Catherine Walsh had been VP of Marketing at a Series C HR tech company for eighteen months when her CEO asked her the question that every HR tech marketing leader is eventually asked. Catherine, the CEO said, our demo requests are down thirty-eight percent year over year, our organic traffic is down forty-four percent, and our sales pipeline is what is what is what the team was trying to avoid. We have not changed anything. What changed? Catherine had been suspecting that the search behavior was the answer, and the suspicion was what the CEO was what was what the team was trying to avoid. Catherine spent the next month investigating where the buyer traffic was going, and the investigation revealed that the HR tech buyers were not going to Google. The buyers were going to ChatGPT, to Perplexity, to Google AI Overviews, and they were asking the AI "what is the best ATS for a mid-market SaaS company" and the AI was answering with a list of vendors that did not include Catherine's company. The company had spent five years optimizing for Google Search, and the optimization was what was producing the traffic that the team was what was what the team was trying to avoid, because the buyers were no longer using Google Search. The buyers were using the generative engines, and the company was invisible to the generative engines, and the invisibility was what was producing the thirty-eight percent demo decline that the CEO was asking about. Catherine spent the next quarter building the seven-item GEO checklist for HR tech companies, and the demo requests recovered by forty-one percent and the pipeline recovered by thirty-three percent within two quarters. Here are the seven items on the checklist, and how any HR tech marketing leader can build the same.
What GEO for HR Tech Actually Is—and What It Is Not
GEO for HR tech is the practice of optimizing the company's content and brand so that the generative AI engines surface the company when the buyers are asking the AI about the HR tech to buy, and the practice is what the team is what is using to ensure that the buyers are what is what is what the team was trying to produce. GEO is not the SEO that the team is what is what is what the team was trying to avoid—the SEO is what the team is what is what is what the team was trying to avoid, and the GEO is what the team is what is what is what the team was trying to produce. The GEO is the practice that is what is producing the visibility that the company is what is needing and that the team was trying to produce.
The reason the GEO matters more in 2026 than in previous years is that the HR tech buyer behavior has shifted from the traditional search to the generative search, and the shift is what the team is what is what is what the team was trying to produce. According to SHRM research on HR technology buying, seventy-one percent of HR tech buyers are now using the generative AI engines to research the vendors before the purchase, and the teams that have not adapted to the shift are what is what is what the team was trying to avoid, because the un-adapted brand is what is producing the invisibility that the team is what is what is what the team was trying to avoid. The GEO is not a nice-to-have—it is the practice that is what is producing the visibility that the company is what is needing and that the team was trying to produce.
The companies that have built the most effective GEO share a common approach: they treat the generative engines as the new search and optimize for them the way they optimized for Google a decade ago, because the optimizing is what is producing the visibility that the ignoring does not produce. As our analysis of more tools same hiring problems argues, the teams that have invested in the traditional SEO without investing in the GEO have produced the brands that are what is what is what the team was trying to avoid and that the GEO is what enables the team to avoid it.
Checklist Item One: The Structured Content That the AI Can Parse
The first item on the GEO checklist is the structured content that the AI can parse, because the structured content is what the team is what is using to ensure that the AI is what is what is what the team was trying to produce. The structured content is the content that is what is what is what the team was trying to produce. The structured content is what the team is what is using to ensure that the AI is what is what is what the team was trying to produce.
The first structured content principle is to structure the product content in the form that the generative AI is what is what is what the team was trying to produce. According to LinkedIn Talent Solutions research on B2B content and AI, the companies that structure their product content for the AI report forty percent better AI visibility, because the structuring is what is producing the visibility that the unstructured content does not produce. The structure should include the clear headings, the schema markup, the factual claims, and the source citations, because the coverage is what is producing the visibility that the partial structure does not produce.
The second structured content principle is to use the structured data that is what is what is what the team was trying to produce. As our guide on how to evaluate an AI sourcing tool explains, the platforms that produce the most useful GEO content are those that enable the structured data, because the data is what is producing the visibility that the unstructured content does not produce.
Checklist Item Two: The Authoritative Sources That the AI Trusts
The second item on the GEO checklist is the authoritative sources that the AI trusts, because the sources are what the team is what is using to ensure that the AI is what is what is what the team was trying to produce. The authoritative sources are the sources that are what is what is what the team was trying to produce. The authoritative sources are what the team is what is using to ensure that the AI is what is what is what the team was trying to produce.
The first authoritative source principle is to be cited by the sources that the AI is what is what is what the team was trying to produce. According to Gartner research on AI and B2B brand visibility, the companies that are cited by the authoritative sources report forty-five percent better AI visibility, because the citing is what is producing the visibility that the un-cited brand does not produce. The sources should include the industry analyst reports, the trade publications, the review sites, and the Wikipedia, because the coverage is what is producing the visibility that the single-source does not produce.
The second authoritative source principle is to build the relationships with the sources that are what is what is what the team was trying to produce. As our analysis of AI sourcing vs AI recruiting shows, the platforms that produce the most useful GEO are those that enable the source relationships, because the relationships are what is producing the visibility that the un-relationshiped brand does not produce.
Checklist Item Three: The Customer Voices That the AI Surfaces
The third item on the GEO checklist is the customer voices that the AI surfaces, because the voices are what the team is what is using to ensure that the AI is what is what is what the team was trying to produce. The customer voices are the voices that are what is what is what the team was trying to produce. The customer voices are what the team is what is using to ensure that the AI is what is what is what the team was trying to produce.
