AI in the Recruitment Industry: Both Sides Are Using It Now

The recruitment industry is experiencing something genuinely unprecedented. Both sides of the hiring process are now using AI, and the result is an arms race that's making the whole process more absurd while simultaneously threatening the business model of traditional recruitment agencies.

Employers use AI to screen CVs, rank candidates, conduct initial assessments, and schedule interviews. Candidates use AI to write CVs, craft cover letters, prepare for interviews, and mass-apply to hundreds of roles. The AI screening the application was designed to handle a human volume of applications. It's now handling an AI-amplified volume. And the recruitment agencies that used to sit in the middle of this, adding value through their networks and judgement, are watching their relevance erode from both directions.

i've been on both sides of this. I used AI tools when job hunting after redundancy, and i've seen how companies deploy AI screening from the employer side. The whole thing has become slightly farcical, and the people most affected are the recruitment professionals whose livelihoods depend on the process remaining human.

The employer side: AI screening at scale

Most large employers now use some form of AI in their hiring process. The specifics vary but the pattern is consistent:

CV screening. AI parses incoming CVs, extracts key information, and scores candidates against the role requirements. It looks for relevant experience, skills, qualifications, and keywords. It can process thousands of applications in minutes, reducing what used to take a recruitment team days to a few hours of reviewing the AI's shortlist.

Chatbot initial screening. Candidates interact with an AI chatbot that asks qualifying questions, assesses basic fit, and either progresses them to the next stage or rejects them. This replaces the initial phone screen that a recruiter used to conduct.

Video interview analysis. Some employers use AI to analyse recorded video interviews, assessing candidates on factors like communication skills, keyword usage, and even (controversially) body language and facial expressions. The candidates record their answers. The AI scores them. A human may only see the top-ranked candidates.

Predictive analytics. AI models predict which candidates are most likely to succeed in the role, accept an offer, and stay long-term. These models are trained on historical hiring data and employee performance data. Their accuracy is debatable but their adoption is widespread.

The result is a hiring process that's faster, cheaper per application, and (theoretically) more consistent than human screening. But it's also created problems. The AI optimises for pattern matching against existing successful employees, which can entrench biases. It rewards candidates who know how to game the system over candidates who might actually be better at the job. And it creates a black box where good candidates are rejected for reasons nobody can fully explain.

The candidate side: everyone's using AI now

Here's where it gets interesting. Candidates have figured out that AI is screening them, and they're responding with AI of their own.

AI-written CVs and cover letters. A significant majority of applications now include AI-generated or AI-enhanced content. Candidates use ChatGPT, Claude, or specialised CV tools to craft applications that are keyword-optimised, professionally written, and tailored to each specific job description. The bespoke cover letter that used to signal genuine interest? It takes 30 seconds to generate now.

Mass application tools. There are tools that will automatically apply to hundreds of jobs on your behalf, tailoring each application using AI. The result is that employers are receiving dramatically more applications per role. Some companies report application volumes increasing three to five times. Which means they need more AI screening. Which means candidates need better AI tools. And so the cycle continues.

Interview preparation. AI coaching tools that simulate interviews, provide real-time feedback, and help candidates prepare answers. Some candidates are even using AI earpieces during live interviews to get suggested answers in real time. The ethics are dubious but the technology works.

Assessment gaming. Online assessments and psychometric tests are being completed with AI assistance. Candidates use AI to answer situational judgement tests, personality assessments, and even coding challenges. The assessment companies are in a constant battle to make their tests AI-resistant, and they're losing.

The arms race nobody wins

So we've got AI screening applications written by AI, with candidates using AI to prepare for interviews assessed by AI. At some point you have to ask: what are we actually measuring here?

The honest answer is that we're increasingly measuring each side's ability to use AI effectively. Which might actually be a useful signal for some roles but is completely irrelevant for many others. The care worker, the plumber, the nurse — their ability to craft an AI-optimised CV has zero correlation with their ability to do the job.

The system is becoming less about finding the best candidate and more about navigating an increasingly complex technological process. And that's a problem for everyone.

What this means for recruitment agencies

Traditional recruitment agencies — the ones that earn fees by matching candidates to roles — are being squeezed from every direction.

