disadvantage Indian IT firms and talent.  

Data, however, indicates that Indian IT majors were already cutting down significantly on their H-1B visa applications over the past few years. 

Total petitions from eight leading firms, including Tata Consultancy Services, Infosys, and Wipro dropped from 25,475 in 2022 to 14,319 in 2025, according to US Citizenship and Immigration Services. The figures indicate a 44% drop in visa petitions by Indian IT firms over a four year period.

The decline is coupled with a strategic shift towards localisation, with companies like HCL Technologies reporting an 80% local workforce in the US, followed by Tech Mahindra at 70%, Infosys just over 60%, and TCS at about 50%.

Analysts and industry leaders say the move could reshape the global tech talent landscape, accelerate the trend of offshoring, and paradoxically, bolster India’s own burgeoning tech hubs.

Challenge for Mid to Small Firms 

US president Donald Trump on September 19 imposed a $100,000 fee on H-1B visa petitions under certain conditions.

Immediately after, Big Tech firms advised H-1B holders to be cautious about travel, especially if they were outside the US, amid fears over re-entry and fee implications. The White House on September 20 clarified that the levy is a one-time charge, not annual, and that it would not apply to existing visa holders or renewals, but only to new applicants beginning with the next lottery cycle. 

The rule is applicable to new petitions filed after 12:01 AM on September 21. 

Between September 20–21, the Indian tech community, Nasscom, and the Indian government voiced concerns about the abrupt timeline, the broader impact on businesses and families, and the uncertainty surrounding implementation.

In the aftermath, the Indian rupee weakened slightly pressured by the hit to Indian IT stocks.

India’s IT trade body, Nasscom, highlighted that while the long-term impact on large Indian IT firms might be marginal due to their reduced dependency on these visas, the sudden nature of the change “creates considerable uncertainty for businesses, professionals, and students across the world.” 

The fee hike is expected to hit smaller and mid-sized IT service companies harder, as they still rely more heavily on H-1B visas. 

“This would discourage mass H-1B for lower tech salaries from foreign countries, largely impacting mid to small Indian IT services, followed by mid to small GCCs and US startups trying to hire from foreign lands,” said Gaurav Vasu, founder and CEO of UnearthInsight, a cognitive intelligence platform covering Indian Startups. 

Vasu noted that this steep hike in visa fee will not cause a dent to the finances of US tech giants like Amazon and Microsoft, who hire high-skilled foreign workers at salaries well above the minimum threshold.

A report by Motilal Oswal Financial Services reveals that the Big Tech, including Google, Amazon, Microsoft, and Meta, account for a larger share of fresh applications, and Indian vendors are relatively better placed to adapt due to localisation and subcontracting. 

It adds that visa applications for FY26 are already locked in, so the $100,000 fee will be applicable from FY27 when new petitions are filed. A firm seeking 5,000 H-1B visas would face an expenditure of $500 million in fees. 

The report highlights that if new H-1Bs vanish, on-site revenues and costs would both decline, potentially improving margins given the higher profitability of offshore work, leaving the net effect on earnings per share neutral in the medium term, though top-line growth could slow.

It observed that the order is likely to face legal challenges in the US and may not survive in its current form.

Reverse Brain Drain?

The proposal is “nothing short of a wall against global talent,” according to Sanjay Tripathy, CEO & co-founder of Briskpe, a cross-border payments platform. 

By pricing out the world’s best doctors, engineers, and innovators, the US risks stalling its own engine of innovation, he argued. 

“Instead, this will accelerate India’s rise as the hub for research, patents, and startups. What the US loses in innovation, India stands to gain in progress and global leadership,” Tripathy added.

Entrepreneurs agree it could be an opportunity for India to harness its domestic talent pool more effectively. 

Shantanu Gangal, co-founder & CEO of Prodigal, a California-based AI platform that has built its entire AI and engineering team in India, warned that “startups and smaller businesses may soon find H-1Bs unaffordable, pushing talent to other hubs and risking America’s lead in AI innovation.”

Some companies, however, are projecting minimal financial disturbance. 

Engineering and technology firm Cyient, which had only six employees on H-1B visas in FY25, stated it “does not anticipate any material impact on its financials for FY26 and immediate term,” citing its philosophy of building a global enterprise with a local approach to talent. 

Persistent Systems said it is not expecting any material impact from the decision. “We will continue to monitor the developments closely and will provide updates as appropriate,” it said in a regulatory filing.

Infosys, TCS, Wipro, HCLTech and other mid-tier companies did not respond to AIM’s queries. However, according to reports, several mid-tier Indian IT firms downplayed the potential impact of the decision, citing their reduced reliance on fresh filings and stronger focus on localisation.

The reaction underscores a broader industry pivot, where years of visa uncertainty have already prompted Indian IT firms to diversify their talent strategies and invest heavily in local hiring within the US, a trend this hefty fee is poised to accelerate.

However, this is not the first time a clarion call was made.

The agenda to “bring jobs back to America” echoed recently in Washington with India in focus.

Republican senator from Ohio, Bernie Moreno, had introduced the Halting International Relocation of Employment Act (HIRE Act), which sought to impose a 25% tax on payments made by American companies to foreign firms for services provided to US customers, mainly targeting outsourcing. 

It also blocks such transactions from being tax-deductible, requires companies to report them to the government, and directs the tax proceeds into job training and workforce programs in the US.

The post Indian IT Majors Cut Visa Petitions by 44% in Four Years  appeared first on Analytics India Magazine.

“Mass upskilling is not AI innovation.” The remark by Hari Varrier, senior vice president at Havells, cut to the heart of a debate over whether India’s IT giants can reinvent themselves as product innovators in the AI era. The provocation drew sharp responses from other speakers who defended the scale and trust built by legacy firms.

The exchange unfolded at Cypher 2025, where leaders including Lenskart co-founder Ramneek Khurana, Adani Renewables chief digital officer Kiran KR, and Tube Investments CIO Krupasindhu Roul debated the future of Indian enterprise AI. The discussion pitted the experience and reach of firms like TCS, Infosys, and Wipro against the agility of startups and global platforms.

Scale vs Agility

Khurana and Roul argued that IT giants enjoy the advantages of scale, established client trust, and deep integration with enterprises. They pointed to India’s digital infrastructure, such as UPI and Aadhaar, as a unique base for building AI.

“With the results we have delivered, what we have built in terms of talent pool and talent depth in the country speaks for itself,” Khurana said.

Varrier and Kiran challenged that view. They highlighted the inertia and “service DNA” within large firms that hampers product innovation.

Kiran noted that despite India’s three-decade IT dominance and 5.8 million software developers, the country has yet to produce a global ERP, database, or social media platform. He pointed out that Indian IT majors paid $17.5 billion in dividends in two years, while innovators like OpenAI raised similar amounts for building new technologies.

He urged giants to shed complacency and invest in world-class AI products.

Giants Making Moves

The panel noted ongoing investments. TCS has earmarked funds to upskill 3.5 lakh employees, while Infosys is backing its Topaz platform. Projects such as TCS’s Ignio and multi-LLM platforms were cited as evidence of progress.

Yet both sides admitted these steps remain incremental compared with startups’ agility or the scale of global players.

That said, Startups were praised for moving fast in focused domains. Varrier said lasting innovations often come from nimble teams free from legacy processes. He added that “new-age companies” are better positioned to pioneer AI, while giants can play a role by investing in or acquiring them.

Toward Collaboration

Despite disagreements, a consensus formed around collaboration. Varrier and Kiran said India’s AI future depends on ecosystems where startups drive risk and innovation, and giants provide reach and trust.

Government pushes, such as India.ai and subsidised GPUs, were seen as positive steps to democratise data and infrastructure.

A live poll showed startups as the audience’s clear choice to lead enterprise AI over the next five years.

In closing, speakers agreed that both sides will play a role. Startups will spark “10x” shifts in services and business models, while giants bring maturity and enterprise adoption.

Roul said IT majors and startups must “tie up” to leverage each other’s strengths. Kiran and Varrier cautioned that leadership will only emerge when legacy firms adopt risk with the same enthusiasm as startups.

The post Indian IT Giants vs Startups: Who Will Script India’s AI Enterprise Story? appeared first on Analytics India Magazine.

AI should be seen as a transformative force to reinvent businesses and industries, not just as a tool for marginal efficiency, according to Saurabh Jha, SVP and global head (Data and Analytics) at Tech Mahindra. 

Speaking at Cypher 25, India’s largest AI conference organised by AIM from September 17-19 in Bengaluru, Jha argued that most large enterprises are underutilising AI by focusing only on incremental process improvements—like automating customer service—rather than reimagining and reinventing their entire business models.

Studies back this concern. MIT’s GenAI Divide report found that 95% of generative AI projects fail to deliver results. An IBM survey of 2,000 CEOs showed only one in four AI initiatives delivered expected ROI, with just 16% scaling enterprise-wide. CEOs cited disconnected technology, risk aversion, and short-term investment pressures.

During his session on “Reimagine to Scale: Beyond AI Hype to Agentic Strategy, ROI, and Trust,” Jha questioned why so few leaders are satisfied with AI investments. “Less than 30% of CEOs are satisfied. My question is, why? How has your business changed? Has it transformed your industry, your customer, your processes?” he asked.

A Gartner report also showed that despite an average spend of $1.9 million on generative AI in 2024, fewer than 30% of AI leaders said their CEOs were happy with the returns.

Jha criticised the narrow focus on customer service. “Wherever I go, the first thing they talk about is customer service. They want to use agents to replace service reps. Is that the potential of AI? It’s way beyond that,” he said.

He compared the arrival of generative AI in 2022 to the launch of the iPhone in 2007, which disrupted industries and created new businesses. “There’s a huge lack of imagination. We are trying to harness transformative technology with linear thinking,” he said.

To illustrate, he described a “faceless app” that could manage the entire home-buying process—from search to financing—by coordinating multiple businesses in the background. “Which CEO will stand up and say, let’s change the entire game of house purchase for our customers? Because that’s what AI is capable of. If they don’t do it, a startup will,” he warned.

Jha urged enterprises to move from being “AI enabled” to truly “AI first.” Resisting AI or restricting it to enablement, he said, would lead to obsolescence. “The only way to exist 10 or 20 years down the line is the third one—total business model reinvention,” he said.

He also pushed back against job cuts as the default approach. “Why not the other way around? Let’s keep all the people, make them super agents, and perform 20 times better?” he asked.

Measuring AI through old ROI metrics such as cost savings or turnaround times, he argued, misses its transformative value. “It’s a transformative technology, which we are trying to measure with tools from the 1990s. The hardest question is, how did you change your company or industry, and what competitive edge did you gain?” he said.

On governance, Jha warned of challenges as companies deploy “thousands of agents talking to each other 24/7.” Leaders must decide who owns these agents, who can stop them, and how to explain their actions. “The CEO cannot say AI did that, because the next question will be, why did it do that? And you will have no answers,” he said.

He cited a packaged food company that created a parallel startup arm to experiment with transformation, planning to absorb or replace the legacy business once the new AI-first model scales.

Jha ended by noting AI could solve bigger problems such as urban traffic, but also stressed the role of “common sense” solutions and cross-sector collaboration with government and startups.

The post Stop Babying AI: Tech Mahindra’s Saurabh Jha Wants CEOs to Reinvent, Not Just Tinker appeared first on Analytics India Magazine.

Indian IT firms are on a vibe coding spree. After Cognizant’s week-long experiment with Lovable, a vibe coding platform, Hexaware, a Mumbai-based global IT services and solutions provider, announced its partnership with Replit for secure vibe coding for enterprises. 

For Hexaware, the AI push is not new. CTO Satyajith Mundakkal says that the company had already trained 80% of its 21,000 developers on GitHub Copilot. Now, the Replit partnership is set to expand adoption across its 32,000 employees, including those who are not software engineers. 

“Many people have ideas, but unfortunately, they don’t know how to convert those ideas into applications,” Satyajith Mundakkal, chief technology officer at Hexaware, told AIM. “What the industry is trying to do with vibe coding is eliminate the need for anybody else to be there. Every individual who has an idea or a thought process can develop.”

Mundakkal said the company’s focus was on making its employees more productive and putting them at the centre of building products. That push drove Hexaware into vibe coding.

The Crazy Vibe Demand

Hexaware explored multiple products in the market before zeroing in on Replit. What stood out, according to Mundakkal, was its ability not just to build apps but also to host and test them in dynamic, collaborative environments. Developers, program managers, product managers, and subject matter experts could all come together on a single platform.

The company has been working closely with Replit on its latest release, Agent 3, which launched globally on September 10. Hexaware had early access. And shared feedback during the product cycle. 

Replit’s Agent 3 is built for autonomy. It can test and fix its own code in a loop, improving applications in the background. Its runtime has jumped from 40 minutes to 200 minutes, allowing it to think and act independently for hours.

Another breakthrough came through Replit’s integration with Microsoft. Enterprises had resisted being forced to deploy apps in Replit’s own environment, citing security concerns. “It takes a long sales cycle to convince a client why they should use your environment when they already have a massive one,” Mundakkal said.  

Hexaware’s feedback pushed Replit to integrate with Azure. Now, apps built on Replit can be deployed directly on Microsoft’s stack, making them immediately enterprise-friendly. While Replit is Hexaware’s preferred vibe coding partner, Microsoft Copilot is also part of the mix. Copilot Spark, however, is not yet available for enterprise. 

This move aligns Hexaware with other Indian IT companies such as Cognizant, Infosys, TCS and HCLTech, all of which are rushing into AI partnerships. 

The Impact of AI and India

“If I’m a Replit expert, my job is guaranteed for a long time compared to someone who doesn’t know it. We are trying to ensure our 30,000 employees are not part of the impact,” Mundakkal said. He noted that resistance to AI tools is inevitable. But freshers are already heavily reliant on them. 

“If I take GitHub Copilot away, 90% of my young population will struggle to code. They use these as coaches and guides. Our more senior population looks at it with a critical eye. They validate the work. That’s their role.”

On criticism that Indian IT firms get stuck at proof-of-concepts, Mundakkal pushed back, saying Hexaware already has almost 17–18 solutions in production.

Still, he admitted that the return on investment from AI is long-term. “Most of the investment today is enablement. Training 30,000 employees is expensive, but tomorrow, when clients ask for developers, they’ll come to us because our developers can do 20% more. That’s the return.” The challenge, he added, lies in client maturity. Many still ask for discounts rather than focusing on productivity gains. 

Mundakkal dismissed the trend around “agentic washing” where companies inflate their number of AI agents. “You go to LinkedIn and search for a GenAI developer. There is not a single profile without it. Technology is solid, maturing, and if used rightly, very potent. Yes, it’s hyped and oversold, but it is maturing,” he said.

He expressed caution about the service mindset in Indian. “The problem is trust. It takes years to build trust in products, but only a few months to build products,”  Mundakkal said. “We believe in accelerators, not products. Our aim is for clients to become productive fast.”

Demand for AI solutions, he said, remains stronger in the West than in India, where scepticism and low risk appetite hold firms back. “Indian companies would rather trust SAP or some large solution. They are listening to both positive and negative news. Western firms focus more on the positive.”

Mundakkal also pointed to the lack of support for Indian AI models. “We never go and use Indian-generated LLMs. Everyone rushes to test GPT-5, but when Sarvam comes out with a new version, hardly anyone takes it up. It’s a mindset.” 

Despite this, he said IndiaAI must be at least tenfold. “The future of the economy will be driven by AI.”

The post Hexaware CTO Says Without AI, 90% of Young Coders Would Struggle appeared first on Analytics India Magazine.

Wipro’s clients, like enterprises across the world, continue to grapple with challenges in adopting agentic AI. However, as the technology matures, these hurdles are steadily diminishing, according to the company’s chief technology officer, Sandhya Arun.

“The biggest risk that enterprises are really worried about is security, safety, data privacy, as well as whether the AI is really giving you accurate answers,” she explained during a recent interaction.  

“We call it explainability,” the executive said, adding that while these concerns were significant early on, “enterprises are finding ways to overcome it and partners like Wipro help them mitigate the risk.”

Data readiness remains central to AI adoption. Wipro has combined its global AI and data practices under one umbrella and developed proprietary tools to prepare enterprise data for AI.

Among these tools is Wipro Data Intelligence Suite (WDIS), which focuses on getting data ready for AI and Wipro Enterprise GenAI (WeGA), designed to improve explainability and contextual accuracy. 

WeGA, endorsed by NVIDIA, has already helped Wipro win several client deals, the executive revealed. 

