Is Your Interview Feedback Ready to Be Checked by AI?

These days, most interviews are recorded and transcribed.
Candidates can upload their transcripts and their feedback into an AI tool.
AI then checks whether your comments truly reflect what was discussed.

But what happens when the AI comes back with something like:

“The feedback doesn't fully align with the interview transcript. The rejection seems based more on interpretation than on actual evidence.”

That’s when candidates lose trust, not because they were rejected, but because the reasoning feels unfair.

𝗧𝗼 𝗮𝘃𝗼𝗶𝗱 𝘁𝗵𝗶𝘀, 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 𝗻𝗲𝗲𝗱 𝘁𝗼 𝗯𝗲 𝗱𝗲𝘀𝗶𝗴𝗻𝗲𝗱 𝘀𝗸𝗶𝗹𝗹𝗳𝘂𝗹𝗹𝘆 𝘄𝗶𝘁𝗵 𝗶𝗻𝘁𝗲𝗻𝘁𝗶𝗼𝗻:
  • Define clear objectives. What exactly are you assessing?
  • Design questions that reflect those objectives. Make sure they map to the skills you’re testing.
  • Use measurable criteria. Base decisions on observable evidence, not vague impressions.

When your process is structured and thoughtful, your feedback stays solid, even when AI checks it.

Of course, intuition still matters, but we also need to respect candidates and provide transparent feedback they can appreciate, rather than feedback that ends up undermining the employer.