Recruiters have always received applications from candidates who exaggerate their experience or use generic CV templates. Artificial intelligence has significantly increased the scale of that challenge.
A candidate can now generate a polished CV, tailored cover letter and convincing answers to common application questions within minutes. Used responsibly, these tools can help capable people communicate their experience more clearly. However, they can also produce applications that sound impressive while revealing very little about the person behind them.
For recruiters, the problem is not that every candidate uses AI. The problem is that traditional application documents are becoming weaker indicators of genuine skill.
Why Application Volume Is Increasing
AI tools reduce the time required to customize an application. Candidates can quickly match language from a job description, rewrite their professional profile and produce several versions of a cover letter.
This encourages some applicants to apply for far more roles than they would have considered previously. Employers may receive a large number of well-written submissions from people who have not carefully evaluated the position.
A higher application count does not necessarily create a stronger talent pool. It can increase screening time while making genuinely suitable candidates harder to recognise.
Polished Language Is No Longer Enough
Professional writing once suggested that a candidate had invested time in understanding the vacancy. Today, polished language may simply indicate access to an effective AI tool.
Recruiters should focus less on how sophisticated an application sounds and more on whether its claims are specific and supported.
Statements such as “delivered innovative solutions in a fast-paced environment” provide little evidence. Stronger applications explain what the candidate built, what constraints they faced, which decisions they made and what changed as a result.
The goal is not to punish candidates for using AI. It is to distinguish clear communication from unsupported presentation.
Ask Questions That Require Real Experience
Generic questions produce generic AI-generated answers. Recruiters can obtain better evidence by asking candidates to describe a particular decision, mistake or trade-off.
Instead of asking, “What is your greatest strength?” ask the candidate to explain a situation in which that strength changed the outcome of a project.
For technical roles, ask what failed during implementation, how the problem was diagnosed and why one solution was chosen over another. Candidates who completed the work should be able to discuss details that are difficult to reproduce through surface-level preparation.
Introduce Practical Work Samples
A short, relevant work sample can reveal more than another written application question. Developers might review a small piece of code, designers could critique an interface and project managers could prioritise a realistic set of competing requests.
The task should reflect the role without demanding hours of unpaid work. It should also include an opportunity for the candidate to explain their reasoning.
A perfect answer is less important than the process. Recruiters should look for judgement, communication, curiosity and the ability to recognise uncertainty.
Use Live Follow-Up Questions
AI-generated responses often sound complete because they remove hesitation and complexity. Real professional experiences are usually more nuanced.
During an interview, follow up on important claims. Ask what the candidate would change, which stakeholder disagreed or how the result was measured. These questions help determine whether the person understands the experience described in the application.
Live discussion should remain respectful. The purpose is to explore evidence, not to make every candidate feel accused of deception.
Establish a Clear AI-Use Policy
Employers should explain where AI assistance is acceptable. Candidates may be allowed to use it for editing a CV but prohibited from receiving live answers during an interview. Technical assessments might allow AI if using it reflects the actual job.
A clear policy creates a fairer process than leaving candidates to guess. It also allows employers to assess AI fluency openly when that skill matters to the role.
Review the Recruitment Process Itself
An overwhelming number of unsuitable applications may indicate that the vacancy is too broad, the requirements are unclear or the application process rewards keyword matching.
Employers can use Dynamic Brand Gurus to publish opportunities with specific responsibilities and realistic requirements. A well-defined vacancy helps serious candidates assess their suitability before applying and gives recruiters clearer evidence to evaluate.
AI has not made CVs useless, but it has changed what recruiters should expect them to prove. The most reliable hiring processes will combine written applications with specific evidence, practical tasks and thoughtful human conversation.
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