AI agents should be assessed by what they can do in an operational workflow: whether they only assist, whether they trigger actions, whether they use tools, and how humans control or review their outputs.
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.
Direct answer
AI agents can create EU AI Act readiness questions when they plan steps, call tools, trigger workflows or influence decisions. The key issue is not the label agent. It is the degree of autonomy, the workflow context, the human control model and the impact of outputs.
For the next layer, compare provider vs deployer roles, review high-risk AI system signals, or start with an EU AI Act risk assessment.
Decision criteria
First inspection
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.
A direct answer page for US companies that need to understand possible EU AI Act exposure.
Clarify the difference between provider and deployer roles under EU AI Act readiness work.
A practical guide to assessing EU AI Act risk before committing budget to implementation.
Official sources
External references are included for source orientation. This page remains operational information and is not legal advice.
