The AI recruitment ouroboros

Photo by Aleksandr Popov

A job interview used to be a conversation between people.

The purpose was simple: candidates tried to show who they were and what they could do, and employers tried to judge whether they were a good fit for the role, the team, and the work. It was a human exchange, shaped by instinct, ambiguity, and judgement.

Today, that’s no longer the case.

The recruitment process has turned in on itself. Every stage is influenced by AI. Job descriptions, CVs, interview questions, answers, feedback, and final decisions can all be generated, filtered, and processed by machines.

Hiring has become an automated loop where machines speak to other machines through people. Candidates use AI to shape their performance, and employers uses AI to define and evaluate that performance.

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It begins with the job advert.

The hiring manager enters a few bullet points into the recruitment platform. An AI writing tool expands these into a complete job description, adjusting tone to match brand guidelines and optimising for search engines.

The language includes precise, inclusive, and generic terms: 'collaborative environment', 'data-driven decision making', 'growth mindset'. The job post is automatically distributed across job boards and hiring platforms.

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Candidates respond with AI-adjusted CVs and cover letters, tuned to match the posting. Each applicant instructs their AI to 'optimise for keywords' and 'mirror the tone'. AI identifies the phrasing patterns most likely to pass automated filters and adjusts accordingly.

The company receives a batch of polished applications, structured to pass the AI-powered screening tool. This system parses each document, extracts key data points, and scores candidates based on how closely they match the job description.

Hiring managers are sent a ranked shortlist automatically.

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Candidates use AI to generate likely interview questions based on the role, industry, and seniority level. Suggested answers are also provided, tailored to the job description.

Hiring teams prepare using the same AI tools. Both sides relying on near-identical prompts and models.

Candidates rehearse with AI-powered coaching software which tracks filler words, tone, pace, and confidence, and gives feedback for improvement.

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During the video interview, a virtual assistant joins the call. It records, transcribes, and processes the conversation in real time, analysing sentiment and topic coverage.

Afterwards, interviewers use AI to clean up their notes and structure their feedback. The recruitment platform merges all inputs into a single report. It summarises impressions, identifies patterns, flags concerns, and suggests next steps.

The platform compares candidates based on interview scores, screening data, and profile matches. Hiring managers review the recommendations and confirm the decision.

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Finally a concise, legally-compliant, and empathetic rejection letter is drafted, referencing 'appreciate you taking the time', 'a strong field of applicants' and 'alignment with current business priorities'.

Emails are sent in bulk through the platform. No manual edits or reviews are made before dispatch.

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The whole point of a job interview is to find out who someone is, how they think, and whether they could work well with others. It's a moment of messy, subjective, and essential human judgement.

Now, it seems AI writes the roles, screens the people, and scores the conversations. Candidates perform for systems designed to read patterns, not people. Employers review summaries that reduce personalities to matches, metrics and tone scores.

When every step becomes automated, workers stop being seen. The ones who can’t or won’t tailor themselves to the system are filtered out before a person ever reads their name. Skill gives way to prompt literacy. Personality becomes noise.

For companies, the result is no better. They hire mirrors — candidates optimised to reflect their own data back at them. Teams become narrower, less adaptive, less human. Decisions feel efficient but produce sameness, fragility, and mediocrity.

When no one is really choosing, no one is really responsible.

A process still runs, but the purpose has collapsed in on itself.