2026-08-03 · Jack Stovell

AI visibility for job seekers: how recruiters' AI tools see you

Two different machines read a job seeker: the ATS parser that scans the CV you submit, and the AI assistants and search tools a recruiter uses to look you up by name. They read different documents, fail in different ways, and have to be fixed separately. Getting both right does not get you a job — it stops you being invisible to one machine and misread by the other.

How do recruiters use AI to screen candidates?

At two points: when you apply, and when they check you out. At application time, an applicant tracking system parses your CV into structured fields — name, roles, dates, skills — and recruiters filter and search on those fields, so a CV that parses badly is effectively blank no matter how strong its content. Away from the application pipeline, recruiters increasingly ask assistants and search tools about a candidate by name before a call. Vendor specifics are opaque — ATS products differ and none publish their parsing rules — so the honest strategy is not to game one system but to be cleanly readable by all of them.

How do you make your CV readable by AI?

Make it structurally boring. The layout choices that survive the widest range of parsers:

One column. Multi-column layouts scramble reading order in many parsers, interleaving unrelated lines.
Standard headings — Experience, Education, Skills — not creative alternatives a parser has never seen.
Real text everywhere. No skills-as-graphics, no text baked into images, no key facts in headers or footers, which some parsers skip entirely.
Recognisable job titles and explicit dates on every role.

Keep the caveat in view: ATS behaviour varies between vendors and versions, and nobody outside those companies knows exactly what each one does. A single-column, real-text CV is not guaranteed to parse perfectly — it is the format with the fewest known failure modes, which is the strongest claim anyone can honestly make.

What does a recruiter's AI see when it looks you up?

Whatever is publicly crawlable under your name — which for many candidates is nothing, or someone else. A recruiter asking an assistant about you triggers a live search over open pages; what does ChatGPT see when it looks you up? shows how to run exactly that test on yourself before a recruiter does. Do not assume LinkedIn has this covered: most of a LinkedIn profile sits behind a login wall that AI assistants cannot fetch, so the page you polish is largely unreadable to the tools reading you. If nothing crawlable exists, the assistant has nothing to work with; if only fragments exist, it fills the gaps with guesses — or with a different person who shares your name.

Is your CV a public identity source?

No. A CV is a document you hand over, not a page a machine can find. It lives in inboxes and ATS databases, not on the open web, so it contributes nothing to what surfaces when someone searches your name — and even hosted on a personal site, a PDF is a weaker source than an HTML page, as the format comparison in can AI read Notion, Substack, Medium or your PDF CV? sets out. The fix is one public, crawlable page stating who you are, what you do and what you have done — with the generic plumbing every profile needs (open access, Person JSON-LD, a bio consistent with your CV and your other surfaces) covered in how to create an AI-readable profile of yourself. Consistency matters doubly here: a recruiter's tools see both your CV and your public page, and contradictions between them read as noise, or worse.

What won't AI visibility get you?

An interview you were not qualified for. Nothing on this page substitutes for the actual record — skills, experience, references — and a recruiter's tools sit in front of human judgement, not in place of it. What this work removes are the two failure modes you control: the application filtered out because a parser could not read the CV, and the name search that returns nothing or the wrong person. Invisible and misread are both fixable. That is the whole claim.

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