AI-generated CVs have gone from being unusual to being the norm in a relatively short period of time.
Candidates now use AI tools routinely when putting their applications together. CV-Library’s 2026 AI in Recruitment Survey, referenced in their article “How to spot AI-generated CVs and screen candidates more effectively” (8 May 2026), found that 79% of recruiters have seen a rise in AI-generated applications, and 81% say CVs now lack personality or distinction.
That second figure is the one that should concern you as an employer. When every CV starts to sound the same, the detail you need to make a good hiring decision disappears. Strong candidates get lost in a stack of polished, similar-looking and sounding applications, and the risk of making the wrong hire increases.
A candidate using AI to help write their CV is not, on its own, a reason to reject them. Plenty of good people use AI to structure their experience properly, especially if English isn’t their first language or if they’ve never had to write a professional CV before. The question isn’t whether AI helped write the document. The question is whether the person behind it can actually do the job.
At Aspire Jobs, we have a robust screening process that digs deeper than the CV. These are some of the things we look out for:
- Generic language that could apply to almost anyone. Phrases like “results-driven professional” or “proven track record” tell you nothing about what the person has actually done.
- Prolific AI words in use: navigating, transformational, powerful, fostering.
- It’s not this; it’s that phrasing. Short staccato sentences.
- Achievements with no numbers attached. “Improved team performance” means nothing without a figure, a timeframe, or some further context.
- Formatting that is suspiciously uniform. Every role is described in identical rhythm, with no variation in how the person talks about their own work.
- A mismatch between the CV and how the candidate communicates on a call or in a covering letter.
- No mention of the practical detail: tools used, team size, budgets, systems, or the specific challenges they dealt with.
None of these on their own proves a CV is dishonest. They tell us where to look harder.
In every screening interview we run, whether the role is based in Dorset, Hampshire, or anywhere else in the country, we do that digging. We ask candidates to talk us through a specific achievement in their own words. We ask what their actual role was in a project, not the team’s role, and we ask what went wrong before it went right, because that’s the part AI tends to gloss over; AI loves to be super positive!
CVs are only one piece of the recruitment puzzle, which is exactly why the human approach we take at Aspire Jobs is the antidote to over-reliance on them