Candidate Use of AI is Changing Hiring, Assessment Needs to Catch Up
Employers who have used traditional hiring methods of CVs, cover-letters and application forms to shortlist candidates are finding that this approach is becoming less and less effective.
It should be expected that candidates have, and will, always look for ways to get an edge in a recruitment process. As organisations have used more automated approaches to evaluate applications, so have candidates used technology to write these applications.
While candidates would have used support from mentors, recruiters and friends to help them in applications, AI technology provides a more powerful form of assistance and no method of assessment is immune.
Candidate use of AI is not just changing applications. It is exposing weakness in hiring processes that were already there. And for organisations that do not adapt, the risk is clear. Better applications. Less real signal. Worse hiring decisions.
One of the least helpful ways to frame this issue is as a simple question of whether candidates are cheating. That might feel like the obvious concern, but if employers stop the conversation there, they miss the bigger point.
The rise of candidate AI use is not just a candidate behaviour issue. It is an assessment design issue.
If your process relies heavily on poor assessment practices to begin with then it lends itself to being much more easily gamed with AI support.
The CV has always been a blunt tool. It can tell you something about career history, choices and relevance. It can sometimes give a sense of progression or impact. But decades of research continually show it is only slightly more accurate in predicting future job success that tossing a coin. Plus, when compared to tossing a coin, a CV is far more likely to have a negative impact on inclusivity!
The same applies to written applications. Many employers still place a surprising amount of weight on polished written responses, especially in the early stages of recruitment. Yet writing quality, confidence and access to support have always shaped those responses, often as much as capability itself.
Interviews can be a great source of insight into a candidate’s communication style, personal fit and an opportunity to establish rapport. However, when delivered poorly they can also be a source of error in hiring. Often interviewer training cites poor practice as inconsistent, inappropriate or irrelevant questionings. However, simply following a standard well-designed script can also cause issues if an answer prepared by AI is not properly probed by the interviewer.
AI does not create that flaw. It magnifies it. When everyone can present more persuasively, presentation stops being the differentiator employers think it is.
That does not mean CVs and applications have no role. But it does mean they should no longer carry the level of assessment weight they still do in many organisations.
Furthermore, relying only on one type of assessment, especially when this is generic or not linked to the role, leaves organisations more susceptible to candidates using AI. This is especially true at the earlier stages of a selection process where organisations will inevitably make more assessment decisions.
This is the shift many hiring teams are now feeling.
Applications look strong. Profiles seem aligned. Responses sound thoughtful. Shortlists appear promising. Then candidates reach interview or assessment and the substance is not where it was expected to be.
The gap is becoming more common.
Not because candidates are suddenly less capable, but because the distance between how someone presents and what they can actually do is becoming easier to widen.
For employers, that has two clear implications.
First, early-stage screening needs to become more rigorous. Not tougher for the sake of it, but smarter about what it is actually measuring.
Second, assessment needs to move closer to the real work.
That is the part many organisations have still not fully grasped. The answer is to redesign assessment so that it tests what genuinely matters in the role.
The employers who respond best to candidate AI use are unlikely to be the ones trying hardest to catch people out. They will be the ones building stronger, more job-relevant assessment processes.
That starts with a simple principle.
If candidates can use AI to improve how they present themselves, employers need to place more emphasis on how candidates think, solve problems, make decisions and apply judgement.
That usually means shifting away from overreliance on:
And moving towards:
None of that is particularly radical. But it does require organisations to be more intentional than many currently are.
One of the biggest weaknesses in traditional hiring is that too many assessment stages bear little resemblance to the role itself. Candidates are asked broad questions, expected to speak confidently about strengths, or judged heavily on how polished they appear in formal settings.
A stronger approach is to use multiple assessments over the course of a selection process. Each assessment should be chosen based on its accuracy in providing relevant insight. Each assessment should be linked to the specific behavioural or technical skills needed in the role. Each assessment should help to build up an overall picture of the candidate’s suitability for the role and complement, not duplicate, what is being asked before. Ideally, each assessment should also provide some insight to the candidate on what is expected of them in the role. This could include a validated online assessment, a structured behavioural or technical interview, or even a work sample task or simulation.
