AI is everywhere in hiring, but it’s not fixing broken processes — it’s accelerating them. In this episode, we break down how AI actually shows up in the hiring process, what it amplifies on both the candidate and company side, and why blaming the tool misses the real issue. You’ll learn where candidates unintentionally hurt themselves using AI, where companies break trust with automation, and how to use AI in ways that improve hiring without sacrificing judgment, fairness, or candidate experience. Key takeaways - AI is not good or bad; it amplifies the quality of your existing hiring process - Strong interview structure and trained interviewers make AI more effective - Candidates should use AI, but unedited, copy-paste outputs are easy to spot - If AI rewrites your experience so well you can’t explain it, you’re setting yourself up to fail - Using live AI during interviews can lead to poor hiring matches and distrust - Generic, AI-written job descriptions weaken employer brand and clarity - Automated rejections without human review damage trust and miss great talent - AI-generated interview questions often produce canned, low-signal answers - The safest, highest-value AI uses are scheduling and interview note-taking - Interview training and process design matter more than adding new tools Timestamps 00:48 — Why AI isn’t fixing hiring 01:26 — AI reveals strong vs broken processes 01:43 — Candidate AI panic and misconceptions 02:16 — Common mistakes candidates make with AI 04:03 — When resumes don’t match real experience 05:00 — Live AI use during interviews and risks 07:08 — How companies break trust with AI 08:59 — Automated rejections and candidate impact 13:16 — Why AI interview questions fail 18:54 — Where AI actually helps hiring teams Keywords AI in hiring interview process hiring automation AI interviews recruiting technology candidate experience interviewer training hiring bias AI recruiting tools structured interviews
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