What influences the result?
Ask which candidate, role, recruiter, or historical data fields influence scores, matches, rankings, summaries, or recommendations.
ATS evidence
If an ATS ranks candidates, ask for evidence before rollout.
Applicant tracking systems increasingly include AI-assisted screening, ranking, matching, and summarization. A short evidence request can turn a vague feature description into an operating record.
Five questions
Start with the facts a buyer can verify.
What action can the output trigger?
Document whether the output advances, rejects, prioritizes, queues, flags, or merely organizes candidates for review.
Where does human review happen?
Capture the reviewer role, what the reviewer sees, whether the AI output can be overridden, and how overrides are logged.
What testing or audit exists?
Request audit summaries, validation notes, limitation statements, subgroup-performance notes, or other current evidence the vendor can share.
What changed since renewal?
Ask whether AI features, model providers, ranking logic, data sources, or default settings changed since the last contract review.
What candidate-facing support exists?
Collect notice language, public documentation links, accommodation paths, and contact-routing guidance before launch.
Buyer workflow