Assess an AI agent in the specific workflow it will perform—not by its model label or a convincing demo. Before allowing it to use business systems, map its data and permissions, test normal and hostile cases, put independent approval controls around consequential actions, and define how you will detect problems and suspend use.
1. Define the workflow, stakes, and boundaries
Start with a written description of one proposed use, not a broad claim such as “help with operations.” Specify what the agent is meant to accomplish, who will use it, who may be affected, and what a correct result looks like. Record the data it will handle, the systems it may touch, and the likely consequences of a mistaken or unauthorized action.
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Draw a clear line between permitted and prohibited work. For example, an agent might be allowed to draft a customer reply but not send it, or to prepare a payment request but not approve or submit it. Set the organization’s risk tolerance and name the business owner accountable for the workflow.
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2. Map the whole system, including its tools and data
An agent’s behavior depends on more than the underlying model. Document the deployed model and version, prompts and configuration, retrieval sources, memory, connected tools, identities and credentials, human handoffs, vendors, and monitoring. For each connection, trace what data goes in, what comes back, and what the agent can do with the result.
Include the execution environment: the system that grants access, checks permissions, carries out tool calls, and records activity. NIST’s Govern and Map functions and OWASP’s agent-security guidance support looking at the complete system rather than assessing model answers in isolation.
Make an action inventory
For every tool, write down whether the agent can read, create, modify, delete, send, approve, or trigger a transaction. Separate these capabilities where possible. “Can access the mailbox,” for example, is too vague if the agent can both search messages and forward them externally.
- List the business data and systems in scope, including retrieved documents and email.
- Identify the account or service identity used for each tool and who controls its credentials.
- Record whether actions are reversible, externally visible, or likely to affect a person.
- Note where a human takes over and what information that person sees before deciding.
3. Reduce authority and enforce approvals outside the model
Grant each tool only the permissions needed for the defined task. If the workflow needs read access, do not grant write access; if it needs to create a draft, do not also grant send or delete permissions without a separate justification. OWASP’s Excessive Agency guidance identifies unnecessary downstream permissions as a risk, while its agent-security guidance recommends least privilege and independent authorization checks.
Do not treat a prompt such as “never send confidential information” as an access-control mechanism. Enforce authorization in the system that executes the action, so a natural-language instruction cannot grant or substitute for permission. Check approvals at execution time, against the actual user, action, target, and relevant policy.
Put a human gate on material actions
Set human review before actions with significant impact, such as external communications, payments, deletion, access changes, or decisions affecting people. The reviewer should see the specific proposed action, its destination or target, and the data it will use—not merely a summary saying the agent is ready. Record who approved or rejected it and when. OWASP recommends human-in-the-loop approval for high-impact actions.
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4. Test routine work and adversarial inputs
Build a test set from representative tasks and plausible edge cases. Include ambiguous requests, malformed or incomplete outputs, unauthorized requests, and untrusted content in documents or email. Test the connected workflow, including the permissions and execution checks, rather than scoring only the model’s text response.
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In particular, check whether content the agent reads can redirect its goal, induce disclosure, or cause an unauthorized tool call. OWASP describes indirect prompt injection in which a malicious incoming email tries to make an agent search a mailbox and forward sensitive information. Use safe test accounts and data, and verify both what the agent says and what connected systems actually do.
Record evidence for each test
- What task and input were used, including any untrusted content.
- What action the agent proposed and what tool call it attempted.
- Whether the authorization layer allowed or blocked the call.
- Whether a human review was required and what the reviewer could see.
- Whether data was exposed, changed, sent, or deleted, and whether the result was logged.
Compare candidate agents or designs using the same workflow, test set, and acceptance criteria. A clean demonstration on benign inputs does not establish that the agent is safe against hostile content or excess permissions.
5. Verify what happens when something fails
Test failure paths deliberately. Simulate unavailable tools, expired credentials, invalid or incomplete outputs, policy-lookup failure, rejected approval, and audit-log failure. The system should stop or safely escalate rather than carry on with an unchecked action.
OWASP’s Agent Security Cheat Sheet recommends fail-closed behavior when risk classification, approval validation, policy lookup, or audit logging fails. Confirm that behavior in the deployed setup: a documented rule is not evidence that the execution path actually enforces it.
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Set measures that reflect the workflow’s risks, such as task success and error rates, unauthorized or blocked tool calls, human overrides, sensitive-data exposure, incidents, and latency or cost limits. These are practical implementation examples aligned with NIST’s Measure and Manage functions, not metrics NIST requires universally.
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Assign an owner to review results and incidents, and specify thresholds or events that trigger investigation, suspension, or reassessment. Re-test after changes to the model, prompts, tools, permissions, data sources, or workflow. A changed connector or access scope can alter risk even if the visible task description stays the same.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.7. Approve a bounded configuration, not an agent in general
Make a decision for the exact workflow configuration you assessed: its model and version, tools, permissions, data sources, approval gates, and operating conditions. Record the residual risks, rationale, accountable owners, monitoring plan, and the changes or incidents that require suspension or reassessment.
For a comparison, use the same questions for each design:
| Assessment area | Evidence to examine | Warning sign |
|---|---|---|
| Permission scope | Separate read, write, send, delete, approval, and transaction rights for each tool. | Broad credentials grant capabilities beyond the workflow’s needs. |
| Authorization and approvals | Execution-time checks and an approval record tied to the actual action. | Access depends only on instructions in the prompt or an informal review. |
| Prompt-injection resistance | Results from tests using untrusted documents, messages, and retrieved content. | Untrusted content can redirect work, expose data, or trigger unauthorized calls. |
| Reliability and failure handling | Normal-case and failure-case results, including safe stops and escalation. | Missing tools, policy checks, or approvals lead to unchecked continuation. |
| Privacy and vendor handling | Data flows, retention, and vendor handling relevant to the organization’s requirements. | Data movement or handling is not understood well enough to assess. |
| Auditability and override | Records of actions, decisions, approvals, and human intervention. | Operators cannot establish what the agent did or interrupt it effectively. |
| Fit and residual risk | Remaining risk, implementation burden, and fit to workflow requirements. | A general safety claim substitutes for a workflow-specific decision. |
Trustworthiness includes reliability, safety, security, transparency, privacy, and fairness considerations; their relative importance depends on the use context. NIST’s AI RMF FAQ cautions that addressing trustworthiness characteristics one by one does not ensure trustworthiness, because tradeoffs are involved and not every characteristic applies equally in every setting.
This general assessment cannot determine legal compliance or acceptable residual risk for an unspecified jurisdiction, sector, or deployment. For high-impact workflows, involve the organization’s relevant security, privacy, legal, compliance, and business owners.
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