Identity and ownership
Associate connected agents with an identity and a responsible owner. Make operational accountability explicit.
Platform / Agent control
Give agents a job. And clear boundaries.
Control the tools, permissions and actions behind autonomous workflows. Keep a human decision point where the consequences matter.
The challenge
An agent’s access is a business decision.
Once AI can call tools, modify records or trigger workflows, a good answer is no longer the only concern. You need to know who owns the agent, what it can do and how to stop an action that crosses a boundary.
Discuss your environmentYour controls
From policy to everyday practice.
Scoped permissions
Define which tools and actions an agent may use. Apply checks at integrated action boundaries.
Human approval
Require review for selected consequential actions before execution. Keep routine activity moving within agreed limits.
Action history
Preserve a record of requests and policy decisions for debugging, security review and oversight.
An example in practice
An agent tries to change a customer record.
Illustrative workflow. Controls depend on your configuration.
- 01
Request
An automation prepares a change that falls outside its approved permissions.
- 02
Policy check
The action is checked against the agent’s scope before the connected tool executes it.
- 03
Outcome
The action is denied or routed for approval according to the configured policy.
Deployment
Start with a defined scope.
Identify agents, owners and the tools they can call.
Set permission scopes and approval requirements at action boundaries.
Test allowed and denied actions before expanding autonomy.
Action controls require integration at the relevant tool or execution boundary. Model instructions alone do not enforce permissions.
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