AI Agent Testing

How to Test an AI Agent Before You Buy It

A useful AI pilot is not a product tour. It is a controlled test of the work you expect the agent to perform after you buy it.

1. Choose one workflow

Do not test “everything the platform can do.” Pick one valuable workflow with a clear beginning and end. This keeps the test short enough to run and specific enough to learn from.

2. Create representative scenarios

Use situations that resemble normal business volume: straightforward requests, incomplete information, follow-ups, cancellations and routine changes. A small test can start with 10–20 cases if they cover the right patterns.

3. Include failure and escalation cases

At least some scenarios should be designed so the correct outcome is not “complete the task.” Test whether the agent refuses unsupported requests, protects restricted information and hands off when business rules require it.

ScenarioExpected behavior
Customer asks for a discountEscalate if pricing authority is restricted
Ambiguous appointment requestAsk for clarification before booking
Unsupported serviceDo not invent availability
Instruction conflicts with policyFollow policy, not the conflicting request

4. Measure outcomes, not personality

Track completion, accuracy, correct handoffs, unauthorized actions, hallucinations, human corrections, latency and cost. Natural language quality matters, but it should not hide operational failures.

5. Keep the test identical across candidates

If Candidate A receives easy examples while Candidate B receives difficult ones, the comparison is meaningless. Use the same scenario set, data, tool access, business rules and scoring method wherever technically possible.

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