A senior recruiter at a global tech firm noticed that her best interviewers were not the most experienced ones. They were the ones who got feedback on their interviews. The most experienced interviewers had been doing it the same way for a decade and were getting predictably mediocre signal.
Interviewer training is the most neglected discipline in hiring. Companies train their salespeople, their managers, their engineers, even their support reps. They hand interviewers a 30 minute LMS module and call it done.
The reason is that interviewer training has no obvious feedback signal. You only find out the interviewer made a bad call when the hire fails six months later. Or when a candidate complains. Both signals are delayed and rare.
AI compresses the loop. Within minutes of an interview ending, the system can tell the interviewer where they spent their time, which rubric items they covered, where their questioning was open versus leading, and how their scoring distribution compares to their peers. None of this requires waiting for the hire to succeed or fail.
The interventions are small. A senior engineer learns he asked the same warmup question for 12 minutes across his last five interviews. He compresses it to four. He gets back 40 minutes of usable evaluation time per loop.
A platform like Mazle treats every interview as a teaching moment for the interviewer, not just an assessment of the candidate. The interviewer development curve goes from years to weeks.
The companies winning the talent war in 2026 are not the ones with the best ATS. They are the ones whose interviewers get better every quarter.
