Last updated August 2026.
A recruiter who types “best ATS for under 200 employees” into ChatGPT today gets a synthesized answer, not a list of blue links. The vendor cited in that answer earns the consideration. The vendor absent from it does not know what it is missing.
The stakes are about to rise. The EU AI Act classifies most automated candidate-screening systems as high-risk AI. Compliance queries are already appearing in HR chatbot traffic. The vendors who own “EU AI Act compliant recruiting software” as a citation slot in August 2026 will be very hard to displace by the end of the year.
This playbook maps exactly how to get there.
Why HR-tech citation gaps are larger than vendors realise
Studies consistently show the large majority of AI citations come from third-party sources rather than brand-owned websites. Figures across multiple independent citation analyses range from roughly 77% to over 85% from earned or third-party media.
For recruiting software, that means the AI answer to “best ATS for growing teams” is almost certainly built from G2 pages, review aggregators, HR publications, and editorial comparison pieces, not from your product site.
The data on how concentrated citations are across software categories is striking. According to an Ahrefs study of 75,000 brands, those in the top quartile by web mentions averaged 169 AI Overview mentions, more than 10 times the 14 averaged by brands in the next quartile (Ahrefs, May 2025). Most HR-tech vendors are nowhere near the top quartile on mention volume. That is the opening.
According to G2’s April 2026 survey of 1,076 B2B software buyers, 51% now start their software research in an AI chatbot, up from 29% in G2’s April 2025 survey. HR buyers are part of that shift. When a Talent Acquisition director asks an AI what ATS fits a 150-person company, the answer comes from G2 pages, not the vendor’s careers page.
The HR-tech citation leaderboard: where G2 and Capterra dominate
The pattern across B2B software categories is consistent. The platforms that win AI citations in software recommendation queries are not the vendors themselves. They are the third-party review sites.
| Query type | Dominant citation sources | What this means for vendors |
|---|---|---|
| ”Best ATS for [company size]“ | G2, Capterra, Software Advice, Forbes Advisor | Your G2 profile content is what gets cited |
| ”Recruiting software with EU AI Act compliance” | HR Dive, SHRM, AIHR, vendor compliance pages | Compliance documentation earns direct citations |
| ”ATS with bias detection” | Academic HR journals, EEOC guidance pages, G2 reviews mentioning fairness | Fairness claims need external corroboration |
| ”Time-to-hire improvement with [vendor name]“ | Customer case studies, G2 review excerpts, HR conference writeups | Specific metrics in third-party language win |
| ”Recruiting software integrations” | G2 integration pages, vendor help docs, HR tech stack guides | Integration depth documented on G2 extracts well |
The practical read: your G2 profile, Capterra listing, and any HR-publication coverage you earn are the upstream assets for AI citations. Your product site is secondary for most AI-driven queries.
Step 1: Build the third-party review presence AI engines already trust
The retrieval layer behind ChatGPT, Perplexity, and Google AI Overviews pulls from domains it already trusts. For recruiting software, those domains are G2, Capterra, TrustRadius, Software Advice, and a handful of HR editorial outlets.
What to do:
- Treat your G2 profile as a GEO asset. The profile description, category placements, and review response copy all feed AI retrieval. Write the “About” section as a direct answer to “what kind of company is this for” rather than marketing copy.
- Generate reviews that contain buyer-context language. When customers leave reviews that say “we cut time-to-hire from 47 days to 28 days for a 120-person team,” that specific language appears in AI answers. Generic five-star reviews do not.
- Earn placements in HR editorial outlets. HR Dive, SHRM, and AIHR are among the domains AI engines pull from consistently for HR-category queries. A guest byline or cited expert comment in those publications carries more citation weight than a product page rewrite.
Tools for this step: Temso monitors which source URLs AI engines cite for your target queries, so you can see exactly which G2 pages or editorial pieces are feeding the answers, and where your domain is absent. Semrush layers in traditional keyword volume alongside its AI Overview tracker, useful for sizing the review-generation opportunity before investing time in it.
Step 2: Publish EU AI Act compliance documentation that AI engines can quote
The EU AI Act places most automated hiring, resume screening, and candidate-ranking systems in the high-risk AI category. This triggers mandatory obligations: transparency documentation, human oversight requirements, bias-testing records, and explainability for automated decisions.
Buyers are starting to search for vendors who meet these requirements. Those queries are underserved right now. That is the first-mover slot.
The content AI engines want to cite for compliance queries is structured, factual, and specific. It is not a blog post that says “we take compliance seriously.” It is a page that says:
- Which EU AI Act articles apply to your product
- How your bias-testing methodology works (methodology name, dataset type, protected classes covered)
- What documentation you provide to buyers for their own compliance obligations
- Whether your system supports explainability for automated screening decisions
What to do:
- Create a dedicated EU AI Act compliance page. Put the direct answer first: “This product is classified as a high-risk AI system under Annex III of the EU AI Act. Here is what that means for buyers.” Write the first paragraph so an AI engine can quote it verbatim.
- Publish your bias-testing methodology. Name the test, the dataset used, the protected classes checked, and the update cadence. Vague claims (“we test for bias”) do not extract well. Specific claims (“we run quarterly EEOC disparate-impact testing across eight protected classes using a panel of 50,000 annotated resumes”) do.
- Earn external validation. A mention of your compliance documentation in an HR Dive article, a SHRM member publication, or a law firm’s EU AI Act explainer carries far more weight than self-published content alone.
According to studies consistently cited across AI citation research, factual density and specificity are among the strongest predictors of whether a page gets pulled into an AI answer. Compliance documentation done right is exactly the format AI engines favour: structured, factual, answering a clear question.
