At 3M, AI Agents are Making Data Pipelines ‘Self-Healing’

A robust system prompt ensures consistent behaviour across pipeline executions and helps reduce hallucinations.
Data engineering is shifting from reactive maintenance to intelligent automation. As enterprises grapple with constant schema changes, growing data volumes and evolving source systems, there is a growing push to make pipelines more adaptive and resilient. At the heart of this shift is the use of AI agents, not as replacements for engineers, but as tools that reduce manual intervention and bring consistency to everyday operations. While speaking at AIM’s event DES 2025, Manjunatha G, engineering and site leader at the 3M Global Technology Centre, laid out a practical path to integrate AI agents into data engineering workflows. “Transformation in data is going to be an easy change if we embrace the technology,” he said. However, the change he referred to isn’t flashy. It’s in
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Siddharth Jindal
Siddharth is a media graduate who loves to explore tech through journalism and putting forward ideas worth pondering about in the era of artificial intelligence.
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