Evaluate an AI interviewer by the evidence it produces, not the demo it gives. Check whether its questions are structured and job-related, whether every score traces back to something the candidate actually said, and whether a person can review and override the result. A confident summary is easy to fake; an auditable trail is not. That is the same bar AI interview software should clear before it screens a single applicant.
AI interviewer evaluation criteria
- Structured, job-related questions. Items should map to competencies the role needs, and comparable candidates should get the same core questions.
- Scoring transparency. Every rating should point to the transcript evidence and the rubric anchor behind it, not just a number.
- Bias testing and adverse-impact monitoring. Ask for testing across accents, disabilities and languages, plus ongoing selection-rate checks — not a one-off claim.
- Candidate experience and accessibility. Clear notice that AI is used, a working accommodation path, and an option for a human interview without penalty.
- Human review and override. Reviewers need the raw evidence, the time, and the authority to disagree with the score.
- Integrations and data handling. Confirm where recordings and transcripts live, how long they are kept, and what flows back to your ATS.
- Version control. You should know which model, prompt and rubric produced a rating, and be told before any of them change.
Judging a tool on these points is automated interview scoring turned on the vendor itself. If nobody can explain a score, start by defining the anchors yourself — a plain interview evaluation form template quickly exposes where the tool is guessing.
How to test before you buy
Pilot on one real role, not a scripted demo, and keep the AI in shadow mode: it scores but does not decide. Compare its rankings against a human panel that assessed the same interviews blind, and study the disagreements — those cases reveal what the model actually weighs. Read the candidate feedback on clarity and accessibility, and flag any score you cannot rebuild from the transcript. Then ask whether your reviewers would truly overrule a wrong result, because oversight that never overrides is just a rubber stamp. One more check: whether the tool can flag AI-assisted answers, since interview integrity is now part of the evaluation.
Bottom line
Judge an AI interviewer the way you would judge a human one: job-related questions, evidence you can inspect, and a person able to overrule the result. If that trail exists, the tool is worth piloting. If it does not, speed is the only thing you are buying.