Evaluation · 9 min read
AI Agent Evaluation Checklist
How to evaluate whether an AI agent is safe, useful, reliable, and production-ready.
Short answer
An AI agent should be evaluated on groundedness, tool-use accuracy, escalation behavior, security, privacy, reliability, and business impact. If a team cannot show how the agent is tested, the system is not production-ready.
Core checks
- Does the agent answer from the right source?
- Does it cite or expose supporting context where needed?
- Does it know when not to answer?
- Does it call the correct tool with the correct parameters?
- Does it recover from failed API calls?
- Does it protect private or permissioned data?
- Does it escalate risky actions to a human?
- Does it log decisions and outcomes for review?
Business metrics
Evaluation should include business metrics, not only technical tests. For a support agent, measure ticket deflection, escalation accuracy, grounded answer rate, and CSAT. For a sales agent, measure research accuracy, CRM cleanliness, meeting conversion, and time saved per account.
Need to plan an AI agent project?
Start with the hiring guide, cost guide, and evaluation checklist before choosing a developer or vendor.