“We usually use composable architecture (WDIS and WeGA) like Lego blocks so we can take it out or plug it in, depending on the client’s need,” she highlighted.

Getting the Pricing Right

The Bengaluru-headquartered IT giant expects that outcome-based pricing will dominate the fast-evolving market for agentic AI, with clients pressing for clear returns on investment instead of paying for technology inputs. 

“At the end of the day, the client doesn’t care whether you use 10 agents, 100 agents, five people or 60 people. [What matters is whether] you are delivering the outcome of the best possible quality, delivering the business goals, which could be customer experience or revenue uplift, and [if] you are able to sustain that year on year,” Arun explained.

The company is offering an agentic pricing model, but outcome-linked contracts are emerging as the preferred approach. 

She also clarified that the agentic model does not have to be outcome-based. 

Outcome, according to her, means delivering the result, and the client pays for it under specific terms and conditions. An agentic model, on the other hand, can involve giving an XYZ agentic solution and pricing it based on that. “Can I charge you something which makes sense to you as a client?” the executive said, noting that pricing is ultimately a function of what enterprises consider fair value.

Innovation Network

Wipro is betting on its ‘Innovation Network’ to anchor the next phase of artificial intelligence adoption, with its new centre in India already drawing daily visits from both existing and new clients, and shaping the company’s AI-first strategy.

The Wipro Innovation Network will focus on five strategic frontier technology themes: Agentic AI, robotics with embodied AI, quantum computing, digital ledger technology and quantum-safe cyber resilience. 

The company asserts that the hub will bring together Wipro’s extensive innovation ecosystem, including the Innovation Labs, Partner Labs, Wipro Ventures, its crowdsourcing platform Topcoder, alliances with leading academic and research institutions and its deep technology talent. This combination aims to create an ongoing loop of ideation, research and innovation.

The company is planning to expand the network with a new facility in London and renovations at its existing Mountain View base in California. Meanwhile, its Sydney and Dubai sites will continue to serve regional demand.

“The metric of success of the network is [measured by] impact, not pilots or ROI,” she said,

“Impact means whether your idea has matured into a successful business solution with at least one client. And if it has matured with one client, can this now be scaled as a field of play and scaled across the entire industry?” she explained.  

The network, comprising about 200 core staff and supported by hundreds more specialists, serves as a funnel for ideas ranging from immediate solutions to longer-term bets. 

“Quite often, the innovation originates in a delivery account and is then elevated and pushed into the lab. Quite often, the forward-looking Horizon 2 and Horizon 3 innovations start in the lab and [eventually] go out into the accounts,” she explained. 

AI Adoption Surging

AI adoption is accelerating across Wipro’s global customer base. What began as experimentation two years ago has now matured into scaled deployments, with AI being embedded into most client engagements.

“Almost all of our clients, who are large global enterprises, are now certain that AI is the way to go,” the executive noted. 

While early adoption primarily focused on layering AI onto existing operations, the current focus is on reimagining processes entirely with an AI-first mindset.

Cross Training

When asked how innovation will change the way developers work, Arun explained that today the company’s delivery teams keep the lights on for clients through managed services, with much of the tactical work now being AI-assisted, AI-augmented, or even fully handled by AI. 

From a talent transformation perspective, she said, Wipro has made significant investments in training, mentoring, differentiated projects and hackathons.

For example, one hackathon was won by consultants from M&A and pre-sales, none of whom were engineers. This highlights how technology is being democratised and enabling business-focused professionals to leverage AI for impact.

“Our approach is to train teams, even fresh graduates, first on understanding business, domain knowledge and agile project delivery, and then on strong foundations in software and data engineering,” she underscored. 

“This ensures they can act as supervisors for AI, regardless of age or experience. We also engage directly with campuses to align curricula with industry needs, so new hires come prepared to use AI effectively.”

Responsible AI

On the ethics committee overseeing AI usage, the executive said that Wipro has a dedicated responsible AI leader, Ivana Bartoletti, who serves as the company’s Wipro global chief privacy and AI governance officer. 

Arun explained that Bartoletti’s team holds weekly meetings involving representatives from every practice in Wipro to stay updated on the latest developments, identify risks and explore opportunities.

“We hold strong discussions on issues like patents and intellectual property. For example, whether AI can own IP (it cannot, legally), and how this affects our statements of work,” she revealed.

“We also address claims around productivity: Ivana has been very clear that we should not quote specific percentages like ‘30%, 40% or 70% improvement’, as these figures lack a mathematical foundation and are highly contextual, depending on the client’s maturity, environment and technology landscape.

“Instead, our focus is on how AI helps us reimagine how enterprises are run, going beyond just productivity gains,” she noted. 

When asked if the Innovation Network comes under Wipro’s R&D arm, at a time when the Indian IT industry has often been criticised for underinvesting in research, she was clear,

“Criticism is actually easy, but yes, the Innovation Network is a part of R&D,” the executive concluded.

In FY26, the company reported a modest 0.8% year-on-year revenue increase, reaching ₹221.3 billion. Net income rose by 10.9% YoY and the operating margin improved to 17.3%, an expansion of 0.8% YoY. 

Large-deal bookings surged 131% YoY, while operating cash flow remained strong, exceeding net income.

The post Inside Wipro’s Temple of Innovation: Data Readiness, Outcomes and Industry Impact appeared first on Analytics India Magazine.

For over three decades, Indian IT has thrived on outsourced services, particularly from the US. That model now faces its biggest challenge. The proposed US HIRE Act, which seeks to impose a 25% tax on outsourced services, directly targets India’s $250+ billion IT export industry.

If passed, it could sharply hit revenues at TCS, Infosys, Wipro, and HCLTech. While industry voices have been arguing that this disruption could be an opportunity, a few leaders look at the situation from a different angle. 

Vivek Singhal, founder of VSpartans Consultants, in an X post, urged Indian IT companies to “focus on creating products that can replace American software — email services, cloud storage, maps and navigation.”

With a domestic market of 1.4 billion users, the case for self-reliance has never been stronger, according to Singhal.

Caleb Friesen, the tech influencer, called it a “blessing in disguise”, which could push Indian engineers to create global software products, even startups, rather than contributing billable service hours for others. The irony is that foreign firms are willing to build in India, while Indian IT giants still hesitate.

Outside of rare successes like Zoho or ERPNext, Indian IT firms have struggled to build global-scale products. 

A Decade Without Breakthroughs?

“Indian IT services companies are not product companies,” said Mohandas Pai, noting that the sector hasn’t come up with a single breakthrough product in the past decade. Despite deep pockets, Pai argued, Indian IT largely focuses on client-specific solutions, while the West builds foundational AI models. 

The consequence–dependence on foreign innovation while merely implementing it locally.

Gaurav Vasu, founder of UnearthInsight, had a contrary opinion. He pointed out that Indian IT firms already run multi-billion-dollar product and platform businesses that account for roughly 15–20% of revenues. 

Infosys has Finacle, AssistEdge, XtractEdge, Equinox, and Meridian; TCS has BaNCS, Cognix, Quartz, and MasterCraft; HCL runs HCLSoftware, which includes BigFix, Unica, and AppScan.

But he concedes that these platforms mostly complement service offerings, rather than lead global markets. “While these companies have developed platforms and products complementary to their service lines, their core DNA and expertise still lie in delivering services,” he said, while adding that the real moat for IT services players has traditionally been in implementing, maintaining, and upgrading enterprise license products.

The products that do exist usually complement larger ones, or focus on markets where global vendors aren’t as aggressive, like India and Southeast Asia. 

Sitting on Cash, Watching Others Move

India’s IT giants together hold more than $20 billion in cash reserves. But instead of deploying that war chest on R&D or acquisitions, most of it goes to shareholders. Experts warn that this risk-aversion could cost the sector its future.

Ramkumar Ramamoorthy, partner at Catalincs and former Cognizant India chair, cautions about “techolonisation”—a future where India depends on others for technology needs. “If we don’t act now, we risk looking back in regret for having missed a generational opportunity,” he said.

He argued that Indian IT could use its cash reserves the way Tencent or Alibaba did—taking minority stakes in promising startups and building infrastructure for the country’s own AI and cloud ecosystem. Instead, the sector clings to the logic of its asset-light service model, even as that model comes under threat.

Vasu, however, believes that India already has homegrown alternatives to Western products.

BusinessNext, for example, competes with global CRM systems. Government platforms like Passport Seva, Income Tax e-filing portal, Government e-Marketplace and electricity board systems run on Indian IT technology.

But on critical infrastructure such as cloud, India still depends almost entirely on US players, with even government websites running on Microsoft’s cloud. 

HCLTech CEO C Vijayakumar had earlier said that AI will disrupt IT services in ways that cloud or digital transformation never did. Generative AI is reducing timelines for billion-dollar projects by years. Infosys CEO Salil Parekh has admitted the industry has to be “paranoid” about what comes next.

The paranoia is warranted. AI coding tools, agents, and automation threaten the very foundation of India’s services play—millions of engineers assigned to testing, maintenance, and integration projects. Now this, coupled with the looming threat of the US HIRE Act, is a challenge for Indian IT.

The AI Disruption is Real

The real disruption, however, is coming from AI. Vasu agrees with the HCLTech CEO that the old services model has run its course. 

“Everybody has investments, everybody has done AI verticals. But we haven’t seen any big outcomes from Indian IT services firms in terms of AI’s contribution to their pure play value,” he said. Clients are still transitioning to cloud and modern ERPs before they can fully embrace AI, which slows down the shift.

Vasu doubts that Indian IT would reinvent itself around AI within the current structures. “It’s not their DNA to completely pivot, shift and become AI-first companies,” he said. For that, they would need separate entities, new leadership, and a product-led mindset. 

That hasn’t stopped them from investing though. Infosys has its AI platform Topaz and has trained 300,000 employees on AI. Wipro launched AI360 with a $1 billion commitment. TCS created an AI and Services Transformation unit under senior executive Amit Kapur. HCL is also building out its AI practice.

Indian IT firms are likely to continue funding or acquiring startups through their venture arms. But even here, Vasu notes, risk appetite is limited because these companies are rich dividend payers with obligations to retail and institutional investors. Unlike VCs, they cannot afford too many failed bets.

Critics argue that the missing piece is not just risk capital, but an entire ecosystem. Without stronger universities, deep research, and venture capitalists willing to take risks, India will struggle to produce world-class products at scale. 

For now, the Indian IT sector faces a fork in the road.

The post A Wake-Up Call for Cash Rich, Idea-Poor Indian IT appeared first on Analytics India Magazine.

Hackathons have moved from being extracurricular coding contests to becoming central to Indian IT’s recruitment and innovation strategies. Programs such as TCS’s CodeVita and Infosys’s HackWithInfy now attract tens of thousands of students, offering fast-track job opportunities while allowing firms to assess candidates in real-world scenarios. 

Unlike global tech giants, which use hackathons primarily for branding and innovation, Indian IT firms are increasingly treating them as high volume, cost-efficient hiring pipelines.

What Draws Job Seekers

Many participants view hackathons as career accelerators. “Events where prizes include fast-track interviews or internships are most attractive. Achieving a high rank demonstrates problem-solving skills and adds weight to a résumé,” said Samkit Sharma, CEO of Hack2skill.

Competitions such as Accenture Innovation Challenge, Metlife Hack4Job, TCS CodeVita, and Infosys’s HackWithInfy are popular because top performers often walk away with job offers. 

“Hackathons provide a chance to learn new skills and demonstrate abilities by working on real projects,” Sharma said.

Candidates prefer domain-specific challenges – AI, fintech or Cloud – where creativity and technical expertise matter more than abstract puzzles.

Different Formats for Different Goals

Hackathon formats are tailored to specific purposes. Internal hackathons identify talent within companies by solving department-specific problems, often using proprietary data. Campus hackathons, like Smart India Hackathon and CodeVita, target students with industry-themed challenges across multiple rounds.

Team-building hackathons emphasise creativity and collaboration without hiring pressure, with organisations focusing on morale and culture rather than recruitment.

Scalable Recruitment Platforms

For recruiters, hackathons streamline talent assessment while reducing costs. “Instead of sifting through thousands of resumes, companies can observe candidates solving real problems,” said Sharma. Hack2skill reports instances of “near-zero hiring costs” in such events.

Sharma said that a recent study claimed that universities accommodating hackathons in their placement process saw a 70% onboarding rate among participants, highlighting their effectiveness. “Well-managed hackathons reduce the need for multiple screening rounds and interviews,” said Neeti Sharma, CEO of TeamLease. Irrelevant participants though could dilute outcomes, affecting the ROI, she cautioned. 

Hackathons are not just for students. “Mid-management professionals know the domain but often lack exposure to new tools,” said Manikandan Ekambaram, senior vice president, RPS Consulting, NIIT Ltd. Hackathons allow them to experiment with real world challenges, bridging the gap between experience and emerging technology.  

India vs Global Tech and Startups

Indian IT’s recruitment-driven hackathons stand in sharp contrast to the innovation-focused events of global tech giants and startups. “Google’s Code Jam or Facebook’s Hacker Cup are prestigious coding competitions, but winning them doesn’t directly land you a job offer; instead, they bolster the brand and let the company court top performers individually,” Sharma observed. 

FAANG events are typically invitation-only or geared towards solving highly technical challenges, often in advanced algorithms, machine learning, or emerging technologies like quantum computing. The scale is global, with rigorous vetting that prioritises elite participation rather than mass hiring.

Indian IT hackathons, by contrast, are designed to find fresh technical talent. “They are faster and more cost-effective than traditional hiring methods,” said Neeti. The goal is to convert top performers into employees quickly, making them more akin to recruitment drives than research initiatives.

Startups and unicorns represent a middle ground. “Participants get to work closely with company mentors and potentially see their solutions adopted if they win,” said Sharma. Domain-specific events like blockchain hackathons or AI-driven fintech challenges allow startups to crowdsource product ideas while engaging niche communities. However, smaller firms may struggle to attract attention, competing with the visibility and prestige of global brands. From Hack2skill’s experience, both formats have merits. 

A large Indian IT company partnered with them to conduct an online qualifier for 50,000 participants, followed by a finale where over 100 job offers were extended in a single day. Conversely, a tech startup hosting an invite-only hackathon of 50 developers didn’t hire immediately, but piloted winning ideas and onboarded participants months later.

Conclusion

The growing traction of hackathons across Indian IT, big tech, and startups underscores their importance. “Companies see value in engaging talent through collaborative competition. I believe this trend will only strengthen, with hackathons evolving to be more inclusive and creatively fulfilling, regardless of who hosts them,” Sharma concluded.

For India’s IT sector, hackathons are no longer optional—they are becoming a blueprint for smarter hiring, upskilling, and innovation.

The post Hackathons Emerge as Recruitment Powerhouses for India’s IT Sector appeared first on Analytics India Magazine.

The call to “bring jobs back to America” is echoing once again in Washington, this time with India in focus.

What began as a campaign refrain has now entered policy deliberations within President Donald Trump’s administration and among his supporters, raising the prospect of new limits on cross-border IT services.

Republican senator from Ohio, Bernie Moreno, has introduced the Halting International Relocation of Employment Act (HIRE Act).

The bill seeks to impose a 25% tax on payments made by American companies to foreign firms for services provided to US customers, mainly targeting outsourcing. 

It also blocks such transactions from being tax-deductible, requires companies to report them to the government, and directs the tax proceeds into job training and workforce programs in the United States.

If passed, the measure would apply to payments made after December 31, 2025.

Right-wing commentator Laura Loomer, reportedly a close aide to President Donald Trump, claimed on X that “the President is now considering blocking US IT companies from outsourcing their work to Indian companies.” 

She added: “In other words, you don’t need to ‘press 2’ for English anymore. Make Call Centers American Again!”

The scale

For Indian outsourcing firms, which have spent decades building a $100 billion export industry around US clients, the signals are troubling, especially at a time when they are already grappling with disruption from artificial intelligence and muted growth. 

Most large IT companies have been reporting only single-digit revenue increases.

India’s IT and IT-enabled services industry is valued at more than $250 billion annually, with about $200 billion generated from exports. Software services exports alone stood at $190.7 billion in FY 2023–24, according to the Reserve Bank of India’s annual survey on software and IT-enabled services exports.

The United States remains the largest client market, accounting for around 54% of India’s software services exports, over $100 billion a year in outsourcing revenue flowing from India to the US.

The impact

Any move to restrict outsourcing would weigh heavily not just on corporate earnings in Bengaluru and Hyderabad, but also on the livelihoods of millions of Indian technology professionals.

The debate is being closely tracked by both the Union and the state governments. Policymakers have long been criticised for failing to secure lasting visa concessions in the critical H-1B category despite years of lobbying.