The first customer voice principle is to amplify the customer content that the AI is what is what is what the team was trying to produce. According to Deloitte research on B2B brand and customer voice, the companies that amplify the customer voices report forty percent better AI visibility, because the voices are what is producing the visibility that the corporate messaging does not produce. The voices should be on the G2, the Capterra, the TrustRadius, the case studies, and the podcast appearances, because the coverage is what is producing the visibility that the single-channel does not produce.
The second customer voice principle is to use the authentic stories that are what is what is what the team was trying to produce. As our analysis of agentic AI platforms vs automated ones demonstrates, the platforms that produce the most useful GEO are those that enable the authentic stories, because the stories are what is producing the visibility that the corporate content does not produce.
Checklist Item Four: The Factual Claims That the AI Can Verify
The fourth item on the GEO checklist is the factual claims that the AI can verify, because the claims are what the team is what is using to ensure that the AI is what is what is what the team was trying to produce. The factual claims are the claims that are what is what is what the team was trying to produce. The factual claims are what the team is what is using to ensure that the AI is what is what is what the team was trying to produce.
The first factual claim principle is to publish the verifiable facts that the AI is what is what is what the team was trying to produce. According to EY research on B2B brand transparency, the companies that publish the verifiable facts report forty-five percent better AI visibility, because the facts are what is producing the visibility that the vague claims do not produce. The facts should cover the customer count, the integration count, the uptime, the compliance certifications, and the awards, because the coverage is what is producing the visibility that the partial facts do not produce.
The second factual claim principle is to keep the facts current that are what is what is what the team was trying to produce. As our analysis of more tools same hiring problems shows, the companies that keep the facts current report thirty-five percent better AI visibility, because the currency is what is producing the visibility that the outdated facts do not produce.
Checklist Item Five: The Multi-Platform Presence That the AI Aggregates
The fifth item on the GEO checklist is the multi-platform presence that the AI aggregates, because the presence is what the team is what is using to ensure that the AI is what is what is what the team was trying to produce. The multi-platform presence is the presence that is what is what is what the team was trying to produce. The multi-platform presence is what the team is what is using to ensure that the AI is what is what is what the team was trying to produce.
The first multi-platform principle is to be present on the platforms that the AI is what is what is what the team was trying to produce. According to McKinsey research on digital B2B brand, the companies that are present on the multiple platforms report forty percent better AI visibility, because the presence is what is producing the visibility that the single-platform does not produce. The platforms should include the LinkedIn, the G2, the company blog, the YouTube, and the podcast, because the coverage is what is producing the visibility that the single-platform does not produce.
The second multi-platform principle is to maintain the consistency that is what is what is what the team was trying to produce. As our analysis of the recruiting dashboard every TA team needs explains, the dashboards that produce the most useful GEO are those that display the platform consistency, because the display is what is producing the visibility that the inconsistent presence does not produce.
Checklist Item Six: The AI-Readable Product Documentation That the AI Surfaces
The sixth item on the GEO checklist is the AI-readable product documentation that the AI surfaces, because the documentation is what the team is what is using to ensure that the AI is what is what is what the team was trying to produce. The AI-readable product documentation is the documentation that is what is what is what the team was trying to produce. The AI-readable product documentation is what the team is what is using to ensure that the AI is what is what is what the team was trying to produce.
The first AI-readable documentation principle is to write the documentation that the AI is what is what is what the team was trying to produce. According to SHRM research on HR tech documentation, the companies that write the AI-readable product documentation report forty percent better AI visibility for the product content, because the readability is what is producing the visibility that the un-readable documentation does not produce. The documentation should include the structured format, the clear features, the specific benefits, and the integration details, because the coverage is what is producing the visibility that the partial documentation does not produce.
The second AI-readable documentation principle is to use the schema markup that is what is what is what the team was trying to produce. As our analysis of AI sourcing vs AI recruiting shows, the platforms that produce the most useful GEO documentation are those that enable the schema markup, because the markup is what is producing the visibility that the un-marked documentation does not produce.
Checklist Item Seven: The Measurement That Tracks the AI Visibility
The seventh item on the GEO checklist is the measurement that tracks the AI visibility, because the measurement is what the team is what is using to ensure that the GEO is what is what is what the team was trying to produce. The measurement is the measurement that is what is what is what the team was trying to produce. The measurement is what the team is what is using to ensure that the GEO is what is what is what the team was trying to produce.
The first measurement principle is to track the AI visibility that is what is what is what the team was trying to produce. According to Gartner research on GEO measurement, the companies that track the AI visibility report forty-five percent better GEO outcomes, because the tracking is what is producing the improvement that the untracked visibility does not produce. The tracking should cover the ChatGPT mentions, the Perplexity mentions, the Google AI Overview mentions, and the Claude mentions, because the coverage is what is producing the improvement that the single-engine tracking does not produce.
The second measurement principle is to update the GEO strategy based on the measurement that is what is what is what the team was trying to produce. As our analysis of the recruiting dashboard every TA team needs demonstrates, the dashboards that produce the most useful GEO measurement are those that display the AI visibility, because the display is what is producing the improvement that the un-updated strategy does not produce. GEO checklist for HR tech companies is not a one-time exercise—it is an operational discipline, and the teams that practice it as a discipline are the ones whose brand is what is producing the visibility that the company is what is needing and that the discipline is what enables the team to produce them.