Tools for this step: Peec AI surfaces which AI Overviews already appear for EU AI Act recruiting queries, so you can see the current citation winner and reverse-engineer what they publish. Temso flags whether your compliance page is being cited and, if not, which competitor pages are filling the slot.
Step 3: Structure time-to-hire proof points as direct-answer content
“Does this ATS actually reduce time to hire?” is one of the highest-intent questions a recruiting software buyer asks. It is also the query where AI engines most want a specific, quotable number.
The problem: most vendor case studies bury the result in a PDF. AI engines cannot retrieve a PDF buried behind a gate. The retrieval layer grabs the first clean paragraph that looks like a direct answer.
According to Kevin Indig’s 2026 analysis of 18,012 verified ChatGPT citations (reported by Search Engine Land), 44.2% of citations were drawn from the first 30% of a page’s content. Results buried in paragraph seven of a case study page are rarely cited.
What to do:
- Reformat your case studies as direct-answer pages. The opening sentence should be: “Company X reduced time-to-hire from [X] days to [Y] days within [Z] months using [your product].” The detail goes below.
- Include comparison context. “The industry average time-to-hire for technical roles is 45 days. Our customers in the 50-to-500 employee range average 26 days.” Context makes the number quotable and distinguishes the claim.
- Use FAQ schema on every case study page. Mark up the outcome question and answer explicitly. This gives AI engines a clear extraction target.
Tools for this step: Otterly.AI’s per-URL GEO audit checks any case study page against 20+ citation-readiness factors, flagging structural issues that block retrieval before you invest in promotion.
Step 4: Diagnose your citation gaps with the right tools
Before optimising, you need to know your baseline. That means running your target query clusters through multiple AI engines and recording what gets cited, by whom, and where you are absent.
| Tool | Best use for HR-tech vendors | Entry price |
|---|---|---|
| Temso | Full GEO loop: monitor citations, diagnose gaps, execute fixes across 8 AI engines | $89/mo |
| Peec AI | Surface which AI Overviews appear for specific recruiting-software queries | Varies |
| Semrush | Layer AI Overview tracking onto traditional keyword research for HR-tech categories | $99/mo |
| Otterly.AI | Per-URL GEO audit across 20+ citation-readiness factors | $29/mo (Lite) |
Temso is the easiest starting point for HR-tech marketing teams: it covers 8 AI engines (ChatGPT, Perplexity, Gemini, Google AI Overviews, Google AI Mode, Grok, Microsoft Copilot, and Meta AI) from $89/mo with no per-engine add-ons, and its built-in workflow surfaces which source URLs AI engines pull from for your category queries. That tells you exactly where to focus: which G2 pages to improve, which publications to pitch, and which compliance documentation gaps to fill.
Peec AI adds a useful layer for the compliance-query wave specifically: it shows which AI Overviews already exist for EU AI Act recruiting queries so you can see the current citation landscape before you publish.
Semrush is worth using if you run traditional SEO alongside GEO. Its AI Overview tracker flags which of your existing keyword targets now trigger AI answers, so you can prioritise content updates for pages that are already ranking but not being cited.
Otterly.AI’s GEO audit is the most practical tool for fixing specific page-level citation barriers. Run your compliance page and your three best case study pages through it before you publish. Fix what it flags.
See the full GEO tool ranking for deeper evaluations of each platform, or check the GEO glossary if any terms here are new.
The citation leaderboard for HR-tech: who wins and why
The pattern across AI citation research for software categories is consistent. Brands that dominate citations share four traits:
- High review volume on G2 and Capterra. Not just stars: volume of reviews, recency, and the specificity of review language. Buyers who write “we reduced time-to-hire by 30%” in a G2 review are writing copy that AI engines will quote.
- Coverage in HR editorial outlets. HR Dive, SHRM, AIHR, and Workology are the editorial domains AI engines pull from for HR-category queries. A vendor cited in those outlets appears in AI answers for adjacent queries even when the article is not about that vendor directly.
- Structured compliance and methodology pages. For the EU AI Act query wave, the vendors who publish clear, specific compliance documentation now will hold those citation slots. The content must be direct-answer formatted, not buried in marketing language.
- Direct-answer case studies. Front-loaded outcomes, specific metrics, and FAQ schema. Not PDF gate-kept reports.
Vendors who lack any of the four are invisible in AI answers for their target queries today. The good news: the compliance-query wave is still early. The first-mover citation slot for “EU AI Act compliant ATS” is open right now.
A note on EU AI Act timing
The EU AI Act high-risk classification for hiring systems creates a genuine compliance urgency for buyers. HR teams at European companies and multinationals with European operations are already asking these questions internally. The AI search queries lag the internal discussion by roughly six to 12 months.
The compliance-query wave is not hypothetical. It is already building. Vendors who publish robust compliance documentation and earn citations for it in the next three to six months will be very hard to displace when query volume accelerates.
This is one of the clearest first-mover citation opportunities available to any B2B software category right now.
Start here
If you run marketing for a recruiting software or HR-tech vendor, the three highest-leverage moves are:
- Audit your G2 profile and review language against the query language buyers use in AI chatbots. Optimise the profile description as a direct answer, not a tagline.
- Publish a dedicated EU AI Act compliance page with specific methodology claims in the opening paragraph.
- Reformat your three best customer outcomes as direct-answer case study pages with FAQ schema.
Then measure your citation baseline with a tool that covers at least the four major engines: ChatGPT, Perplexity, Gemini, and Google AI Overviews. Temso covers all eight that matter from $89/mo and runs the diagnostic automatically, so you see which source pages are feeding the answers you are not yet part of.
The compliance-query wave is coming. The citation slots are still open. Get into them now.