Unearthinsight founder and CEO Gaurav Vasu noted that if the HIRE Act is enacted, the first companies to be hit would be US enterprises across sectors that depend heavily on outsourcing, including Cisco, American Express, Ford, General Electric, JPMorgan, Citi, BlackRock, American Airlines, Walmart, and McDonald’s.

US corporations have long relied on outsourcing to low-cost destinations such as India, Mexico, the Philippines, and Poland, he observed. Forcing them to insource operations could significantly raise costs, hurting profitability and stock market performance. UnearthInsight estimates that insourcing could increase enterprise costs and reduce margins by 1–2%.

“The ripple effect of such a policy will extend to the global outsourcing industry, with India bearing a substantial impact,” Vasu said. “This will slow down the growth of the close to $300 billion Indian technology sector, including IT services, Global Capability Centers, and adjacent industries directly or indirectly connected to outsourcing.”

Vasu and another analyst said companies would need to adopt a wait-and-watch approach.

Stating that it is too early to comment, Karnataka information technology (IT) minister Priyank Kharge said the potential US tariffs on Indian IT services are unlikely to disrupt the country’s $280-billion export sector. 

Speaking at the launch of the Karnataka Mid-Market GCC Report and the KATALYST GCC Handbook on Tuesday, he highlighted the country’s strong offshore delivery model and the global reliance on its technology talent.

Diversification a key?

Saurabh Gupta, president of research and advisory firm HFS Research, said that unlike past downturns driven by economic cycles, this crisis is man-made, with repercussions not only for Indian IT providers, but also for US enterprises that are already struggling with rising costs from tariffs.

“Any restrictions on outsourcing and broader IT services would squeeze both supply and demand sides, making delivery more expensive and less predictable,” he said.

Indian IT companies now face the challenge of diversifying markets, innovating service models, and strengthening domestic growth to cushion against tighter trade barriers.

Vasu noted that Indian IT firms are already relatively diversified, with 30–40% of revenues coming from non-US markets, where growth has been strongest. Non-US segments have been expanding at 8–12% annually.

“HCLTech saw 8.2% year-on-year growth in its ‘rest of the world’ market, Coforge 12.6%, and LTTS 26%. TCS, too, reported 10% growth in the MEA region during Q1 FY26,” he said. 

“The demand environment outside the US has remained resilient, with Europe in particular driving high growth last quarter. Beyond Europe, Asia Pacific and EMEA are emerging as attractive markets, boosted by modernisation and digital transformation needs.”

A senior manager at a Big Four firm in Bengaluru, seeking anonymity, said the potential blocking of outsourced jobs could disrupt established service delivery processes, sharply raise costs for US enterprises, and dent India’s critical role in healthcare billing.

“This would have ripple effects on both nations’ economies and the healthcare sector in particular, which relies on efficient offshore billing operations,” he said, adding that he was apprehensive about his own job given his work for the US healthcare industry.

In a LinkedIn post, Accenture’s global lead for GCC Transformation & Reinvention, Sridhar M said he has been working with clients across the globe on deep tech and innovation projects.

“Today’s technology breakthroughs happen when the best minds collaborate across borders. Disrupting this interconnected ecosystem through policy interventions could mean higher costs that slow down R&D investments, reduced innovation speed when projects can’t access the right talent, and critical skill gaps that impact competitiveness,” he wrote.

Rather than viewing this as countries competing against each other, he noted, the focus should be on creating partnerships where everyone wins—local job creation and global innovation working hand in hand.

Nasscom declined to comment on AIM’s queries.

The post Outsourcing Crackdown Looms in Washington, India’s $100 Billion IT Industry on Edge appeared first on Analytics India Magazine.

Amidst all the vibe coding partnerships and heavy enterprise AI adoption, Mphasis has quietly positioned itself as one of the most aggressive adopters of AI in Indian IT. In the June quarter, the company posted modest revenue growth, but secured record contract wins worth $760 million, 68% of which were AI-led. 

According to chief solutions officer (CSO) Ramanathan Srikumar, this is the result of nearly a decade of early bets like Next Labs, which was started in March 2015, and has been experimenting with AI and other emerging technologies for a decade. It currently is also focused on quantum computing. 

“We started playing with LLMs when it was not in the popular lexicon,” Srikumar said. The guiding philosophy at Mphasis has been to maximise productivity of domain experts by cutting down routine work.

Srikumar said that a typical expert like a mortgage processor spends 60% of their time on collecting, cleaning and preparing information and the remaining on skill application. “If I make a mortgage underwriter, instead of 40% he is spending 70%” time on applying real skill, he added. “The one way to do that is to use AI.”  

Earlier, automation tools like UiPath helped reduce the grunt work. Now, Mphasis is embedding AI agents into these workflows.

Engineering DNA

While Hexaware recently announced its partnership with Replit, Cognizant conducted the world’s largest vibe coding hackathon, and HCLTech has partnered with OpenAI. Mphasis, meanwhile, is betting on its long running partnerships with hyperscalers, while also making small bets on few AI startups.

In June, Mphasis signed a strategic partnership with Sixfold, an AI underwriting company, to speed up submission intake and improve risk assessment in insurance.

“Partnerships are extremely important in this field because we can’t do everything,” said Srikumar, adding that partnerships at Mphasis have been focused and domain-specific to draw the real benefit to the customer. The company also won an AWS Partner award for the airline industry and is co-developing a financial services-oriented product platform with AWS.

Internally, Mphasis has launched two flagship AI platforms. NeoCrux is an SDLC productivity suite that integrates AI agents into developers’ existing IDEs, avoiding the need to switch tools. NeoZeta is aimed at modernising enterprise applications by unlocking hidden knowledge in legacy code and documents.

Mphasis also tested its agents on Hugging Face’s DABStep challenge for multi-step data reasoning, briefly topping the leaderboard, even outperforming Google and Microsoft. “The ability to write multi-step reasoning agents and our experience in automating processes helped,” Srikumar said.

“As our CEO says, we are focused on bringing T back into IT. Because IT was seen more as a talent play rather than a technology play. But we brought the focus back saying we need real solid technology guys because that’s the only way we can solve it.”

That matters at a time when mid-sized IT firms are finding AI to be the great equaliser. For decades, scale determined who could dominate “run the enterprise” contracts. Large players used armies of workers to manage infrastructure and applications. Mid-sized firms had little chance.

According to Srikumar, smaller Indian IT firms are focused on building an AI arbitrage rather than scaling the number of employees and revenue. “For us, it’s not cannibalisation because we didn’t have a huge book of ‘run’ business,” he said, explaining that bigger firms have all of their existing clients seeking AI deals, which is cannibalising a huge part of their business.

AI arbitrage describes a business model where firms leverage AI tools to identify and fulfill client needs for specific AI-driven solutions, effectively arbitraging their expertise against market demand for AI services.

For smaller firms like Mphasis, AI has opened up the space to win new businesses, as customers are also more skeptical now. Mphasis is funding its AI platforms by redeploying margins rather than stretching profits. Returns, Srikumar argued, are already visible. 

“For example, NeoZeta is helping us in the modernisation process. By reducing the cost, you are opening up more opportunities to do modernisation, said Srikumar, terming it a return of investment as it expands the firm’s capabilities.

Obituary to Indian IT?

Recently, Nandan Nilekani co-founder and chairman of Infosys spoke at a panel discussion with founder NR Narayana Murthy and CEO & MD Salil Parekh about how Indian IT is well prepared for the AI wave. 

“I think there have been many times in the past when such obituaries have been written… But I’m very, very confident that in the current environment with the advent of AI, not only will we master this technology capability, but we’ll also actually use it to our advantage to again move forward and become even more critical to the world’s technology needs,” Nilekani said. 

Srikumar aligns with this belief. Model makers like OpenAI and Anthropic are now offering services directly that would disrupt IT providers. But he pointed to history. “Even if it is software, services are going to become through software. It’s a service as a software rather than software as a service,” he reasoned.

Platforms like Salesforce or ServiceNow never killed IT services. “They were building software, so they didn’t need anybody, but there is always that focus on building platforms versus delivering it in a different way. That will still continue.”

“IT service is not going to die. It’s only the nature of service that is going to change,” he said. 

The post Mphasis Uses AI Arbitrage to Take on Bigger IT Rivals appeared first on Analytics India Magazine.

Puneet Chandok, president of Microsoft India and South Asia, said the rise of AI has changed the way work is experienced, breaking free from the endless repetition symbolised by the Greek myth of Sisyphus.

He said as per the myth, Sisyphus is condemned to push a rock uphill only to see it roll back down. That’s what work felt like for many of us. Endless, repetitive, never truly done. “But with AI and technology… we’re not Sisyphus anymore.”

At the Microsoft Work Trend Index event in Noida, Chandok said that Indian enterprises are preparing to adopt AI agents at scale. According to him, 93% of leaders believe these agents will become part of the workforce in the next 12 to 18 months.

He said that AI agents will soon become digital teammates. “It’s becoming a companion, a teammate, a colleague for me before any meeting I go to,” Chandok said, citing his own experience. According to him, Copilot can now provide contextual information and work across Microsoft 365 apps.

Indian IT and New Job Roles

About the impact of AI on IT jobs, Chandok said the workforce requires rewiring instead of restructuring. He said that AI is creating new roles such as “agent orchestrator, AI workflow designer, and system optimiser.” 

Chandok said the future lies in skilling. “All of us need to be AI fluent. We need to know how to work with these tools, build agents, and get digital colleagues to work for us.”

He said the Indian IT companies seem well-positioned. “Five million people are deployed across IT services in India. We’re partnering with Cognizant, HCLTech, Infosys, LTIMindtree. Microsoft brings the best AI stack, and IT services bring domain expertise and access to customers. Together, the future is bright.” 

Echoing the sentiment at a recent event, Nandan Nilekani, co-founder and chairman of Infosys, dismissed concerns about the future of Indian IT, saying the sector has often been prematurely written off but continues to remain resilient. He stressed that both Infosys and the wider industry are well-placed to thrive in the AI era.

Nilekani added that such “obituaries” for the Indian IT have surfaced repeatedly in the past whenever a major technology shift was underway, while expressing confidence in Infosys’ and the wider sectors’ capabilities to adapt to AI and utilise it for growth of business. 

How Indian IT Firms Are Deploying AI

Beyond optimism, companies are already reshaping internal systems and workflows with AI. At Microsoft’s event, LTIMindtree’s CIO, Rajesh Kumar R, said the company is embedding AI into daily employee systems, adding, “Our vision is to provide every employee with a digital companion right from onboarding.”

Cognizant’s global solutioning head, Poornima Sathy, pointed to a workforce-wide effort. “Through our Synapse program, we’ve made a bold commitment to empower 1 million people with AI fluency globally.”

She added that when the company designs workflows, it brings together human effort, automation, generative AI agents, autonomous agents, and even ambient intelligence.

Besides that, Cognizant is bullish on vibe coding and has partnered with Lovable. In a post on X, Lovable CEO Anton Osika said, “Cognizant is now Lovable’s largest enterprise customer, a 340,000-person global technology services company.”

Cognizant aims to generate 50% of its code using AI within a year and states it has already achieved 20% of that target. The company has already trained 35,000 developers on GitHub Copilot through its Synapse skilling program and plans to train an additional 40,000 developers.

Tata Consultancy Services (TCS) is actively advancing its AI capabilities by forming a new AI and Services Transformation unit led by Amit Kapur. This unit consolidates all existing AI teams and capabilities within TCS, including the previously separated AI & data unit, to provide a unified, strategic focus on AI-driven innovation and digital transformation for its clients.

This comes after the company announced plans to cut over 12,000 jobs, primarily affecting mid and senior management levels, which is about 2% of its global workforce. 

The Indian IT company recently inaugurated a Google Cloud Gemini Experience Centre at its Banking, Financial Services and Insurance (BFSI) Innovation Lab in Bengaluru. The facility will enable financial institutions to explore AI capabilities, co-create solutions, and prototype applications by combining the company’s domain expertise with Google Cloud technologies.

Similarly, Wipro recently teamed up with Google Cloud to roll out 200 production-ready generative AI agents across sectors such as healthcare, banking, insurance, retail, manufacturing, and IT solutions. 

HCLTech is leading India’s IT sector in AI. Last quarter, the company entered into a multi-year partnership with OpenAI, making it the only major Indian IT firm with direct access to ChatGPT’s portfolio. Apoorv Iyer, global head of GenAI practice at HCLTech, said the tie-up is a turning point and the impact is threefold.

“We were the only large SI chosen after a technical assessment,” Iyer told AIM. “The focus is on capability building, adoption of ChatGPT Enterprise, creating strong technical AI solutions with OpenAI, and taking them to customers in healthcare, manufacturing, and BFSI.”

The Road Ahead

Indian IT companies are betting on AI agents as the next growth driver, with Microsoft at the centre of enterprise adoption. But the transition will require reskilling millions of workers, balancing efficiency gains with job security, and ensuring India’s IT edge remains global.

Chandok said India’s fast AI adoption is being driven by its young workforce, strong digital infrastructure, and a thriving ecosystem of startups and multinationals.

“India has got the second largest AI talent pool in the world, 17 million developers on GitHub, and the fastest growing developer community,” he said.

The post Future of Indian IT is Bright With New Job Roles: Microsoft’s Puneet Chandok  appeared first on Analytics India Magazine.

In India, landing a job at one of the top 10 IT firms has long been a dream for many engineers. For years, it was almost seen as an equivalent to securing a government job with countless perks and benefits and, most importantly, the assurance of stability with little fear of layoffs. For many, it was the epitome of success.

On the other side of this coin, however, are the comfortable software engineers at IT services companies who have been performing the same tasks over and over again, working with skills that gradually lose relevance. When they eventually face the tough job market, whether due to layoffs or while seeking new jobs, they often discover that the skills they have honed over the years no longer hold value.

A recent Reddit discussion illustrates this well. One developer shared how they spent five years in a tier-2 service company in Tamil Nadu, steadily rising from developer to “tech lead”. 

Over time, they started to believe that they were a seasoned engineer. But the illusion quickly crumbled the moment they stepped out and encountered the wider market, where the demands and expectations were very different.

The Reality Check

After spending over five years at a firm, a software engineer went job hunting only to realise that his skills weren’t even at the “basic industry level”. Despite the titles and years of experience, they struggled to keep up with what was expected outside. It took them eight months of relearning fundamentals before they finally landed a new job.

This is not an isolated instance. The IT services industry often relies on software engineers for routine maintenance and testing tasks, while current hiring trends demand software engineers who are skilled in AI. Yet, many Indian IT engineers are just not keeping pace.

Neeti Sharma, CEO of TeamLease Digital, explained to AIM that such cases are common when employees stop investing in their own growth. “Many believe that once they’ve got a job, they don’t need to learn anything new, or that upskilling is their employer’s responsibility. That’s where they get stuck,” she said. 

She added that another challenge is the nature of the work itself. Many engineers spend years working on legacy systems, only to realise later that companies they aspire to join are working on completely different stacks.

The gap in skills is further highlighted by the experiences of those with “senior” titles who admit that they never touched system design, scaling or even proper coding standards. One developer revealed that his entire project amounted to little more than a series of “if-else conditions” strung together, with no exposure to meaningful engineering practices. 

Meanwhile, some engineers, even after spending five years in the same project, worry about being labelled as ‘senior’ while still possessing junior-level knowledge. This sentiment is also signalled by the recent surge of freshers who are rejecting offers from the Indian IT firms, citing a lack of real value in joining these firms.

Read: Why Engineers are Rejecting Indian IT Offer Letters

These conversations raise a larger question: are a large chunk of Indian IT jobs truly “software engineering”, or are they essentially glorified delivery roles where tenure outweighs technical depth?

“Indian IT services don’t code,” Tanay Pratap, YouTuber and founder of Invact Metaversity, earlier told AIM. “Thirty years of IT revolution in the country, but we still don’t know how to produce coders at scale.” 

He argued that even when computer science graduates join IT firms straight out of university, their ability to code remains questionable. “The whole business model [of Indian IT] is about exporting services like testing to global customers,” Pratap further said.

Sharma, on the other hand, offered a more nuanced outlook. “While traditional IT service firms expect developers to just code, maintain and manage deliverables, many others now include design, architecture, automation and even innovation as part of the role,” she said. 

In her view, while some jobs may still look routine, the overall direction of the industry is moving closer to the expectations of global firms and startups.

Service companies, especially in non-metro cities, often train freshers just enough to deliver client projects. As long as deadlines are met, nobody cares if the engineer has learned about architecture, algorithms or even why a system works the way it does. Tenure is too often mistaken for experience. 

