Agentic systems should be reviewed by their operational autonomy, tool access, workflow impact, human control points and evidence trail. The more an AI system can act, route or trigger actions, the more important diagnostic triage becomes.
Operational information, not legal advice.
Autonomy control model
Autonomy scope
Clarify whether the system only assists or can plan, call tools, act, adapt or escalate.
Tool access
Map which APIs, data sources, workflows and external actions the system can reach.
Human control
Define where review, approval, override and shutdown must remain possible.
Traceability
Keep prompts, actions, outputs and proof signals reviewable after execution.
Autonomy control
Autonomy scope, tool access, human control and traceability define whether agentic AI remains governable.
Strategic answer
Agentic AI systems create readiness questions when they can plan, call tools, trigger actions or route workflows. The practical issue is not the term agent. It is what the system can do, who controls it, what evidence exists and who is affected.
Start with the EU AI Act Diagnostic, turn findings into an implementation plan, and see how the diagnostic works as a reference app on M13.
Exposure focus
First action
This page provides operational information for AI governance readiness. It is not legal advice.
Related guides
Run a diagnostic-first EU AI Act assessment for role, risk, documentation and implementation exposure.
Understand high-risk AI system triage and why early classification matters before implementation.
A practical guide to assessing EU AI Act risk before committing budget to implementation.
Build a practical implementation path after scope, role and risk have been diagnosed.
Official sources
External references are included for source orientation. This page remains operational information and is not legal advice.
