Practical risk review
AI Agent Risk Assessment
An AI agent risk assessment starts with simple questions: what can this agent read, what can it change, and who can stop it? Roxea gives teams a consistent way to answer them.
What is an AI agent risk assessment?
It is a structured review of an agent, the tools it uses, the permissions it holds and the safeguards around its actions. The goal is not to judge the model in isolation. The goal is to understand what can happen in the real workflow.
A support assistant that drafts a reply carries a different risk from one that can read the full inbox and issue refunds. The model may be similar. The access and autonomy are not.
Why AI agent risk is different from classic software risk
Agents can interpret instructions, choose a sequence of actions and operate across several tools. Their behaviour depends on prompts, context, connected data and the limits configured around them.
A classic access review may show that a service account can update a CRM. An agent review must also ask when it decides to make that update, whether a person approves it and whether the action is logged.
What Roxea helps you review
Roxea keeps the assessment grounded in facts your team can verify. Each finding points back to declared access or a missing safeguard.
- The agent owner, department and business purpose.
- Tools the agent can access and whether access is read or write.
- Sensitive actions such as sending messages, editing code or issuing refunds.
- Human approval, activity logs and emergency stop controls.
- The action needed, its priority, owner and due date where available.
Common AI agent risks
Most issues are ordinary control gaps rather than unusual model failures. An agent has more access than its task requires. A high-impact action has no approval step. Nobody owns the workflow after the person who built it leaves.
- Reading customer emails or HR documents without a clear scope.
- Updating CRM, finance or production data without validation.
- Accessing source code or secrets from an automation runtime.
- Triggering payments, refunds or outbound messages without approval.
- Operating without useful logs or a tested way to stop it.
AI agent risk assessment checklist
Start with one business workflow. Record the agent, its owner and every connected tool. For each tool, review what the agent can read, write, send or trigger. Then document approval, logging and stop controls.
Prioritise changes by impact and exposure. Removing an unused write permission is usually more useful than writing a broad policy nobody can apply.
- Confirm a named business owner.
- List every tool and permission.
- Identify sensitive data and high-impact actions.
- Check human approval at the point of action.
- Verify logs and a practical kill switch.
- Assign fixes and set a review date.
FAQ
Questions people ask before a review
Continue the review
Related guides and product details
Review one agent from access to action plan.
Create an inventory, record its permissions and see which control gaps deserve attention first.