An AI recruiting pilot checklist for a small hiring team

Choose one task for an AI recruiting pilot. A small team can learn more from testing resume summaries for a defined vacancy than from switching on every available feature and trying to judge the overall impression.

Write down what the pilot may influence and which decisions remain outside its scope.

Agree on the task and owner

Name the person responsible for the pilot, the reviewer who understands the role, and the contact for operational failures. Define whether the output will be used only in a test environment or alongside live work under an approved process.

Describe the intended benefit in observable terms. "Reviewers can locate evidence for the agreed requirements" can be tested. A general promise to improve quality of hire cannot be established by a short software trial.

Prepare approved inputs

Use synthetic documents or data whose use has been properly authorized. Record the document types, languages, and job criteria the pilot covers.

Ask the provider how information is processed and retained, and which controls are available. Resolve access and data-handling questions before uploading real resumes.

Include difficult examples deliberately. A pilot that excludes unreadable documents, career changes, or missing information will tell you little about handling those cases later.

Set a review procedure

Have qualified people assess the same examples using a defined rubric. Compare extraction, summaries, and recommendations separately. Keep disagreements and unknowns visible.

Your pilot log can include the application reference, expected task, observed output, reviewer concern, and action taken. Avoid placing raw personal information into a broadly shared evaluation document.

Test what happens when processing fails, an analysis is rerun, or the tool reports an unsupported conclusion. Assign a manual path so work can continue.

Decide when to pause

Agree in advance which findings require investigation before wider use. Examples might include invented qualifications, hidden processing failures, or repeated inability to read an expected document type. The exact conditions should reflect your use and the consequences of error.

Keep a record of product or model changes during the pilot. If the underlying behavior changes, decide which tests need repeating.

Review the evidence before expanding

Discuss whether the task became easier, where reviewers still needed to intervene, and what additional operating work the tool created. Include usage costs and support time.

Approve expansion only for the uses your evidence supports. Keep an owner for later monitoring and communicate limitations to the people who will rely on the output. A pilot is useful when it produces a clear operating decision, including a decision to keep the task manual.

Further reading

• Artificial Intelligence and the ADA | U.S. Equal Employment Opportunity Commission
• TIPS FOR WORKERS:

Related guides

• Evaluate screening with controlled examples
• Prepare a failure-handling procedure
• AI resume screening: how it works and where it can go wrong