AI agent monitoring: what to watch once your agents are running
AI agent monitoring is keeping an eye on what your agents actually do once they are in use: who uses them, which systems they reach, what they change, and what your rules stop.
Developers monitor agents for errors and speed. For the business, the questions are different: is the agent doing the right things, for the right people, within the rules?
Five signals worth following
Two sides of the same log
How Deployed OS handles it
Deployed OS logs every call with the person, the system and what was read or changed, in every AI tool your people use, and shows who uses what. The log can be exported, for example to the tools your IT team already uses.
This is one of five controls every company needs for its agents. See all five in our guide to AI agent governance.
Questions about AI agent monitoring
Following what AI agents do once they run: who uses them, which systems they reach, what they change, what rules block, and whether anything looks unusual.
Observability is mostly a developer term for tracing how an agent works inside: steps, errors and speed. Monitoring for the business is about what agents do in your systems and for whom.
Start with what agents change, not what they read, and with what your rules block. Those two show the real risk and the real needs fastest.
Not if every agent reaches your systems through one connection layer that logs each call. Then that log is the source, and it can be sent on to the tools IT already uses.