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AnalysisGovernance, catalog & semantic layer
DataRobot Blog · Read source ↗

The article discusses the importance of governance in deploying agentic AI systems. It highlights the unique risks posed by agents, which can not only produce incorrect predictions but also act on them, potentially accessing sensitive data or triggering unintended workflows.

MyDataWork POV — Agentic AI governance is essential, not merely a checklist item. Each agent you deploy carries the potential to act autonomously, and that means the stakes are higher than ever. The ability to retrieve sensitive data or alter systems of record shifts the conversation from model accuracy to authority management. Not every organization is ready for this level of responsibility. If your data governance is already stretched thin, adding agents might be a leap too far. Prioritize readiness over ambition.
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Agent Studio offers a structured way to assess whether an agentic use case is appropriate for your organization. By scoping out potential risks and governance needs before deployment, MyDataWork users can better manage the authority and impact of their agents. Explore MyDataWork ↗
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