When Everyone Has a Perfect CV, How Do We Find the Exceptional Candidate?

After more than 30 years in recruitment, I have seen the industry evolve in ways few could have predicted. The arrival of AI is one of the most significant shifts yet—not because it replaces recruitment, but because it is quietly changing the behaviour of both candidates and employers.

AI can now write a highly polished CV in seconds, tailor it to a job description, and even rehearse interview answers. It also enables candidates to apply for far more roles than they would previously have considered, often without genuinely reflecting on whether the opportunity is right for them.

The result is a paradox. Employers have more applicants than ever before, yet identifying genuinely strong, genuinely interested candidates is becoming harder.

LinkedIn has reported a sharp rise in application volumes, and much of this is widely attributed to AI-assisted applications. At the same time, the World Economic Forum has highlighted that over 90% of employers now use some form of automated system—such as applicant tracking systems or AI-enabled screening tools—to filter, rank or shortlist candidates. In other words, AI-generated applications are increasingly being assessed by AI-driven systems before a human ever sees them.

So the question becomes unavoidable: where does that leave human judgement—and genuine interest in the role?

A polished answer is no longer proof of understanding

We are already seeing candidates who perform extremely well in remote interviews but struggle when the conversation becomes more probing or moves into a face-to-face environment.

This does not automatically indicate dishonesty. In fact, most sensible candidates now use AI in some form—to research companies, refine CVs, or prepare for interviews. That is simply the modern equivalent of using search engines, mentors or preparation notes.

The issue arises when preparation becomes substitution—when a candidate can deliver a perfect answer but cannot explain the thinking, experience or trade-offs behind it.

At that point, the difference between knowledge and understanding becomes very clear.

Interviewers therefore need to adapt. The answer is not simply to ask more questions, but to ask better ones.

What did you do first?
What went wrong?
What would you do differently?
Which option did you reject, and why?
How did your decision affect the wider programme?

It is remarkably difficult to fabricate real experience when someone is asked to go beyond rehearsed responses and into the detail of decision-making.

Some employers are already recognising this shift. The Financial Times has reported that organisations such as EY and L’Oréal are introducing “AI-free” elements into their recruitment processes, placing greater emphasis on in-person discussion, scenario-based assessment and exercises designed to test judgement rather than memorised answers.

The CV is only the beginning

At TalentHawk, we have never believed recruitment is simply about matching keywords on a CV to a job description.

A CV cannot tell you how someone behaves when a programme is under pressure, whether they will challenge a delivery partner when it matters, or how effectively they will represent a client in difficult stakeholder environments.

It also cannot tell you something equally important: whether a candidate is genuinely interested in the role, the client, and the work itself.

That is why recommendation remains central to how we operate.

We value working with people whose delivery we know, or who come recommended by professionals whose judgement we trust. Many of our contractors have worked with us before—sometimes across multiple clients and programmes. We understand how they operate, how they communicate, and where they add the most value.

We are also genuinely interested in candidates who are recommended to us by people we respect. A strong recommendation is rarely just about capability; it is about attitude, reliability, and how someone behaves when things are difficult.

That does not mean we operate a closed network. Far from it. New talent must always be able to enter. But entry into a trusted community should be earned through proper assessment, credible references, strong recommendation, and ultimately, proven delivery.

AI can help us work more intelligently. It can surface candidates we might otherwise miss, improve search capability, and free consultants to spend more time speaking to people rather than processing data.

What it cannot do is turn an unproven candidate into a proven one—or create genuine interest where none exists.

As CVs become more polished and applications more abundant, recruitment businesses should not compete on volume. They should compete on clarity: clarity about who can actually deliver, and who is genuinely engaged in the opportunity.

The future of recruitment will undoubtedly involve more technology. But the exceptional candidate will still be identified by looking beyond the perfect CV—and by recognising real intent, not just well-written answers.

We remain genuinely interested in candidates, in people who are recommended to us, and in those who are recommended by professionals we already trust.

And finally, if you know delivery consultants who consistently perform, who clients would happily work with again, and who you would confidently recommend—please introduce them to us. We would genuinely like to know them, and to help them find the right opportunities in the future.

Sources: World Economic Forum—Hiring with AI doesn’t have to be inhumane and Financial Times—Why recruiters are making interviews AI-free zones.