Ultimately, the onus falls not just on the engineers but also on the incentives that these firms offer for the applicants to build genuine coding experience.

Finding a Way Forward

Among engineers, there is an ongoing debate about what constitutes “real” knowledge; whether it is true software engineering or simply keeping up with the latest market trends. 

A recurring theme, however, is frustration. Many engineers reveal feeling stuck in jobs where learning plateaus. One such employee described their experience: “I’ve been on the same project the whole time, with Vue.js on the frontend and Firebase on the backend. The application is just full of if-else conditions. I feel like I’m wasting my time.” 

According to Sharma, the way forward lies in continuous learning, through certifications, online programmes, open-source projects, hackathons and tech groups. Yet, she stressed that real progress comes from building projects, experimenting with new technologies and exploring high-demand areas like cloud, data engineering, AI/ML, cybersecurity and product development. 

“Most importantly, developers need to move beyond just following instructions and aim to solve problems creatively. That’s what will keep them valuable as the industry keeps changing,” she added.

But the problem runs deeper. A large portion of computer science graduates leave college with minimal exposure to coding, making them eligible only for IT services jobs if they do not take the initiative to learn on their own. A recent report by TeamLease Digital indicated that only 5.5% of total engineers possess basic knowledge of coding.

In big tech firms, even when engineers aren’t building distributed systems every day, the exposure to complex problems and rigorous quality standards sharpens their thinking. In many small or service-based companies, the focus is on delivery rather than engineering. This leaves developers with skills that don’t transfer when they try to move ahead in their careers.

The issue isn’t confined to junior engineers alone. Even software engineers who have spent decades working at Indian IT firms find themselves sidelined. A senior tech professional involved in hiring, speaking on condition of anonymity, earlier shared that in Indian IT, after the age of 40, technical expertise alone holds less value unless one is in the right role, the right domain or the right circle. And AI is making the situation even worse.

Engineers often start looking for managerial roles as early as three to four years into their IT careers, which creates a mismatch between their technical needs and their aspirations. While these candidates may excel in managerial tasks, they “struggle with the technical stuff”. 

It isn’t just about small companies. Even in metros, IT service firms and captive centres often reduce engineering to task execution. The titles are inflated: developer, senior developer, tech lead, manager. But when these employees compete with peers from product companies or global firms, the knowledge gap becomes obvious.

Read: Why India is Running Out of Skilled Engineers

The post Most Indian IT Jobs Aren’t Really Software Engineering Jobs appeared first on Analytics India Magazine.

The confidence gap between larger firms and their mid-sized peers stands out in the Indian IT industry when it comes to generative and agentic AI. 

On the one hand are firms like TCS, Infosys, and Wipro, that are building hundreds of AI agents for clients but are still pessimistic about the upcoming quarters and do not expect much growth. On the other, smaller firms are vibe coding and reporting AI revenue, such as the startups reporting $100 million ARR with a single month of spiral growth.

Great examples of AI confident smaller firms are Sonata Software and Happiest Minds, which are not only quantifying it, but projecting bold numbers. Coforge, Persistent Systems, Mphasis, LTIMindtree, and Tech Mahindra are building libraries of AI agents, rolling out new coding practices, and showcasing AI-driven platforms at a pace in comparison to which, the big four seem cautious.

The question is whether these smaller firms are genuinely ahead or whether they’re guilty of what the industry is beginning to call “agentic washing”.

What’s in it for Smaller Firms?

In a recent interaction with AIM, Apoorv Iyer, global head of GenAI practice at HCLTech, one of the larger firms which is showing confidence with AI, said that there is the possibility of agentic AI washing in the IT industry, as reporting AI-related revenue is vague since it is now part of all services.

Read: HCLTech GenAI Head Calls Out Agentic Washing in Indian IT

Sonata Software is the most aggressive in its projections. CEO Samir Dhir has said the company expects AI-enabled services to make up 20% of its revenue over the next three years. Based on its current run rate, that could mean more than $300 million coming directly from AI by FY28. 

Also, Happiest Minds has already started breaking out generative AI revenue, with $1.48 million, or 2.3% of its revenue, coming from this segment in the last quarter alone.

These disclosures echo what Accenture and ServiceNow have been doing globally, but they are unusual for India. The largest IT firms have avoided separating AI revenue so far. Only TCS had reported its generative AI pipeline of $1.5 billion in Q1 FY25, but since then, it stopped doing so.

Infosys and HCLTech highlight the number of agents they’ve built, not what those agents are earning.

“There’s a lot of superficial claiming of agency, with people describing simple tasks and labelling them as agents. It is not really about the quantity of agents, it is about the complexity, quality and adoption of AI within your customer base and enterprise,” Iyer added.

In other words, everyone is chasing the AI label, but what that means in rupee terms is unclear. It is possible that mid-size firms might also be doing the same. The only different one in the larger firms is Cognizant, which just made it into the Guinness world record for world’s largest online generative AI hackathon with 30,601 working prototypes.

The vibe coding event had more than 53,000 Cognizant associates across 40 countries. CEO Ravi Kumar S is extremely confident with generative AI. He aims to generate 50% of the firm’s code using AI within a year and states it has already achieved 30% of that target.

Bu to take an example similar to Cognizant but in the mid caps, Coforge is also experimenting with vibe coding. It has tested tools like Cursor and Windsurf, building a secure setup for its internal TechCon conference where engineers could describe applications and have them generated by on-premise LLMs. 

As for the revenue from all of this, Vikrant Karnik, EVP for digital, data, cloud, and AI at Coforge, told AIM that reporting AI revenue is not exact. “It’s a little bit like asking a hotel to list electricity as a revenue line,” he said. “We’re here to deliver shareholder value for our customers. If AI helps us do that, we’ll use it.”

Read: Coforge’s AI Reality Check for Indian IT to ‘Strip Away the Fat’

Mid-Caps Pulling Ahead with Agentic Washing?

Even with the ambiguity, the numbers tell their own story. Persistent Systems reported $389.7 million in revenue last quarter, up 18.8% year-on-year. Profits jumped nearly 39%. The company has now delivered 21 straight quarters of double-digit growth. 

Coforge grew even faster, up 56.5% year-on-year, with profits more than doubling. It also became the seventh-largest IT firm in India, surpassing Mphasis.

Both companies are attributing their success to AI. 

Persistent credits a platform-driven approach similar to ServiceNow, embedding AI into client projects instead of keeping it as a side offering, for its growth. Coforge has built AgentSphere, a library of 100-plus AI agents for sectors like travel and healthcare, and is betting on scaling them.

Mphasis booked its highest TCV in eight quarters, with 68% of those wins being AI-led. LTIMindtree launched BlueVerse, a unit offering 300 specialised AI agents across industries. Tech Mahindra deployed more than 200 AI agents while managing a 34% year-on-year jump in profit.

Compare this to the Big Four. Wipro doubled its large-deal bookings but still saw topline revenue decline. TCS managed just 1.3% growth, with constant currency revenue falling 3.1%, and Infosys delivered modest growth but still lagged behind mid-cap peers in pace and clarity.

Enthusiasm among smaller firms though, raises a red flag. Declaring 15–20% revenue through AI when the category is in its infancy might be overreach since even their larger counterparts choose not to do so. 

Many of these deals are small contracts. For mid-sized companies, a $5–10 million AI engagement can look transformational against a smaller revenue base. For giants like Infosys or TCS, the same deal is barely a rounding error.

Also read: AI ROI is Better for Coforge, Persistent, Mphasis, L&T than the Big Four Indian IT

The post Mid-Size Indian IT Might Be ‘Vibing’ a Little Too Much with AI appeared first on Analytics India Magazine.

When OpenAI unveiled GPT-5, an incremental yet meaningful advance in artificial intelligence, the global tech world sat up and took notice. The launch is poised to reshape India’s sprawling IT services industry.

Many industry experts believe the progress could potentially dent revenues in the short term, but unlock a new wave of long-term opportunities in the long run.  

With marked improvements in reasoning, a sharp reduction in hallucinations and lower pricing than competitors, GPT-5 is expected to accelerate enterprise adoption of generative AI, particularly in software development. 

This increased efficiency, however, could slow the Indian IT industry growth, creating a 2-3% drag over the next two to three years. As productivity gains rise, traditional effort-based billing models face revenue deflation for services based on, according to a Kotak Institutional Equities report accessed by AIM. 

While the analysts who drafted the report argue that this is only a temporary setback, they believe the sector is on the cusp of a significant transformation, where new AI-driven businesses will eventually offset the short-term pressure. 

Enterprises, they noted, will increasingly turn to IT partners to build strong cloud and data foundations necessary to harness AI, modernise legacy applications with lower risk, and deploy AI across sector-specific use cases.

Insiders See the Light

Firstsource views this trend as an opportunity rather than a threat. The company’s chief digital and AI officer, Hasit Trivedi, emphasises that it isn’t just GPT-5 alone; new models will continue to emerge, offering the developer community powerful productivity tools.

Trivedi acknowledges that the technology would compress some legacy revenue streams in the short-term, but argues that the focus should not be on offsetting deflation but on stepping into a larger, higher-value opportunity space.

AI is already reviving long-postponed modernisation decisions, building trusted data foundations and operationalising AI use cases at scale, he added.

Among the most promising areas, he identifies four: legacy modernisation; data foundations for AI, AI operationalisation and edge AI.

A senior executive at a leading platform-based company, who asked not to be named, pointed out that advanced large language models are set to reshape the sector. 

Clients of IT companies, he noted, are primarily focused on creating applications faster and differentiating from competitors. With AI tools like GPT, “companies can accelerate coding, boost reasoning capabilities, and enhance productivity”, he said. 

Rather than job losses, he argued that the shift has led to faster delivery and higher-quality output.

The impact is also visible in sustenance services, where AI can correlate incidents quickly and provide real-time summaries to improve 24×7 operations. However, he admitted that revenues may take a short-term hit.

While consulting engagements may shrink in duration, from a year to four months, IT firms will be able to execute more projects at a higher quality. 

He agreed that while headcount needs may fall in some functions, “overall work will expand as clients push for faster modernisation, greater automation and better user experience”.

The executive dismissed the idea that clients might bypass IT firms altogether to adopt these technologies themselves. 

“If that were the case, it would have happened earlier,” he said, explaining that enterprises prefer to focus on their core business and rely on external expertise for complex migrations and AI integration. 

On this point, Trivedi differs. He contended that there is no one-size-fits-all approach. As with every significant technology wave, he believes some enterprises will adopt directly, some will rely on IT partners, and others will go through startups or hyperscalers. 

“Most will experiment across all of these and eventually settle into an equilibrium of in-house vs outsourced, build vs buy. The key role for IT and digital partners will be bringing domain context, integration expertise and governance discipline, because that’s where enterprises will need the most support,” he shared.

Relook the Approach

Roopa Sunder Raj, former MD at Accenture, acknowledged that GPT-5 and similar technologies will have a “huge impact across several IT functions”.

The first barrier to adoption of advanced technology, she highlighted, is mindset, wherein fears of layoffs must be replaced with an exploration of new possibilities. 

Once that shift happens, enterprises need a clear vision and the willingness to experiment with pilot programmes, Raj added. 

Moreover, she also spoke about the need to look into the aspect of immense revenue-generating potential beyond simple cost savings. Raj cited the example of AI’s ability to screen thousands of resumes for a single job opening, something “humanly impossible for recruiters”.

This evolution will fundamentally alter the client-vendor relationship, she observed. 

The future, in her view, lies in a combination of service models where enterprises combine traditional IT support with “plug-and-play” solutions from startups specialising in agentic AI.

The impact, she warned, will be felt most by manpower-heavy IT services. 

“In the past, clients asked for 100 Java developers or 200 Python developers,” she recalled. “Now with generative AI and agentic AI, a lot of tasks that once required large teams no longer need to be built from scratch.”

Consequently, the traditional pricing model of charging for headcount or developer hours is being directly challenged. 

Clients, she added, “will expect new pricing models aligned with outcomes delivered by AI”.

The post GPT-5 Forces a Rethink Across Indian IT appeared first on Analytics India Magazine.

In the bustling corridors of India’s IT sector, “outcome-based” has become the new mantra. Spurred by the AI revolution, industry leaders are declaring a break from legacy billing models. Clients, they argue, are no longer interested in paying for hours worked or personnel deployed; they want to pay for tangible results.

Yet, the shift appears to be more aspirational than actual. While the language on earnings calls and in sales pitches has evolved, the fine print in most contracts reveals a different story. The majority of AI deals continue to follow the very models they’re meant to replace, compelling clients to ask the uncomfortable but inevitable question: “What’s the outcome?”

The Reality Check: Old Wine in a New AI Bottle

Despite the hype, Indian IT services have yet to meaningfully sell AI solutions as true outcome or value-based deals. The numbers, says Gaurav Vasu, founder of the research firm UnearthInsight, tell a stark story.

“About 95-98% of current AI deals are traditional services with AI solutions layered on, focused on productivity improvement targets,” Vasu noted. He added that even the standalone AI proofs-of-concept (PoCs) are typically small, in the $1-5 million range.

A senior executive at a top-tier Indian IT firm, speaking to AIM on condition of anonymity, confirmed this cautious approach. “IT companies are adopting different pricing approaches as no one is clear on how comprehensively AI will impact IT services,” he admitted.

The sticking point is that not every project has a clear, definable outcome. “Take app maintenance projects. Such projects are sometimes priced on a pod or squad basis, with a fixed price for each pod of developers,” the executive explained. 

Other experiments include bill of materials-based pricing, where separate line items cover services, AI agents and tools. 

For Ankit Bose, head of Nasscom AI, this reflects evolution. He described the shift as a “clear progression, not a sudden shift”. He argues that the industry is moving toward a hybrid model that “combines fixed fees with success-linked bonuses tied to measurable business outcomes.”

The Devil in the Definitions: Outcome vs Value

Part of the confusion stems from the way “outcome-based” and “value-based” pricing are often used interchangeably. While related, the two are not the same. Outcome-based pricing ties fees directly to specific, measurable KPIs. For instance, a 30% reduction in customer ticket resolution time. It is tangible and relatively easy to structure. 

In contrast, value-based pricing is a far more ambitious model, linking charges to broader business outcomes, such as revenue growth or market share gains. This approach is much harder to execute, considering quantifying and attributing this kind of impact is notoriously difficult.

Companies are trying to navigate this spectrum. Kalyan Kolachala, MD of SAIGroup India, said his firm leans towards a value-based approach by focusing on the “productive benefits” AI brings. “If you’re saving X, can we get a small percentage of that X? That way, pricing is tied to outcomes,” he explained.

Hasit Trivedi, chief digital and AI officer at Firstsource, said his organisation is already there. “For us, AI pricing always starts with the ‘what’, what business value can we deliver,” he said, adding that their commercial models are “driven by value”. However, he concedes that “the real challenge is measuring the full impact”.

Why Deals Go Into ‘Cold Storage’

This measurement challenge is one reason many promising conversations are stalling. Vinay Kumar HS, global business head at AidenAI, noted on LinkedIn that deals often slip into “cold storage” due to a lack of clarity. “One of the key reasons for client hesitance is the lack of clarity around the KPIs used to define success, as well as the internal dependencies required to achieve those outcomes,” he explained.

Multiple critical roadblocks stand in the way. A big one is the fear of cannibalisation. As NimbleEdge co-founder Neeraj Poddar pointed out, vendors charging per-seat for human agents face a dilemma where pricing an AI agent per-ticket could undercut their existing, lucrative business. 

Attribution poses another hurdle. Attributing revenue uplift directly to an AI solution is “never straightforward,” Poddar observed, making pure value-based models a tough sell. 

Cost unpredictability and risks adds to the caution. Kolachala revealed that “only when scaled in volumes do clients realise that…costs can be higher than expected,” citing expensive calls to large language models. 

Moreover, the risk of AI “hallucinations” remains a persistent concern, requiring costly human oversight.

A Radical Alternative: Ditch Complexity for a Flat Rate

Frustrated with the messy variables of both legacy and emerging models, some experts are proposing a third way. Saurabh Gupta, president (research and advisory) at HFS Research, argues that both effort-based billing and outcome-linked pricing are becoming obsolete.

“In an AI-led world, effort-based pricing doesn’t just feel outdated, it’s meaningless,” Gupta stated. “Measuring its value in FTE equivalents is like measuring streaming bandwidth in DVDs shipped.”

