Agentic AI Governance: 3 Controls to Manage them in Production

Published November 25, 2025

Agentic AI is already moving from experimentation into production. In PwC’s May 2025 AI Agent Survey of 300 senior executives, 79% report AI agents are already being adopted in their companies, and 66% of adopters report measurable productivity gains. Agents introduce a different risk profile than copilots: they plan tasks, call tools/APIs, and can execute end-to-end actions in live systems shifting the risk from “bad output” to “bad action.”

Key takeaways

• Classify agents by decision authority and impact. Document where agents are used, which systems they can touch, and what happens if they’re wrong.

• Define explicit decision limits. Write down what decisions the agent can make autonomously, with clear thresholds (dollars, customer impact) and when human approval is required.

• Instrument for observability and control before go-live. Log plans, tool calls, referenced data, and final actions; implement anomaly monitoring and a clearly owned kill switch.

Watch the video: https://youtu.be/bJi0Y4SzKPk