Governance that finally does something
Data governance has always been built on human judgment, manual process, and controls that kick in after something has already gone wrong. Against tens of thousands of data assets, billions of daily events, and a regulatory load that keeps growing, that model is structurally overmatched. Agentic AI changes the equation. These are systems that can plan, reason across multiple steps, and act, so governance can finally fix problems instead of just reporting them.
In this point of view, Krishna Jyoti Das, Senior Architect, and Anish Bishen, VP and Head of Data – EMEA, make the case for governance where AI agents are active participants and humans keep the judgment and the accountability. The goal isn’t to take people out of the loop. It’s to give governance teams leverage over a data estate no human team could watch alone.
The piece covers the architecture of an agentic governance system, eleven high-impact use cases, a four-phase path from foundation to continuous improvement, and the guardrails and KPIs that keep it accountable.