He pointed to the unpredictable nature of AI costs, ranging from compute power (NVIDIA GPUs), token charges (GPT-4) and storage to fine-tuning and API fees. His solution: flat-rate pricing. 

The model is simple—a single, all-inclusive annual fee for an AI platform within a defined scope. For example, he shared, “$150,000 a year for an AI-led customer query automation platform handling up to 10 million queries.” This approach offers clients cost certainty and incentivises providers to optimise their operations.

Gupta frames this as a “trust-building move”, on his blog. Yet it comes with risks. What happens if a client’s usage explodes beyond the scope, making the contract unprofitable for the vendor? Conversely, what if the client pays a large fee but their usage is minimal? He did not respond to requests for comment on how such pitfalls might be addressed. 

For now, the Indian IT industry remains in a state of pricing uncertainty. 

Everyone agrees the old world of time and materials (T&M) and full-time equivalent (FTE) billing is fading, but a clear, scalable and sustainable model for the AI era has yet to emerge. 

The transition from selling effort to selling outcomes is proving to be the industry’s most complex project yet.

The post Indian IT Caught Between Hours and Outcomes appeared first on Analytics India Magazine.

Mid-Tier IT firms, despite strong revenue growth, haven’t seen a significant increase in revenue per employee (RPE) compared to the largers players in the industry. Mid-tier companies such as LTIMindtree and Coforge are growing revenues at 15–20% year-over-year (YoY) but have not matched this pace in RPE expansion. 

In contrast, Infosys and HCLTech have delivered among the highest RPE CAGRs in the sector, with Infosys achieving ~13% over six years. With mid-tier IT, Persistent Systems stands out, recording 58.2% growth in RPE since FY2022, the highest among peers. 

A factor to consider is that the employee growth rate in mid-tier IT firms is much greater than that of the ‘Big Five’ of India’s IT industry. But is this the only factor at play? Analysts report that strategic factors such as pricing, automation, portfolio mix and IP monetisation are equally important in shaping RPE growth.

Big IT vs Mid IT

Among the Tier-1 IT firms, RPE has grown steadily in the 20–34% range between FY22 and FY25. Infosys leads this group with a 34% jump, followed closely by TCS and HCLTech at nearly 30% each. Tech Mahindra reported 25% growth, while Wipro lagged at 20%. In absolute terms, HCLTech and Infosys now generate the highest RPE at over ₹52 lakh per employee, with TCS close behind at about ₹42 lakh.

Mid-tier IT firms present a more uneven picture. Persistent Systems is the clear outlier, with RPE soaring from ₹30.7 lakh to ₹48.6 lakh—a 58% rise that puts it nearly on par with Cognizant and within striking distance of HCLTech and Infosys. LTIMindtree also showed strong performance with 27% growth, broadly in line with Tier-1 peers.

Others, however, have lagged. Coforge, Hexaware and Cognizant managed only mid-teen growth, while Mphasis rose just 13%. Firstsource stands apart, barely moving the needle with less than 2% growth, reflecting the constraints of its BPO-heavy model.

Taken together, Tier-1 firms demonstrate consistency at scale, while mid-tier players are more polarised: a few, like Persistent, are catching up rapidly, while others trail well behind.

Big IT Breaks the Headcount-Revenue Link

Tier-1 IT firms are moving away from linear growth models that tie revenue directly to headcount. By embedding automation, IP assets and accelerators, they are scaling programmes without proportionally expanding teams, lifting RPE in the process.

Sanchit Vir Gogia, CEO at Greyhound Research, noted that this reflects a deliberate decoupling of revenue from staff count. “Infosys, TCS and HCLTech slowed hiring pyramids, redeployed AI in delivery and exited low-margin work. Infosys, for example, posted double-digit RPE growth even as its operating margin fell from 25% to ~21%. Margins are under strain, but rising RPE now acts as a strategic buffer,” he said. 

According to Gogia, mid-tier IT firms’ revenue growth is still predominantly manpower-led. Their pyramid-heavy hiring models dilute average RPE. While they excel at $1-5 million bite-sized deals that clients now prefer, such contracts typically require nearly proportional increases in staffing. 

Automation Boosts RPE

Automation has become a direct lever for RPE growth. As per Greyhound’s CIO Pulse 2025 report, a European bank—a client of Infosys—embedded AI in its trade finance operations, lifting contract value by 22% YoY while reducing staffing needs. The deal boosted RPE but required onshore compliance-heavy delivery, which dampened margins. The bank’s CIO admitted the paradox: “We’re paying more per solution, but the vendor’s per-head profitability is shrinking.”

Mid-tier firms are also adopting AI, but without comparable scale. “Outcome-based AI projects are emerging, but mid-tier players often absorb upfront costs, keeping RPE low. “Without scale investments in automation platforms, their revenue per employee remains structurally capped,” Gogia said. 

Mid IT Lacks IP Monetisation

Tier-1 firms are leveraging proprietary IP and platforms to drive both productivity and higher billing rates per employee. This gives them an edge in sustaining RPE growth.

Mid-tier players, however, continue to struggle with IP monetisation. According to Greyhound, a Japanese automotive client praised a mid-tier vendor’s AI-enhanced outcomes but admitted the vendor had to discount due to a lack of proprietary IP. “The value-add was capped by the model,” the CIO said.

IP-based offerings carry higher margins because they are reusable, licensed and often outcome-linked. Owning even small IP lets mid-tier IT protect margins in a market where pricing power is otherwise eroding. This creates repeatable revenue stream without having to grow proportional headcount.

Similarly, Kishor Patil, CEO at KPIT Technologies, acknowledged productivity gains from AI but noted they are not backfilling attrition, leading to “softness on the employee side” and limited RPE growth.

Clients Want Big IT for RPE Gains

Client preferences are shifting in line with RPE performance. Greyhound CIO Pulse 2025 shows global buyers gravitating to Tier-1 firms for multi-year transformation contracts, especially in AI-enabled operations and engineering. 

CIOs consistently report that these firms bring greater automation and reusable platforms to engagements, allowing projects to scale faster without proportional increases in staffing. While buyers acknowledge that vendor margins are under pressure, their experience is that Tier-1 firms deliver greater per-person value on engagements compared with mid-tier firms.

Mid-tier firms, in contrast, remain boxed into staff augmentation roles, essentially supplementing the existing workforce. About 58% of CIOs surveyed still see them that way, and only 12% said they received proprietary IP or accelerators.

Clients acknowledge their agility and responsiveness, but do not perceive the same per-employee value uplift delivered by Tier-1 providers. This reinforces the perception that mid-tier growth remains linear and manpower-driven—a key reason why clients do not see the same per-employee value uplift they experience with larger providers.

RPE as the Market Divider

The industry now reflects two distinct growth models. Tier-1 firms are driving higher revenue per employee through automation, platforms and IP, using RPE to cushion margin pressure. Mid-tier players remain reliant on headcount-led growth, limiting per-person productivity. For clients, the split is clear: Tier-1 firms deliver stronger RPE gains, while mid-tiers offer agility but less value per worker.

The post The RPE Divide: Giants Build Value, Mid-Tier Builds Volume appeared first on Analytics India Magazine.

India isn’t just a market for ServiceNow — it’s a core R&D hub. About 40% of its global product engineering happens here. That’s not limited to product creation; engineering teams here often work directly on large-scale deployments.

The platform-as-a-service company could possibly resolve one of Indian IT’s chronic problems: the bench. 

ServiceNow’s MD and GVP, India and SAARC, Ganesh Lakshminarayanan said that AI could match skills in real-time, recommend training, and push people into billable work faster, while reflecting on resolving the demand and supply conundrum of the Indian IT industry. 

While speaking with AIM, he said that access to data on both the ends and AI agent’s intervention would be critical to design such workflows.

“Assume that there are AI agents working on both sides. Somebody who’s coming up with personalised recommendations and somebody who’s pushing the workflow. Suddenly, you’re solving the most important problem SIs are having,” Lakshminarayanan said, talking about reducing the numbers on the bench.

This is where a platform approach beats siloed tools, he argued. It’s also why ServiceNow is investing in an “AI Control Tower” that can orchestrate not just its own agents, but those built on Microsoft, ERP systems, or other vendors. “Our approach has never been proprietary,” he said. 

“We work with multiple LLMs. The value is in the data and workflows.”

This will help companies train and upskill employees in real time with new skillsets without a human push. “You can build AI which learns on both sides and creates personalised recommendations for each employee,” he explained.

Lakshminarayanan said that the Indian market, by all accounts, is heating up fast. “The country is going through a major AI uptick. We are in the right stage of growth.” The proximity to both customers and developers, he said, is a “boon”, allowing rapid innovation and problem-solving.

ServiceNow’s Big Bets on India

While Indian IT and consulting giants are busy promising AI transformation, ServiceNow is already delivering it. In a market filled with pilots, the company’s AI subscription revenue has risen to $3 billion, and AI deal volume has increased by 50% in a single quarter, as per its Q2 earnings results.

ServiceNow’s own research predicts AI will create 10.3 million jobs in India by 2030. Lakshminarayanan has lived through three tech booms—the internet, BPO, and now AI—and believes each has been a net job creator. 

The roles may shift away from pure coding to “business-tech-commercial” skills, but the demand will be massive. He’s backing that belief with a goal to train one million Indian learners in AI skills by 2027, part of a global goal of three million of ServiceNow University. 

“India needs AI, but AI needs India,” he said, pointing to the country’s unmatched scale in banking, telecom, retail, and IT services. “If a particular AI company wants to make their AI agents useful for banking, where else are you going to find the biggest banks in terms of volume of transactions? You’re going to find them in India.”

Most importantly, Lakshminarayanan is clear that the future belongs to platforms that can bring together data, workflows, and AI agents. ServiceNow’s Workflow Data Fabric (WDF) is designed to do exactly that—connect multiple systems of record without copying data, making it instantly accessible to AI agents with minimal latency.

This is similar to what Sumeet Mathur, SVP and MD of ServiceNow India Technology & Business Centre, told AIM earlier.

“Our one-platform approach gives us a significant edge over competitors who rely on acquisitions to piece together solutions,” Mathur explained. ServiceNow stands out with its commitment to providing a single platform, data model, and architecture. This strategy ensures an integrated and seamless user experience across an enterprise’s various functions.

Paul Smith, former president of global customer and field operation at ServiceNow, told AIM earlier in an interaction: “One in five of all ServiceNow employees is based in India. And 85% of the resources that we have in ServiceNow India are in R&D and engineering roles — especially core engineering.” 

Smith went on to highlight that a significant number of these engineers are working on leading-edge research around AI, underlining India’s role in building the future of enterprise automation. He is currently the chief commercial officer at Anthropic. 

The Service Deficit

Infosys and TCS, two of ServiceNow’s biggest Indian partners, are also building AI platforms. Lakshminarayanan sees their role as complementary. “AI value comes from data plus workflows. We’ve been doing IT workflows for 20 years, which is why we can achieve 78% automation already with agentic AI.”

Lakshminarayanan is quick to draw a line between ServiceNow’s positioning and that of other IT vendors. “We are an AI platform company,” he said. This shift is deliberate. 

ServiceNow’s long-standing IT workflows, HR automation, and service management tools have given it something many AI startups and consultancies don’t have: deep, structured, enterprise-wide data. 

Lakshminarayanan pushes back on the narrative that AI adoption would lead to reduced jobs. Instead, he sees Indian enterprises using AI to bridge what he calls “the service deficit.”

He recalls a conversation with the ED of a large public-sector bank. The executive asked: Why should only a small percentage of accounts get a dedicated relationship manager? Why not use AI agents to make that experience available to every account holder?

It’s a theme he sees across industries — from consulting firms looking to give every employee a digital executive assistant, to HR leaders wanting a dedicated recruiter for every candidate. “It’s about hyper-personalised service, so people can focus on meaningful work,” he said.

With OpenAI now hiring forward-deployed engineers in a Palantir-style move, is there a threat to ServiceNow’s position? Lakshminarayanan doesn’t think so. 

“Yes, you can deploy forward engineers, but without existing data and workflows, you’re starting from scratch. We have 150 AI agents out-of-the-box, going to a thousand in six months. Time to value matters.”

The post ServiceNow India Head Says AI Agents Can Shrink the Indian IT Bench appeared first on Analytics India Magazine.

HCLTech is leading India’s IT sector in AI. Last quarter, the company entered into a multi-year partnership with OpenAI, making it the only major Indian IT firm with direct access to ChatGPT’s portfolio.

Apoorv Iyer, global head of GenAI practice at HCLTech, said the tie-up is a turning point and the impact is threefold.

“We were the only large SI chosen after a technical assessment,” Iyer told AIM. “The focus is on capability building, adoption of ChatGPT Enterprise, creating strong technical AI solutions with OpenAI, and taking them to customers in healthcare, manufacturing, and BFSI.”

Iyer said that HCLTech has early access to some of the OpenAI models and is working with them very closely to make sure they are evaluated well and benchmarked for use cases. “We also have a partnership with Anthropic from a cloud model standpoint,” Iyer said.

HCLTech has taken a different route from peers who rely on Microsoft Azure to access OpenAI services. The company works directly with OpenAI’s models, while still maintaining its partnership with Microsoft. This makes HCLTech one of the early adopters of OpenAI, integrating its stack across the company. “We are driving a lot of unique use cases within HCLTech on their models and solutions,” Iyer said.

The AI Revenue Question

While smaller firms like Sonata Software and Happiest Minds are claiming 15–20% of their revenue from AI, HCLTech, Infosys, and others have not yet separated this segment. Iyer explained that, similar to AI washing in India’s IT sector, the same is now true for agentic AI. It’s the current buzzword among the leading IT firms that are developing hundreds of AI agents. 

“I would say a lot of firms started to be early in reporting AI revenue, but there was a lot of AI washing happening in this space,” he added. “The real truth is that AI is everywhere—in every deal, every pipeline.”

Iyer said that calculating revenue from AI is similar to how firms were tracking cloud revenue five years ago. “Today, everything is cloud [revenue]. AI is likely to follow a similar path. Almost all deals now include AI enablement and AI solutioning. Distinguishing what constitutes AI revenue and what does not is vague,” he said.

He noted that there’s a lot of superficial claiming of agency in the field, with people describing simple tasks and labelling them as agents. “It is not really about the quantity of agents, it is about the complexity, quality and adoption of AI within your customer base and enterprise,” he said.

HCLTech is embracing it with products such as UnO, an agent orchestrator, and VisionX, an AI-powered port operations platform. Iyer states that this approach is unique.

Full-Stack AI Play

Apart from OpenAI, HCLTech has also partnered with SAP, NVIDIA, and ServiceNow for joint training and research & development initiatives. 

The company’s offerings are packed into four branded stacks: AI Force, AI Foundry, AI Engineering, and AI Labs. AI Force already has 35 customers and 70 deployments, with HCLTech aiming to reach 200 by next year. “These are all places where customers can come in, build MVPs, and prioritise use cases,” Iyer said.

Furthermore, Indian IT firms are also focusing on extensive internal AI coding. For instance, Cognizant recently ran a vibe-coding week, and Coforge is working with Lovable and Windsurf for its upcoming TechCon conference. Similarly, HCLTech’s approach is to democratise AI beyond just engineers. 

Iyer acknowledged that revenue per employee is inherently nonlinear. “We have already said publicly that nonlinearity is a reality. But the focus is not on reducing employees — it’s on gaining more opportunities and market share.”

The shift is already transforming the IT sector, with changes to structures, skills, and capabilities. Iyer views this as a positive opportunity for industry transformation. 

“You don’t need to be technically savvy to prototype. But vibe coding by itself means nothing unless you can scale to 10,000 users in production,” Iyer said.

On trust and governance, he highlighted HCLTech’s Office of Responsible AI, red-teaming models, and involvement in the EU AI Act and the White House AI plan. The company has even collaborated with MIT on agentic AI. In India, it utilises the Shiv Nadar Foundation and Shiv Nadar University to develop AI talent.

“The pace of AI is very high. We have to be fast-paced, assertive and confident. That’s what will decide whether any company can adapt and continue to be relevant,” Iyer admitted. “We really think hard about how to take things to production and scale and option in the enterprise, so that you get the right ROI.”

The Hard Numbers

Although HCLTech touts its OpenAI partnership and agentic AI capabilities, its Q1 FY26 figures reveal a more challenging reality. Profit fell 9.7% YoY to ₹3,843 crore, while revenue increased 3.7% to ₹30,349 crore. Generative AI deals declined to nine from 12 in the previous quarter.

