Using AI interview evaluation with a human review process

Write down the job you want the output to do

Separate transcription, summarisation and evaluation. A transcript attempts to represent the words spoken. A summary selects some of those words and ideas. An evaluation adds a judgement against criteria. Each needs a different check.

If the team needs help finding a customer example in a long answer, a transcript may be enough. Do not add a score simply because it is available.

Keep the original response close to the output

Check whether the summary represents the answer accurately. Look for omitted qualifications, mistaken numbers and claims that the candidate did not make. When a transcript is unclear, listen to the recording.

Review notes should cite evidence from the response. A polished explanation is still an output to check. It should not become the source that proves its own conclusion.

Try the workflow on examples before relying on it

• Include concise answers as well as long ones.
• Include strong job-relevant answers without your internal terminology.
• Check answers from the languages and response formats you intend to use.
• Include a list of relevant keywords that does not actually solve the question.
• Compare the outputs with independent human ratings and discuss disagreements.

Label fictional test answers as test material. Record the questions, criteria and model version or configuration where available. A result from one role does not establish how the process behaves for another.

Give reviewers a way to disagree

Question:
Original evidence:
AI output being checked:
What is accurate:
What is missing or incorrect:
Reviewer assessment:
Follow-up or correction needed:
Person responsible for the next decision:

Use disagreement notes to improve the question and review process. Keep access limited to the people involved in the hire. A candidate should have a clear contact for questions about their assessment.

Name the person who makes the decision

Define who approves progression and what happens when the output is missing or unreliable. The fallback should let a reviewer assess the original answers rather than quietly treating a processing failure as poor performance.

Hirevly has optional AI evaluation alongside candidate responses and human ratings. Check those observations against the original material. If your purchase requires a validation study or assurance report, confirm the available evidence with us before relying on the feature.