The closer your assessment gets to work, the harder it becomes to bluff and the easier it becomes to make fairer decisions.
That matters for quality of hire, but also matters for candidate confidence. Most people are more likely to trust an assessment process when it feel relevant rather than arbitrary.
This point is important, because the conversation can become too one-sided if it’s not handled carefully.
AI use by candidates is not always about gaining an unfair edge. In some cases, it helps people communicate more clearly, structure their thoughts or overcome barriers that might otherwise hold them back. For some candidates, that may improve access rather than undermine fairness.
That is one reason why blanket opposition is unlikely to be helpful.
The better response is not to try to remove AI from the equation entirely. It is to create hiring processes that are fair, relevant and resilient enough to assess capability properly, regardless of the support tools candidates may have used beforehand.
That is a much stronger position to take.
Because it shifts the focus away from policing behaviour and towards improving assessment quality.
This is the part HA and TA leaders should take seriously.
It is easy to look at AI-enabled applications and conclude that the problem sits with candidates. But the more strategic risk sits elsewhere.
If organisations keep using hiring methods that are no longer robust enough for the market they are operating in, they will make weaker hiring decisions while believing their process is still round.
That is the danger.
A process can appear structured and professional while quietly losing its ability to distinguish between polished presentation and real capability. Over time, that affects quality of hire, manager confidence and the credibility of Talent Acquisition itself.
And once hiring managers begin to feel that the process is no longer helping them identify the right people, trust breaks down internally as well as externally.
That is why this issue needs more than a policy statement on AI use. It needs assessment redesign.
For organisations wondering where to start, the most useful move is usually to focus on the parts of the process most exposed to presentation bias.
A sensible starting point would be:
Build an assessment process that ensure each of the critical ones are assessed multiple times.
If written responses are doing too much of the filtering work, that is now a risk.
A short, well-designed online assessment often gives more insight than another round of written responses
Good probing and consistent scoring matter much more in an AI-enabled candidate market.
Candidates are more likely to trust the process when assessment criteria feel clear and relevant.
Candidate use of AI is not going away. If anything, understanding how individuals will perform when using AI is a better prediction of their ultimate job success.
That means the employers who continue to rely on yesterday’s assessment methods will find it harder to identify the right people with confidence.
The organisations that adapt, on the other hand, have an opportunity.
They can build processes that are more robust, more relevant and fairer than many of the models they replace. They can move towards assessing real capability. And they can give hiring managers greater confidence that the process is helping them make better decisions, not just more adminstratively tidy ones.
That is where this needs to go.
Because AI is not breaking hiring.
But it is exposing where hiring was already weaker than many organisations realised.
And for employers prepared to respond, that is not a threat. It is a chance to build a better assessment model than the one they had before.
If candidates are changing how they apply, employers need to change how they assess. Our latest Candidate Experience Report explores how candidate behaviour is evolving and what that means for hiring decisions
At Omni, we prioritise an evidence-based approach that ensures reliable and effective assessment processes. Our team of expert Organisational Psychologists brings extensive experience in designing and delivering robust assessments that are inclusive, skills-focused, and tailored to your unique organisational needs. We also offer flexibility and support throughout the assessment process, ensuring successful implementation and tangible results.
Our assessment solutions are designed to elevate your hiring process by identifying the best candidates based on their skills, potential, and fit for the role. We help you define the critical competencies required for success, develop tailored assessments that accurately evaluate these competencies, and provide deep insights into candidates’ aptitude and personality traits. This evidence-based approach improves productivity, reduces turnover, and ensures a positive candidate experience. There are several benefits that personality profiling can bring to the recruitment process, such as supporting inclusive hiring, improved decision making, and increased efficiency.
Our internal team of Psychologists can both design and you facilitate assessments for change. We use the same of rigour and evidence based assessment for restructures as we do for external recruitment. We understand the additional pressure and stress internal change brings, and so our assessments are designed with this in mind, supportive to both leaders as well as employees directly affected.
At Omni, we believe that lasting success begins with a tailored, people-centric approach. Our recruitment process goes beyond matching skills to roles – we focus on building long-term partnerships that drive strategic outcomes for both clients and candidates.