CEO C Vijayakumar, during the Q1 FY26 earnings call, insisted the AI narrative is landing. “Our propositions are resonating well with clients and have been augmented further by our partnership with OpenAI,” he said. He also pointed out that around 127,000 employees are trained as AI users, including 42,000 with advanced training.

Meanwhile, TCS reported weak growth in the same quarter and talked less about GenAI. And its peer, Infosys, is hedging bets with modular AI and in-house small language models. Wipro, another tech firm in the agentic league, is leaning into AI templates for healthcare and pharma. 

Read: Indian IT’s AI Talks Get Louder as Revenues Go Mute

Regardless, HCLTech, by securing a direct line into OpenAI, has broken ranks. And whether this partnership will pay off in the long run is something to wait and watch as the industry upskills its workforce and embraces the change, by redefining roles, be it software engineering, IT operations, or business processes.

The post HCLTech GenAI Head Calls Out Agentic Washing in Indian IT appeared first on Analytics India Magazine.

Coforge is witnessing an upward move in its growth trajectory as its big bets on generative AI and agentic AI provide a positive momentum. Just this quarter, the company became the seventh largest Indian IT firm posting ₹3,689 crore in revenue for Q1 FY26, a staggering 56.5% jump year-on-year.

Leveraging AI and adapting to the new tech landscape is the main factor driving this growth, according to CEO Sudhir Singh. At the helm of these AI advancements over the last one year has been Vikrant Karnik as the EVP for digital, data, cloud, and AI at Coforge. 

Karnik avoids abstract promises or lofty slogans as he has seen the technology’s hype cycles over decades starting his career from EY to Capgemini to Genpact, and now at Coforge. “I think AI was always seen as something with a lot of potential but that would never come to realisation,” he said in an interaction with AIM.

Karnik is blunt about the influence AI is having on Indian IT. “AI is stripping away layers of ‘fat’ that once masked underperformance, exposing who is actually adding value.”

The Reality Check

AI hype for Karnik is about speed, decisiveness, and delivering measurable outcomes. In his view, some leaders will inevitably be replaced in this shift. The winners will be those that quickly double down on what works. “I expect some experiments to fail — perhaps four out of ten — but the winners will be those that double down quickly on the six that work,” he said.

According to him, the Transformer architectures and GPT models convinced enterprises that AI could be both valuable and practical, but India presents unique challenges.

With low labour costs, automation doesn’t create the same shareholder value argument as in high-wage economies. “It’s a little bit like asking a hotel to list electricity as a revenue line,” he said. “We’re here to deliver shareholder value for our customers. If AI helps us do that, we’ll use it.”

Despite that, he points to bright spots — such as a large Indian bank that has become one of Coforge’s strongest AI case studies. In Southeast Asia, some of the most complex AI deals involve custom infrastructure and distilled models, which then become examples for Western clients.

From Ghost Pilots to AgentSphere

Coforge has worked with machine learning for over seven years and with generative AI and agentic architectures for more than three. One recurring problem was the “ghost pipeline” — pilots that never make it into production. 

Research with a partner agency showed that pilots with clear business outcomes were three to four times more likely to be deployed.

That principle led to the creation of AgentSphere, a catalog of over 100 AI agents. It wasn’t a product born out of marketing ambition, but from client needs. “We are an engineering company at heart,” said Karnik. “We specialise at the intersection of domain and engineering.”

One client, a company that supplies construction materials, struggled to help seasonal sales associates navigate a 57,000-item catalog. Even with generative AI and RAG, results weren’t accurate enough. 

Coforge built an agentic architecture instead, which revealed the need for a centralised “agent catalog” to manage agents across Salesforce, service systems, and in-house tools. 

The company also launched Forge-X, an AI-powered delivery platform designed to accelerate application development and modernisation across client portfolios.

When it comes to AI, Karnik categorises customers into three groups. First are specific-need clients who know exactly what they want built. Second are the explorers who suspect value in a cumbersome workflow and want to reimagine it.

And the last group are the transformers with executive mandates for large-scale change, such as improving EBITDA by hundreds of basis points. For this, trust is key. Karnik recalls a case where Coforge wasn’t the client’s largest tech provider — Capgemini and Cognizant were involved — but was still chosen for cost-transformation work.

Vibe Coding and Quasar

Like many IT firms, Coforge is experimenting with AI-driven coding. Cognizant, for example, aims to generate 50% of its code with AI within a year, and has already trained 35,000 developers on GitHub Copilot. 

Coforge has tested tools like Cursor and Windsurf, building a secure setup for its internal TechCon conference where engineers could describe applications and have them generated by on-premise LLMs.

“We didn’t just connect to public LLM APIs,” Karnik explained. “The minute you use an external model, your code is going outside. We wanted something customers could run in their own environment.”

This approach led to Quasar, launched in May last year. Powered by 23 LLMs — including OpenAI’s GPT models, Google’s Gemini, and open-source alternatives — it enforces 90 coding rules to keep AI-generated code maintainable. Coforge often starts with Mistral’s CodeStral for performance reasons but tests new entrants, including OpenAI’s recently open-sourced models.

Clients, such as a large specialty insurer, have also used Coforge’s environment to run secure AI hackathons. “The point isn’t to sell products — it’s to show what a real, working framework looks like,” Karnik said.

With AI and automation, IT firms are debating whether to stick to headcount-based billing or move to outcome-based models. For Karnik, the answer is simple: “If we deliver more, we will grow. If we deliver less, we will shrink.”

The post Coforge’s AI Reality Check for Indian IT to ‘Strip Away the Fat’ appeared first on Analytics India Magazine.

At a time when automation is steadily eating into jobs and revenues are slowing across the Indian IT sector, chief executives continue to draw exorbitant pay packages, many of which rise year after year.

C Vijayakumar is reportedly walking away with the biggest paycheque among his peers in the country’s top IT firms. While the HCLTech CEO is already the highest-paid executive among the top five such companies at ₹94 crore, his remuneration is expected to go even higher. 

Starting September 1, as he begins a third term as CEO and MD, he will draw an annual salary of ₹154 crore (~$18.6 million)—a staggering 71% jump over his current compensation.

Moreover, over the next five years, Vijayakumar is also set to receive long-term incentives worth $8.82 million, linked to the company’s business performance.

The announcement comes as HCLTech, which posted 4.3% revenue growth to $13.8 billion in FY25, continues to outpace its peers. This marks the company’s second consecutive year as the fastest-growing IT firm among the top five Indian players. On the AI front, the company has also formed a partnership with OpenAI, which distinguishes it from its peers.

The board attributed Vijayakumar’s reappointment to his “superior financial execution” and “commitment to long-term value creation”.

Meanwhile, TCS is trimming its workforce by 2% and Infosys has projected its slowest growth in a decade. The $283 billion IT sector is undergoing a period of transition, and not every player is making it through with equal success.

Among the leaders, Infosys CEO Salil Parekh ranks next after Vijayakumar, earning ₹80.62 crore following a 22% pay hike. He oversees a considerably larger company, generating $19.28 billion in revenue. 

In contrast, despite heading India’s largest IT firm with $30.18 billion in revenue, TCS boss K Krithivasan is the lowest-paid CEO among the top five players, drawing ₹26.5 crore.

Wipro’s Srinivas Pallia and Tech Mahindra’s Mohit Joshi each took home roughly ₹54 crore in annual pay, with Joshi standing out as the youngest among the lot at 51.

Notably, the executives’ stock holdings reveal another layer of disparity. Parekh’s stake in Infosys is valued at approximately ₹175 crore, while Vijayakumar’s HCLTech shares are worth around ₹98 crore. Krithivasan’s holdings in TCS amount to just ₹3.4 crore, considering that the company does not offer ESOPs.

The Mid-Cap Millions

The spotlight is increasingly turning to mid-sized IT companies, not solely for their growth. Their CEOs are quietly emerging as some of the highest-paid leaders in the sector.

At the top of that list is Sandeep Kalra, CEO of Persistent Systems, who earned ₹148 crore in FY25, narrowly behind Vijayakumar. The bulk of his compensation came from a one-time stock grant issued at the time of his appointment. Yet, even excluding this, his salary is significantly higher than that of several CEOs running much larger firms.

Close on his heels is Sudhir Singh of Coforge, whose FY25 compensation totals ₹105 crore—more than double the compensation of the TCS chief. Coforge has had a breakout year—revenues are up, profits have doubled, and its AI-first strategy is being rewarded on the bourses and at the boardroom table.

Nitin Rakesh, the long-time CEO of Mphasis, earned ₹59.2 crore this year, slightly ahead of his peers at Wipro and Tech Mahindra. His pay package includes a mix of long-term incentives and bonuses tied to new deal wins and operating margins.

Amit Chadha, CEO of L&T Technology Services (LTTS), drew ₹18.1 crore. While modest in this context, it’s still up from the previous year and includes a healthy mix of salary, bonus and stock grants, especially notable in a year when LTTS reported only flat profit growth despite strong revenues.

Not far away in the rankings is Samir Dhir, CEO of Sonata Software, who took home ₹14.3 crore—modest when compared to the others, but reflective of the company’s current scale. Sonata has made strides in product engineering and digital transformation, and Dhir’s pay has been aligned with targets set during the firm’s recent pivot towards platform-led offerings.

In the business process management space, WNS Holdings’ Keshav Murugesh earned ₹22.8 crore this year, making him one of the most well-compensated leaders in the non-IT services space. His package reflects both longevity and consistent delivery in a segment of the tech industry that rarely commands the spotlight.

Worker Pay Tells Another Story

While executive compensation packages hit record highs, employee salaries tell a more complicated story. HCLTech did raise its median employee salary by 17.63% in FY25, up from 7% the previous year. But at Wipro and Tech Mahindra, median pay actually dropped, citing revenue dips and headcount reduction.

TCS, which employs over six lakh people, granted a 7.5% raise, down from last year’s 9%. Infosys offered a 9.63% increase.

On the other hand, Tech Mahindra, which saw a revenue dip of 0.21%, slashed median salaries by more than 6%, while Wipro cut overall employee compensation by 0.6%.

The numbers reveal a clear and growing divergence: top executives are being rewarded as if they’re in a bull market, while much of the workforce is working through a slowdown. For an industry built on the strength of its talent, the message is hard to miss—AI may be the new engine, but the rewards are being driven to the front of the plane.

That wave is lifting the boardroom a lot higher than the rest.

The post Indian IT CEOs Keep Getting Richer, Even in the Mid-Tier appeared first on Analytics India Magazine.

July witnessed significant activity in the AI acquisitions space. Notable among these was the high-profile $2.4 billion transaction involving OpenAI, Cognition, and Windsurf. However, developments extended even into the services industry, marked by a substantial deal with noteworthy implications for the Indian IT sector.

Paris-based Capgemini announced the acquisition of WNS for $3.3 billion in cash. This move goes far beyond a typical BPO deal; it’s a bet on agentic AI, and yet another wake-up call for Indian IT firms, many of which are sitting on billions of dollars of idle cash. 

As of June, India’s five largest IT services firms, namely TCS, Infosys, Wipro, HCLTech and Tech Mahindra, collectively hold over $20.6 billion in cash and investments. 

TCS leads the pack with $5.6 billion, followed closely by Infosys at $5.33 billion and Wipro at $4.61 billion. Meanwhile, HCLTech sits on $3.16 billion, while Tech Mahindra holds $1.9 billion. 

That’s more than ₹1.7 lakh crore in financial firepower—yet merger and acquisition (M&A) activity remains timid at best.

Despite an 18% increase in M&A volume in India during 2024, the overall value of those deals dropped, reflecting an industry that prefers safe bets over bold moves. Most acquisitions were mid-sized, quiet and private. 

No Interest at All

HCLTech CEO Vijayakumar C had emphasised back in February that AI’s disruption in IT services is unlike previous technological shifts such as cloud computing and digital transformation. He warned that Indian IT firms must become increasingly “paranoid”.

“The changes AI is assuring are very different, and we need to be more proactive to even categorise our revenues to create completely new businesses,” he said. 

HCLTech is slowly moving in that direction, as it announced its biggest partnership yet with OpenAI to deliver AI services for its clients. Yet, arguably, that’s not enough. 

This cautious approach has become characteristic of Indian IT firms as they choose to either develop AI capabilities in-house, which takes a lot of time considering it is stuck with PoCs, or partner with AI startups for the same. In the end, these efforts rarely translate to anything beyond modest revenue contributions.

In sharp contrast, the Capgemini-WNS deal shows confidence in the long-term value of domain-specific knowledge, process excellence and scalable AI integration. 

Indian IT majors shy away from such strategic bets while sitting on single-digit growths since 2023. That mindset, many believe, needs to change.

Ramkumar Ramamoorthy, partner at Catalincs and former chairman and MD of Cognizant India, believes Indian IT is sitting on a generational opportunity—and might just sleep through it. With revenue growth stuck in the low-to-mid single digits for a second consecutive year, he argues it’s time the industry put its sizeable cash reserves to more strategic use.

“It is estimated that the Indian IT services companies generate approximately $20 billion in free cash flow and more than 75% of that is returned to shareholders,” he wrote in a LinkedIn post. This money, Ramamoorthy insists, could do more than just reward investors. 

He proposes two ambitious ideas: first, Indian IT could act like venture capitalists.

“Could they use their substantial cash flows as ‘risk capital’ (akin to what Alibaba or Tencent did) to take minority stakes in promising next-gen companies that are into products, platforms, deep tech and more?” he asked rhetorically, while adding that Indian IT’s leadership and operational expertise would make them ideal mentors for startups.

Next, he calls for a coalition of cash-rich IT firms to build India’s own tech infrastructure and invest in building the country’s own compute, AI, cloud, and cyber infrastructure, thereby benefiting from it. He also challenges the conventional view that IT services don’t need significant reinvestment due to their asset-light model. 

“While this reasoning holds, the landscape is changing…Isn’t now an opportune moment for companies to capitalise on these shifts by reinvesting in the business and leaping into the future instead of playing by yesterday’s rules?” he asked.

Time to Go Big

The risk, Ramamoorthy warns, isn’t just about missing out on big returns. It’s about missing the future. 

“If we don’t act now, we risk looking back in regret for having missed a generational opportunity. Worse still, we may find ourselves caught in ‘techolonisation’—a future of dependency on others for our technology needs and opportunities!”

This is exactly the kind of transformative plays needed in the age of generative AI and automation. During the acquisition announcement, Aiman Ezzat, CEO of Capgemini, said that WNS will provide the group with the scale and vertical sector expertise with agentic AI-powered intelligent operations focusing on the US market. 

It seems increasingly evident that while global peers like Accenture, ServiceNow, and now even Capgemini are aggressively acquiring AI-ready assets and process IP, India’s top tech companies remain curiously passive, sitting on piles of cash with little intention to deploy it strategically.

This year, ServiceNow acquired Moveworks for $2.5 billion and Logik.ai specifically for generative AI and agentic AI capabilities. Accenture, with its billion-dollar AI deal pipeline, has acquired Halfspace, announced plans to acquire Yumemi, and invested in YearOne this year alone just for AI capabilities.

Cut to their latest earnings call—AI now accounts for a significant share of their revenue. 

Even Cognizant is slowly reinventing itself as a ‘vibe coding’ company with increasing collaborations with Lovable and Windsurf and running one of the largest AI hackathons using AI tools. LTIMindtree, however, invested $6 million in Voicing AI in December 2024 for AI capabilities, but showed little momentum since.

No one’s expecting Indian IT to take reckless risks. However, when even companies like Cognizant begin to resemble startups, while many Indian IT firms remain cautious, it stresses a gap in approach. 

As Ramamoorthy suggested, if these firms don’t start acquiring talent, instead of simply billing hours, they could risk losing relevance within the next decade.

The post Indian IT Sits on $20 Bn Cash as Accenture, Capgemini Keep Buying AI Startups appeared first on Analytics India Magazine.

As client expectations evolve, IT firms are moving beyond traditional business process outsourcing (BPO) to embrace platformisation – provision of wider services under a common platform. Enterprises today are no longer satisfied with siloed services. They seek integrated, intelligent solutions that deliver automation, agility, and measurable business impact.

This shift is not just strategic but necessary. The $3.3 billion acquisition of WNS by Capgemini in July 2025 reflects a growing market demand for end-to-end digital transformation capabilities that extend far beyond implementation. Similarly, Infosys launched Cobalt as a cloud-first, AI-enabled suite for companies and clients to accelerate digital transformation. 

Technological and Financial Necessity

Varun Goswami, global head of product and AI at Newgen Software, emphasised that being product-native has become central to how modern platforms create value. He said, “Product-native approach creates two key advantages: firstly, from a go-to-market lens, it enables the delivery of ready-to-deploy, industry-specific solutions that address real-world challenges, and secondly, from a technology perspective, it ensures performance, scalability, and resilience, without over-reliance on the shifting landscape of native AI stacks.” 

