Does Your Resume Read as AI-Generated? What Recruiters Actually Notice

Recruiters who read hundreds of resumes a week have gotten fast at spotting a particular texture of writing — not because they can reliably detect whether AI was involved (no one can do that with real accuracy, despite what some tools claim), but because a specific set of patterns has become extremely common, and those patterns read as generic regardless of how they were produced.

Here's what actually triggers that reaction, and what to do about each one.

Banned phrases and buzzwords

Certain words have been used so often, in so many resumes, that they've stopped carrying information. "Results-driven," "proven track record," "synergy," "cross-functional," "self-starter," "go-getter" — these phrases describe a category of person rather than anything specific about you. A recruiter's eyes slide past them because they've seen the exact same words thousands of times.

The fix isn't a better synonym. Swapping "leveraged" for "utilized" doesn't help — it's still an empty verb. The fix is replacing the vague claim with the concrete thing you actually did.

Every bullet has the same shape

Read your bullets in sequence. If every single one starts with "Verb + adjective + noun" — "Spearheaded innovative solutions," "Drove strategic initiatives," "Delivered exceptional results" — the uniform cadence itself reads as generated, even if no individual bullet contains a banned word. Real accomplishments don't naturally compress into identical sentence shapes, because real work varies.

The fix: vary sentence structure the way you'd naturally vary it if you were describing your work out loud to a colleague.

Claims with no concrete object

"Drove significant improvements" — to what, specifically? "Enhanced operational efficiency" — which operation, and how? A claim becomes credible the moment it names a real system, team, process, or number. Without that, it's an assertion a reader has no way to evaluate, and experienced reviewers have learned to discount assertions like this by default.

Suspiciously round, unsupported metrics

"Improved efficiency by 50%" with no named process or baseline reads as a number chosen for effect rather than measured. This doesn't mean don't use numbers — real, specific metrics are one of the strongest things a resume can contain. It means a number needs the context that makes it verifiable: efficiency of what, measured how, compared to what baseline.

Why this matters even though "AI detection" isn't real

It's worth being direct about something: there is no reliable, validated way for a recruiter or a tool to determine whether a specific resume was written with AI assistance. Detection tools that claim to do this are not backed by credible evidence — one of the few independent studies on the topic found human raters distinguishing AI-assisted text from human-written text at roughly chance level.

So the goal isn't passing an "AI detector." It's avoiding the actual patterns above, because those patterns read as generic and get skimmed past regardless of how the resume was produced — by a template, by an AI tool used carelessly, or by a person defaulting to resume-speak out of habit. The fix is the same either way: specificity.

How to check your own resume

Read each bullet and ask: could this sentence, word for word, describe someone else in a similar role at a different company? If yes, it's too generic — even if every word in it is true. A bullet that could only describe your specific work, because it names the specific system, team, or result, is doing its job.

JobSeekersHub.app scores every tailored resume against this exact list — banned phrases, uniform cadence, inflated claims, unsupported metrics — and flags each one with a specific fix, so you can see where a resume is generic before a recruiter does.