The sourcing advantage is gone. Recruitment agencies used to add value by having access to candidates that employers couldn't find on their own. LinkedIn, job boards, and AI sourcing tools have made candidate identification trivially easy for employers. The agencies' databases are no longer a competitive advantage.

The screening advantage is going. The initial screening and shortlisting that agencies provided is now done by AI tools that employers can use directly. Why pay a 15-20% fee for a recruitment agency to screen candidates when an AI tool can do the initial screening for a fraction of the cost?

The application volume problem helps and hurts. On one hand, the explosion in application volumes means employers need help processing them. On the other hand, AI tools handle that processing better than human recruiters can.

The relationship still matters — sometimes. For senior roles, specialist positions, and confidential searches, the human relationship between recruiter, client, and candidate still has value. The recruiter who genuinely understands a niche market, has trusted relationships with passive candidates, and can assess cultural fit through personal interaction provides something AI can't replicate. But this is the premium end of the market. It's not where most agency revenue comes from.

The recruitment agencies that are surviving are doing one or more of the following:

Specialising deeply in niche markets where their expertise and relationships are genuinely irreplaceable. Moving up-market to executive search and senior appointments. Pivoting to recruitment process outsourcing (RPO) where they manage the entire hiring process, including the AI tools, on behalf of the employer. Or becoming technology companies themselves, building or licensing AI recruitment tools.

The generalist high-street recruitment agency that placed office temps and mid-level permanent staff? That model is dying. The economics don't work when AI can do most of what they offered.

In-house recruitment teams

Corporate in-house recruitment teams are also changing. The large teams that processed applications, conducted phone screens, and managed scheduling are shrinking. AI handles the processing and scheduling. Chatbots handle the initial screening.

What remains is more strategic: employer branding, candidate experience design, hiring manager coaching, diversity and inclusion strategy, and the high-touch elements of senior hiring. The recruiter becomes less of a processor and more of a consultant.

The tactical recruiter who spent their day reviewing CVs and conducting phone screens is being replaced. The strategic recruitment partner who advises hiring managers, improves processes, and manages complex stakeholder relationships is still needed. The ratio is shifting heavily towards the latter.

The bias and fairness problem

i have to mention this because it's significant. AI recruitment tools have repeatedly been shown to perpetuate and sometimes amplify existing biases. Amazon famously scrapped an AI recruitment tool that was biased against women. Other systems have been shown to discriminate based on age, ethnicity, and socioeconomic background.

The issue is fundamental: these systems learn from historical data, and historical hiring data reflects historical biases. Training an AI on "what successful hires looked like" when your historical hiring was biased produces a biased AI.

Regulation is catching up. The EU AI Act classifies recruitment AI as high-risk and imposes significant requirements on transparency, fairness testing, and human oversight. Similar regulations are emerging elsewhere. This is creating demand for people who understand AI fairness, audit AI systems for bias, and ensure compliance with emerging regulations. It's one of the growth areas in recruitment.

What to do if you work in recruitment

If you're at an agency: Specialise or move. Generalist agency recruitment is not a viable long-term career. Find a niche where your expertise and relationships provide genuine value that AI can't replicate. Executive search, specialist technical recruitment, and roles requiring complex candidate assessment are more defensible.

If you're in-house: Move towards the strategic end. Employer branding, candidate experience, diversity strategy, hiring manager coaching. The processing work is being automated. The strategic and consultative work is growing.

If you're in recruitment technology: This is probably the best position. The tools that power AI recruitment are a growth market. If you understand recruitment and can work with AI tools, you're valuable.

If you're a hiring manager: Understand that the AI screening your candidates has limitations. Ask your recruitment team how the AI works, what it optimises for, and what it might miss. The best candidate for your role might be getting filtered out because they didn't use the right keywords. Push for human review of borderline candidates.

Watch for restructuring signals in your organisation. Recruitment teams are often early targets for AI-driven restructuring because the ROI case is so clear — fewer recruiters processing more applications with AI assistance.

The one thing to do today: if you're a recruiter, try using the AI tools that candidates are using. Apply for a few jobs with an AI-crafted CV. Use a chatbot interview prep tool. Understanding the candidate experience of AI-mediated hiring will make you better at your job and help you understand what's coming.