To Goswami, being AI-first and product-native is no longer a choice; it is what organisations need to drive meaningful, future-ready transformation.

M&As Reshape the IT-SaaS-BPO Landscape

The convergence of BPO, SaaS and large IT services firms is picking up pace as enterprises shift how they consume technology and transformation services. 

According to Goutham Parcha, vice president, application development, Pegasystems India, this shift is driving a new era of strategic mergers, where SaaS and BPO companies are increasingly becoming integral components of global IT services offerings. He noted that this trend is only set to intensify. “In the coming years, we can expect this trend to deepen further. Strategic acquisitions, ecosystem alliances, and even co-innovation models will become more common, as firms look to accelerate time-to-value for clients and defend margins.”

A key factor accelerating this evolution is the emergence of intelligent agents, which have the potential to upend traditional BPO models. SaaS companies, Gautham believes, are in a strong position to lead this disruption by offering automation solutions driven by intelligent agents. 

Sarat Varanasi, practice leader – insurance analytics, AI services and platforms at EXL,  echoed a similar sentiment.“Domain expertise is becoming critical for deploying AI and agentic AI solutions effectively. As a result, domain-rich BPOs are increasingly attractive to IT giants seeking to enhance workflow IP, GenAI capabilities, and operational depth,” he said.

Varanasi added that going forward, SaaS providers are likely to build their own delivery arms, while BPOs will work to embed AI more deeply into their workflows further blurring the traditional boundaries between these sectors.

Backward Integration Isn’t the Future

With regard to this growing trend and its impact, Parcha noted, “Backward integration of SaaS platforms into traditional outsourcing models is unlikely to align with market trends. Instead, value will come from platforms that are intelligent by default and resilient by design, reducing reliance on labour intensive processes.”

He said that SaaS platforms are expanding their capabilities by embedding automation, workflow orchestration, and predictive AI directly into the product, minimising dependence on people-heavy service models while ensuring consistent, high-quality outcomes.

The Big IT Bottleneck

Big IT firms are navigating multiple hurdles as they shift from services-led models to product-native and AI-driven operations. 

Varanasi outlines the key roadblocks as “legacy models, talent gaps/upskilling, lack of product IP, ecosystem limitations, data preparedness for AI adoption, and change management.”

Many firms are still tied to outdated contracts that slow progress. As he noted, “We believe we will have people working on AI or with AI. However, leading pure-play IT firms can be constrained by legacy IT contracts that need to be cannibalised to enable AI adoption. This has resulted in a slower pace of innovation.”

In contrast, domain-led digital operations firms are moving faster. “With their domain expertise,” he added, “they’ve enabled faster implementation of AI/GenAI, accelerated product development, and reduced time-to-market.”

Parcha pointed out the strain on old systems: “These systems are difficult to replace, expensive to maintain, and do not easily connect with modern technologies.” This complexity increases cost and delays, while also creating “technical debt, so companies get stuck using most of their resources keeping them running instead of moving forward.”

Beyond infrastructure, internal collaboration is another critical barrier. “Another challenge is that teams often work in silos, making collaboration and integration of new tools difficult. It slows decision-making and the need for rapid product innovation,” said Parcha. Security is also emerging as a serious concern: “Older platforms can be more vulnerable to cyber threats and are harder to keep compliant with fast-changing regulations.”

Strategies for AI- first Startups

The most successful AI-first startups will be those that build deep, domain-specific solutions, rather than relying on generic tools. Varanasi emphasised, “The real opportunity lies in moving beyond generic tools to deliver workflow-embedded, domain-specific solutions.” As horizontal SaaS models become increasingly commoditised, startups will need to differentiate by delivering measurable business impact.

“As horizontal SaaS rapidly commoditises, the future belongs to IP-rich platforms that directly enhance client KPIs and deliver measurable business value,” he noted.

While many emerging startups are focused on areas like data annotation, customer service, or call centre automation, lasting value will come from embedding AI into core operational workflows.

In this context, digital operations providers have a built-in advantage. “Digital operations providers hold a distinct advantage due to their domain expertise and process knowledge, positioning them well to co-create verticalised, AI-native SaaS models,” said Varanasi.

He also pointed out a critical industry dynamic. “AI commoditises faster than service delivery changes. Winners will own use-case outcomes (claims processing, billing, underwriting).” The edge, he suggested, lies in mastering outcomes that align directly with client business goals.

The post How Product-Native IT Models Are Reshaping Enterprise Tech appeared first on Analytics India Magazine.

“The Sholay days of ‘Kitne Aadmi The’ for the Indian IT sector are over,” quipped CP Gurnani, former CEO of Tech Mahindra, in a recent interview. His statement sums up a shift underway in the industry–a move away from valuing manpower to valuing outcomes, driven by AI. 

This change is vividly portrayed by Genpact, a global technology and consulting firm. Like most enterprises, Genpact is in the early stages of its agentic AI journey and is strategically aligning its business model. The company is transitioning from a traditional full-time equivalent (FTE) model, where clients are billed based on the number of people assigned to a project, to a service-oriented, outcome-focused approach. 

This new model leverages agentic AI to deliver results, fundamentally changing how value is created and measured. 

The shift is not happening in a vacuum. It reflects broader industry trends, exemplified by moves at tech giants like Tata Consultancy Services (TCS).  Against the backdrop of AI driver transformation, TCS is reportedly planning to reduce its workforce by 2% by 2026, impacting nearly 12,000 jobs primarily at the middle and senior levels. 

The company has stated it is undergoing a significant overhaul that includes strategic initiatives in new markets and the large-scale deployment of AI for its clients, signalling that efficiency and tech-led delivery are now paramount.

The philosophy behind this industry-wide change was articulated by Gurnani in his interview with CNBC. “I think all of us will have to rewire ourselves to start looking at output- and outcome-based business models, outcome-based pricing,” Gurnani said. 

“More importantly, looking at what it does for the business or what it does for the customer’s customer, instead of looking at IT and systems in isolation.” 

Industry analysts are putting a name to this new paradigm. Saurabh Gupta, president of research and advisory services at HFS Research, calls it “Services-as-Software (SaS).” 

He had earlier described it as a transformative model where delivering outcomes no longer depends on traditional, manpower-intensive services but is driven primarily by advanced technology, reducing human intervention and maximising efficiency. 

Meanwhile, Jinsook Han, chief strategy, corporate development, and global agentic AI officer, said that at Genpact, this shift is made possible by combining AI and domain-specific human experts. 

“What we’re doing is combining domain-specific small and large language models with expert people into what we call agentic solutions,” she said, in an exclusive interview with AIM.  

Han further added that these solutions, offered as SaaS 2.0, blend pre-trained agents, years of domain knowledge, and compliance-aware exception handling, providing clients with modular services across finance, supply chain, insurance, and more.

“The people in the agentic world are highly trained to work with agents and make sure that it’s driven through the outcome, in addition to what they were doing before,” Han added. 

She noted that, with agentic AI in enterprise environments, the company is already experiencing revenue growth, despite productivity gains and discounts passed to clients.

The market expectation is that if you offer agentic AI, clients will ask for discounts and are used to paying based on that. However, Han said, amidst this, the company has defied that expectation and is expanding its revenue stream. 

While large-scale AI deployment remains in its early stages globally, Genpact is reportedly seeing measurable gains. Han said the company reported a 3% growth even as some investors remained sceptical about the financial impact of automation-led transformation.

In the first quarter of 2025, Genpact reported net revenue of $1.215 billion, marking a 7.4% increase compared to the same period last year.  

For the second quarter of 2025, the results, which will be announced on August 7, the company expects net revenues to be between $1.210 billion and $1.233 billion.  It would reflect a year-over-year growth of approximately 2.8% to 4.8% on a reported basis. On a constant currency basis, the company projects growth in the range of 2.5% to 4.5%.

Genpact is deploying agents across industries, including finance, supply chain, insurance, healthcare, retail, manufacturing, and media, and plans to expand further.

Moving Beyond Headcount Metrics

The company recently launched Genpact’s AP Suite, an AI-agentic solution built to automate the entire accounts payable (AP) workflow. It combines deep finance domain expertise with Microsoft Azure’s AI stack to deliver goal-oriented autonomy across invoice processing, anomaly detection, and vendor communication. 

The suite comprises four primary modules: AP Capture for smart data extraction, AP Advance for complete invoice processing, AP Trace for identifying fraud and errors, and AP Assist, a GenAI-powered helpdesk that handles supplier queries via conversational interfaces. 

Han said the solution is available on Oracle and will soon be available on Workday. She further added that Genpact deployed the Accounts Payable (AP) solution internally before offering it to clients, calling itself Client Zero. 

“Even with our already efficient process, we saw a double-digit reduction in headcount and throughput improved anywhere from 30% to 70%,” she claimed. Notably, the company’s agentic AP Suite agents now handle more than 70% of Genpact’s invoices and payments.

Human in the Loop

Genpact’s AI Gigafactory accelerates product development and scaling, utilising a proprietary code generator called Cora Code Geny. Agents created at the Gigafactory are delivered more swiftly and are utilised both internally and externally.

Han clarified that AI coding tools manage the basics, but human oversight remains crucial. Senior engineers review, fill gaps, and ensure smooth operation. She said, “Machines break, and no one can predict when.” 

She added that even well-performing models can unexpectedly break due to new environments or variables. So, Genpact monitors 24/7 using dashboards, action boards, and signal boards to detect anomalies.

To enable this transformation, Genpact is investing heavily in upskilling. Employees go through layered training programs using external resources, internal platforms like Genome.ai, and account-specific assessments.

The post Genpact Ditches Headcount Model for Outcome-Focused Approach appeared first on Analytics India Magazine.

Another quarter goes by, and mid-sized IT firms are once again outshining the traditional heavyweights. Persistent Systems, Coforge, Mphasis, LTTS, and even Tech Mahindra are doing what the Big Four—TCS, Infosys, Wipro, and HCLTech—can’t seem to manage: deliver growth backed by real AI traction. 

Just like in Q4 FY25, the pattern in Q1 FY26 is unmistakable. The midcaps are no longer trying to catch up—they’re pulling ahead.

Take Persistent Systems, for instance. The company reported ₹3,333 crore in revenue this quarter, up nearly 22% year-on-year. Profits surged nearly 39% to ₹425 crore. In dollar terms, the revenue stood at $389.7 million, up 18.8% from last year. 

This growth isn’t a one-off. Persistent has now clocked 21 consecutive quarters of double-digit year-on-year revenue growth. It’s doing what the giants no longer can.

The company’s Total Contract Value (TCV) for the quarter stood at ₹4524.55 crore ($520.8 million), with Annual Contract Value (ACV) at ₹3347.37 crore ($385.3 million). Its top 10 clients still contribute 42% of revenue—a sign that large accounts are sticking around. 

The number of clients delivering more than $5 million (about ₹43.44 crore) annually also inched up, showing a steady climb in customer value.

CEO Sandeep Kalra attributed the company’s success to its platform-driven AI strategy. Founder Anand Deshpande said that their early investments in AI—not vague promises, but actual tech embedded in deals—are now paying off. 

Coforge Beats Everyone All Together

Coforge is on an even sharper trajectory, becoming the seventh largest IT firm. The company posted ₹3,689 crore in revenue for Q1 FY26, a staggering 56.5% jump year-on-year and 8.2% sequentially. 

Profits more than doubled, rising 138% over last year. While others talk about AI potential, Coforge is building actual platforms like AgentSphere, a library of over 100 AI agents targeting pain points in travel, BFSI, and healthcare. 

CEO Sudhir Singh is clear about where the company is headed, and it’s not towards speculative use cases. The company signed five large deals this quarter, and its order book for the next twelve months is up 46% from a year ago.

Meanwhile, Mphasis might not have delivered the same top-line fireworks, but it booked the highest TCV in eight quarters— ₹6602.65 crore ($760 million)—with 68% of those wins being AI-led. Revenue growth was modest at 0.4% sequentially and 9.2% year-on-year. But that’s not the story. 

The real narrative is about execution. CEO Nitin Rakesh made it clear that their early push into AI has begun to translate into client wins across the board. Mphasis is already deploying AI to overhaul platforms in areas like wealth management, not just experimenting with proof-of-concepts.

Hexaware posted modest growth in the second quarter of calendar year 2025. However, a sharp rise in one-off costs and slower-than-expected deal momentum weighed heavily on margins.

The company reported Q2 revenue of ₹3,260 crore ($382.1 million), marking a sequential growth of 1.6% in INR and 2.8% in USD. Year-on-year, revenue was up 11.1% in INR. That said, the tepid quarter-on-quarter increase has raised concerns about growth saturation.

Margins also took a hit, dropping to 12.4% from 16.5% in Q1 and 14.7% in Q2 last year. The company attributed the decline to a steep jump in other expenses, which rose to ₹142 crore from just ₹8.7 crore a year ago.

L&T Story

L&T Technology Services (LTTS) reported ₹2,866 crore in revenue this quarter, growing 16.4% year-on-year. While the top line impressed, profit growth remained muted at just 0.7%. Margins slipped due to cost pressures, but the company’s deal flow and innovation efforts are anything but sluggish. 

With a $50 million deal and several more in the $10–$30 million range, LTTS is clearly expanding its base. The launch of its proprietary PLxAI framework and a new AI and cybersecurity-focused design centre in Texas shows that it’s not just talking about the future—it’s building for it.

When it comes to LTIMindtree, the story is similar to LTTS. The firm reported a revenue increase of 0.7% quarter-on-quarter (QoQ) and 7.6% year-on-year, reaching ₹9,840.6 crore, while net profit rose 11.2% QoQ to ₹1,254.6 crore.

“We had a promising start to the year delivering broad-based growth, expanding margins, and making significant progress on our strategic priorities,” Venu Lambu, CEO and managing director of LTIMindtree, said. He attributed the growth to ongoing sales transformation, the adoption of AI, and operational discipline.

In this quarter, LTIMindtree also launched BlueVerse, a new business unit offering 300 specialised AI agents across industries and functions to help companies adopt and scale AI across operations.

Tech Mahindra Sees Profit Growth

Tech Mahindra, which had struggled in recent quarters, reported a strong 34% year-on-year growth in net profit. Revenue grew slightly at 2.7% to ₹13,351 crores, largely due to client delays, but the profit spike signals improved internal discipline. 

The company booked ₹7,028 crore ($809 million) in new deals and deployed over 200 AI agents. CEO Mohit Joshi remains bullish on a hybrid model where humans and AI agents collaborate at scale, and it seems to be working, at least on the margin front.

Speaking of which, strong margin expansion and robust deal momentum kept the narrative optimistic. “We have delivered seven consecutive quarters of margin expansion, a clear reflection of the discipline and focus across our organisation,” said Rohit Anand, CFO, highlighting the success of Project Fortius in driving operational efficiencies even in an uncertain environment.

The project is envisioned to improve its operating margin to 15% by the end of fiscal year 2027.

The Not so Big Four

Compare this to the Big Four, and the contrast couldn’t be starker. Wipro may have doubled its large deal bookings to ₹23,456.8 crore ($2.7 billion) and rolled out over 200 enterprise AI agents, but its topline declined by 2.3% in constant currency. 

TCS posted a 1.3% revenue growth, but that’s where the good news ended—constant currency revenue declined by 3.1%. The company’s TCV dropped significantly, and whatever AI revenue it once claimed to be building has now conveniently disappeared from earnings calls. 

HCLTech had one of the loudest AI quarters in terms of announcements with its partnership with OpenAI. But revenue barely moved, and profits dropped nearly 10% from the previous year.

Infosys claims to have built 300 AI agents and that is the driver for the revenue growth. The company reported a profit of ₹6,921 crore for Q1 FY26, an 8.7% increase year-on-year and a revenue increase of 7.5% QoQ to INR 42,279 crore. But the performance was still mellow when compared to smaller firms.

The problem with these giants isn’t just that they’re moving slowly. It’s that the numbers no longer back the story. Everyone is talking about AI being “part of every deal,” yet no one is willing to break down what that actually means in revenue terms. 

In contrast, mid-sized Indian IT firms are more focused, more agile, and more realistic about their strengths. This pivot began last year when firms like LTIMindtree invested in startups like Voicing AI and partnered with GitHub to roll out Copilot for developers. 

Mphasis launched NeoCrux to enhance developer productivity. Persistent acquired a privacy-first AI consultancy, Arrka. These moves were small but strategic. They’re already showing up in revenues, deal wins, and client stickiness.

The Indian IT landscape is no longer just about size. It’s about speed, clarity of execution, and willingness to bet on the future without being paralysed by legacy models.

The post AI ROI is Better for Coforge, Persistent, Mphasis, L&T than the Big Four Indian IT appeared first on Analytics India Magazine.

The first quarter of FY26 was a challenging period for Indian IT giants, including TCS, Wipro, and HCLTech, with some reporting a drop in revenue and others recording single-digit growth. However, beyond the revenue figures, the focus on AI might be overshadowing the broader story of these firms.

According to a report by Moneycontrol, TCS plans to reduce its workforce by 2% by 2026. This would impact 12,000 jobs primarily at the middle and senior levels. “It has not been an easy decision and one of the toughest decisions I have had to take as CEO,” TCS CEO K Krithivasan said, while adding that AI is not the complete reason for the layoff.

The company also mentioned that it is undergoing a significant overhaul, which includes strategic initiatives in new markets and the deployment of AI at scale for its clients. 

TCS attrition ticked up to 13.8% in Q1 FY 26 from 13.3% in the prior quarter.

AI is finally catching up with India’s 30-year-old IT business model, which has been primed for disruption ever since ChatGPT entered the scene. 

In the US, the impact has been swift, and several leading tech companies started layoffs late last year. Over 50,000 jobs have vanished this year as giants like Meta, IBM, and Microsoft have reduced their workforces, fueled by AI, cost-cutting measures, and the cancellation of Federal contracts. 

The $200 Million AI Question

Besides the layoff, which is relatively small compared to its overall workforce of 6,13,069 employees, the company’s significant drop in ‘cost of equipment and software licences’ expenditure, the narrative around GenAI and AI-led productivity gains suggests AI is in action. 

Typically, AI adoption increases software and infra costs due to GPU provisioning, LLM API usage, and onboarding of new development tools and platforms. 

But the software license expenses reduced from ₹2,748 crore in the previous quarter to just ₹726 crore now, according to TCS’s latest quarterly financial statement. 

Queries sent by AIM to TCS regarding this notable decrease remained unanswered. However, during the earnings call, CFO Samir Seksaria clarified that the drop was due to a completed transformation deal, not AI. 

Read: AI Coding Could Be Indian IT Engineers’ Biggest Threat

The company’s COO, Aarthi Subramanian, had earlier said that AI for modernisation is emerging as a strong theme. “GenAI is now becoming the tool to really understand the legacy code and use GenAI to convert and forward engineers to a modernised architecture and application,” she had said. 

Subramanian added that productivity gains are visible in coding, but software is much more end-to-end, right from conceptualisation all the way to testing and delivery. 

However, the company attributes margin increases to deal closures and policy changes, not automation.

Read: Indian IT ‘Should Be Paranoid’ About AI & Ditch its 30-Year-Old Business Model

Agentic AI is at the Core

Also, TCS did not disclose any major wins related to generative AI this quarter, nor did it specify its GenAI revenues, despite revealing a $1.5 billion GenAI pipeline in Q1 FY25. But the company showcased new platforms, including SovereignSecure and DigiBOLT, both of which are positioned as scalable, AI-native frameworks. 

“We have already built agents, and many are in the roadmap,” said Subramanian during the earnings call. “Clients are increasingly shifting their focus from use case-based approach to ROI-led scaling of AI.”

She added that agentic AI is becoming an integral part of all client conversations across various sectors, including BFSI and manufacturing. Subramanian further noted that the shift from experimentation to production has begun, and AI revenues have grown.

Read: Indian IT’s AI Revenue is Still 2–3 Years Away 

Meanwhile, addressing the talent acquisition and attrition, Milind Lakkad, the outgoing CHRO, said: “Talent Development is core to TCS. In this quarter, our associates invested 15 million hours in building expertise in emerging technologies, enabling them to lead the transformation journey for our customers.”

He added that over 114,000 employees are now equipped with ‘higher-order AI skills’. The company did not quantify how this would translate to revenue, productivity, or delivery improvements.

TCS also rolled out a more aggressive bench policy, mandating 225 billable days per year, with only 35 days of allowable non-billable time. The company attributed this to automation and client demand for faster, AI-led delivery.

That’s a subtle but telling shift: clients no longer want just headcount. They want outcomes delivered at AI speed.

Krithivasan had said that TCS is “comfortable” with the deal volume in Q1. But comfort doesn’t necessarily translate to confidence. “It could be too early to call out when growth will resume,” he added. 

The post TCS to ‘Layoff 2% Workforce’,  Software Spend Down by $200 Mn Amidst AI Overhaul appeared first on Analytics India Magazine.

Unlike other IT companies that incorporate hundreds of AI agents into their services, Cognizant has chosen a different approach. Apart from the multi-agent approach, the company is integrating ‘vibe coding’ as a key part of its broader AI-driven strategy. 

“Vibe coding is emerging as a key catalyst in this journey, empowering everyone—from seasoned developers to those who have never written a line of code—to build, solve, and innovate with the power of AI at their fingertips,” a Cognizant spokesperson told AIM in an email response. 

The idea is simple but radical. CEO Ravi Kumar S, in a conversation with Lovable CEO Anton Osika, said that anyone, not just software engineers, should be able to build software using natural language. And machines, not humans, should write most of the code.

“I’m a big believer that we could produce more by democratising it [technology], and I’m hoping my software development community gets more productive using levelling,” Kumar said in the podcast, when Osika asked him how the company is using Lovable in their latest vibe coding journey. 

Cognizant aims to generate 50% of its code using AI within a year and states it has already achieved 20% of that target.

The company has already trained 35,000 developers on GitHub Copilot through its Synapse skilling program and plans to train an additional 40,000 developers.

“At Cognizant, we are harnessing AI to reimagine our company and equipping our associates with AI fluency, a gateway to new capabilities, roles, and opportunities,” the company stated. 

‘Vibe Coding is Serious Business’

In a recent blog, Cognizant discussed the Windsurf acquisition by Cognition and cited Andrej Karpathy, stating that by embracing the vibes and ignoring the code, it has made coding accessible to all.

But this isn’t just about making engineers more efficient. Cognizant is trying to change who gets to write software in the first place. 

I’m hoping to introduce more non-STEM disciplines into software development cycles,” Kumar added. “We have too many engineers trying to write code for the world. I want people with a sense of diversity. I want an anthropologist, sociologist, or even a psychologist to code.” 

The goal is to address the increasingly diverse, complex, and real-world problems that Kumar describes. “It’s all driven by software. We aim to be a pioneer in this area.” 

Software should not be the exclusive domain of computer science graduates. With tools like Microsoft Copilot and Cognizant’s own open-source Neuro platform, even a liberal arts graduate should be able to build functional prototypes by telling an AI what they want.

To prove the point, Cognizant is launching a company-wide event called Vibe Coding Week on July 30. This isn’t a small side project.

All Cognizant associates will participate in hands-on workshops with AI coding assistants, explore a prompt engineering toolkit, join best-practice sessions, and participate in innovation competitions, engaging with AI experts and thought leaders.

This is in line with Cognizant’s announcement in 2023 of investing $1 billion in generative AI over three years covering people, partnerships, platforms, and M&As.

What about Business?

One of the key components of Cognizant’s infrastructure is the previously mentioned Neuro AI Multi-Agent Accelerator. This framework helps teams build networks of AI agents to handle tasks ranging from code writing to testing, deployment, and even documentation. 

Neuro was open-sourced in May 2025, and several developers have already forked the codebase.

In many ways, this approach is about increasing volume and speed. Cognizant aims to make software development more industrialised—producing more code, more quickly, with a larger team. Yet, there’s also a meaningful change happening beneath the surface. 

Highlighting their recent research, Cognizant stated that business leaders recognise there is work to be done before fully capitalising on the vibe coding opportunity. 

“Even while 94% of senior leaders feel they’d lose out on productivity gains if they didn’t adopt AI, only 43% said they have established formal policies, procedures and guidelines regarding its use,” read the blog.

But client deployments are already underway. Telstra is using Cognizant’s Neuro agents to prototype service workflows. A US-based healthcare payer is using AI agents to streamline contract negotiations, thereby reducing the turnaround time on medical appeals. Aker Solutions has signed a multi-year deal to modernise its IT systems using the same framework.

Accenture, Infosys, and TCS are all investing in GenAI, but they haven’t open-sourced agent frameworks or committed to challenging targets, such as 50% machine-generated code. Cognizant’s decision to go public with its roadmap puts pressure on the rest of the industry to follow suit.

If vibe coding proves effective at this scale, it won’t just transform the way software is developed, but it will also shift the demographics of who creates it.

The post Cognizant’s Vibe Coding Lesson for Indian IT appeared first on Analytics India Magazine.

As legacy IT giants deepen their collaborations with global capability centres (GCCs), mid-tier IT firms are seizing a timely opportunity. Mid-market GCCs, often focused on niche domains and run by lean teams, are increasingly turning to these agile IT players for support in scaling operations.

A NASSCOM-Zinnov report noted that, although mid-tier GCCs accounted for nearly 35% of total GCCs, they faced significant challenges. These pertained to attracting early-career talent, the lack of standardised operating procedures, their struggle to establish innovation partnerships, and their minimal brand presence in local ecosystems.

These factors make it clear that mid-tier GCCs require a different kind of support model than what traditional IT giants typically provide.

Where Large IT Falls Short, Mid-IT Steps In

Mid-IT is not just an alternative to legacy IT but the need of the hour. Legacy IT is usually caught in multi-year contracts with big-ticket clients for constant revenue streams. Smaller GCCs, due to their size, might receive less attention and dedicated resources.

“Large IT companies often have extensive internal procedures that can create friction when dealing with these nimbler entities,” said Praveen RP, chief operating officer of the GBS Business Unit at Happiest Minds Technologies. “Large IT services companies, with their inherent multi-layered structures, can struggle to match this pace, leading to slower response times and potentially hindering the goals of smaller GCCs.”

Cost Arbitration is No Longer the Moat 

Enterprises are moving beyond cost savings to seek deeper value from their GCCs through greater ownership and integration.

“The optimal model for GCCs—one that delivers the greatest value to enterprises beyond just cost arbitrage—is where applications and processes are fully owned within the GCC,” said Rohit Jayachandran, head of banking & financial services at Mphasis. “Few organisations have reached this level of maturity; most are still in the early stages of this often costly journey.”

For smaller or newer GCCs still building this maturity, shared services can offer a practical path forward. “Shared services for support functions like HR, payroll, talent acquisition, compliance, and legal can be leveraged instead of investing in CapEx, helping optimise OpEx,” Praveen noted. These services are especially useful for firms that lack the internal capacity to fully staff such functions. 

Sustainable Growth Requires Flexibility 

Much like startups, GCCs rely on the ability to pivot and adapt quickly. Flexibility has become a key driver of sustainable growth, and mid-sized IT firms are well-positioned to deliver on this need.

“Flexibility is perhaps the biggest differentiator,” noted Srinivas Chamarthy, SVP, engineering, and country head, Diligent India. “Mid-sized firms can tailor delivery models, team structures, and even technology stacks to align with a GCC’s specific goals. They’re not constrained by legacy contracts or rigid SLAs, which makes them more adaptive.”

Mid-sized IT firms are increasingly offering ‘GCC as a service’, giving companies the flexibility to choose the service model that best fits their needs. “The biggest benefit of this model is that it reduces setup time and effort, allowing GCCs to start operations and realise value faster,” said Vybhava Srinivasan, managing director at Availity India.

Employment Generation 

As delivery models evolve, mid-sized IT firms are expected to play a key role in job creation within the GCC ecosystem. Srinivasan believes that shorter delivery cycles will, in the near term, boost employment and offer better compensation for skilled talent. However, he pointed out that the long-term impact will depend on how well these delivery models create lasting value for GCC headquarters.

Sustained value, he noted, must go beyond cost arbitrage. “More value creation beyond the expected cost arbitrage will eventually create a virtuous cycle of growth of existing GCCs and more new GCCs flowing, resulting in increased employment.” At the same time, he warned that “if the delivery is suboptimal and there is no value creation, this could lead to reduced employment.”

Cultural Alignment 

Small and Micro GCCs setting up in India for the first time are looking for trusted partners and prioritise business continuity, cultural alignment and operational resilience.

“Mid-size IT firms or GCC ecosystem partners are not just vendors to these GCCs, but they become strategic partners for their success and growth in India, especially now since the geopolitical uncertainties such as visa restrictions, trade tensions, and data localisation laws are at the forefront currently,” Neeti Sharma, CEO of Teamlease, stated.

Mid-sized IT firms are set to drive the next phase of GCC growth in India. By supporting faster scale, stronger integration, and greater agility, they have the potential to transform how global enterprises build and expand their India operations, creating lasting value beyond just cost savings.

The post Why Smaller GCCs Should Move Away From Bigger IT Firms appeared first on Analytics India Magazine.

ServiceNow has once again delivered on what Indian IT firms have been promising every time—turning generative AI into actual revenue. 

In its second-quarter earnings, the California-based enterprise software company posted $3.11 billion in AI subscription revenue, a 23% jump from last year. 

The company attributed its strong performance to the continued adoption of Now Assist, its flagship generative AI platform, through which it’s earning revenues. 

“Every business process in every industry is being refactored for agentic AI,” said ServiceNow chair and CEO Bill McDermott in a release.

ServiceNow’s CFO Gina Mastantuono said that bookings for Now Assist “surpassed expectations,” and it was driven by an increase in the deals.

“ServiceNow holds a distinct advantage, because we’re the only company that has AI plus data plus workflows on one platform, and in an agentic AI world, that’s a game changer and a huge differentiator,” she said in an interview with CRN.

Deal Volumes Grew 50% with AI in Them

According to Mastantuono, AI is now embedded across the platform—and the results show. 

In the second quarter, she said twenty-one deals involved five or more of their AI products. “Deal volume increased by 50% quarter-over-quarter, and they secured their largest Now Assist AI deal to date, valued at over $20 million,” Mastantuono said. 

The company is not just leading the AI race, but also running it themselves and that makes them stand out from most Indian IT firms.

While TCS is incorporating AI agents into 150+ client conversations and Infosys is running 300+ agentic AI projects, they are not reporting yet on how much money they’re making from it. 

Wipro, on the brighter side, had generative AI in most of its deals—but no breakdown on revenues despite doubling the total deals for the quarter. HCLTech was happily flaunting its OpenAI deal throughout the quarter despite a 10% decline in profit.

In contrast, ServiceNow had 528 customers with contracts worth over $5 million annually, up from 508 last quarter. 

Mastantuono was also quick to point out that while the US federal sector is facing headwinds—tightening budgets and evolving mission demands—ServiceNow still closed six new federal customers in Q2.

“We’re delivering exactly what federal agencies need most right now. It’s what the administration is driving: speed, efficiency, modernisation, and scale, especially for agentic AI,” she said in the interview.

This is a significant distinction. While Indian firms continue to pilot AI projects in silos, often unsure about whether to bet on GPT or Mistral or Claude, ServiceNow is undertaking enterprise-wide rollouts with measurable ROI. 

She also noted that the company’s Workflow Data Fabric, which enables customers to integrate real-time data from any source to power AI, was included in 17 of the top 20 deals. “RaptorDB, which is our next-gen database for AI, continues to gain traction,” Mastantuono added.

So Indian IT?

For Indian IT, which often points to its large client base and domain expertise, ServiceNow’s results are a wake-up call. The company is not only capitalising on the hype around AI but also building a repeatable, monetizable business model around it. 

Just last quarter, it said Now Assist is on track to hit $1 billion in ACV by 2026, up from $250 million now. That projection already looks conservative.

The company is also showing signs of international strength. “Every major region beat expectations,” Mastantuono said, underscoring how the AI strategy isn’t limited to North America.

In Q1, ServiceNow had declared that AI is not just a product enhancement—it’s a business. “We are leading the AI race because we ourselves are running it,” McDermott said back then. This quarter only reaffirmed that statement.

Meanwhile, Indian IT’s obsession with GenAI pilots and proof-of-concepts continues. There are a few signs of full-scale deployments, let alone disclosures of AI-driven revenue. 

Even Accenture is openly attributing $1.5 billion in generative AI bookings for Q3FY25, and Indian IT should be paying very close attention.

The big question now is whether Indian IT can ever catch up to ServiceNow or Accenture’s AI before it’s too late.

The post ServiceNow’s 18 AI Deals, 23% Revenue is Yet Another Wakeup Call for Indian IT appeared first on Analytics India Magazine.