On a recent episode of the RecTech podcast, host Chris Russell sat down with Brianna Huynh, VP of Brand and Creative at Appcast, to discuss how generative AI is shifting candidate behavior and altering how companies should approach their career sites and employer branding.
Candidates aren’t just scrolling through traditional job boards anymore—they are turning to AI tools like ChatGPT and Gemini to discover roles, evaluate company culture, and summarize job opportunities. Because of this, career sites are no longer read solely by humans; they are now parsed, filtered, and judged by AI.
Here are the key takeaways from their conversation:
1. Traditional SEO vs. Generative Engine Optimization (GEO)
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SEO is deterministic; GEO is probabilistic: With traditional SEO, practitioners adjust specific factors to reliably climb rankings and capture clicks. With GEO and AI-driven discoverability, prompting a tool ten times can yield ten different answers. Rather than trying to “game” a ranking, the goal becomes securing recommendations and ensuring accurate representation.
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The 80% rule: Huynh notes that technical GEO relies heavily (about 80%) on sound SEO foundations. If a site has strong technical SEO, it is more likely to perform well with AI scrapers.
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Context is king: The remaining 20% comes down to deep context, real relationships, and answering specific questions. Tools like employee testimonials and structured FAQs go a long way with AI models seeking clear, direct answers.
2. The Danger of Vague Job Descriptions
Relying on generic phrases such as “competitive salary” or “dynamic culture” creates major blind spots:
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When an AI cannot find clear, concrete data on your career site, it doesn’t give up. Instead, it scrapes third-party sources—like Glassdoor, Indeed reviews, and Reddit threads—to fill in the blanks.
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The AI will present those subjective reviews as factual answers to candidate prompts.
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Employers must close the brand narrative gap by publishing transparent details regarding compensation, benefits, and team expectations directly on their own sites so AI models pull from accurate, first-party data.
3. Human Experience vs. AI Architecture
When designing a modern career site, should you cater to algorithms or people?
According to Huynh, the answer is both, but for different layers of the experience:
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Design the front end for humans: Job seekers still want rich media, authentic video testimonials, engaging photography, and an intuitive application flow.
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Structure the back end for AI: Use structured schema markup, clean headers, and labeled data so search robots and AI crawlers can effortlessly ingest, understand, and summarize the site’s content.
4. Who Owns the Career Site?
As career sites become more technical and strategic, Russell and Huynh touched on who within an organization should lead the effort:
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Talent Acquisition (TA): Holds primary ownership and accountability for site performance and candidate conversion.
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Marketing / Corporate Communications: Shapes the storytelling, brand voice, and overall narrative.
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IT: Ensures technical compliance, accessibility, and site security.
Quick Wins: How TA Leaders Can Optimize Today
If you run an audit on platforms like ChatGPT, Gemini, or Claude and find your company’s career site is invisible or misrepresented, consider these first steps:
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Implement structured schema markup: Work with your career site provider or web development team to ensure headers, job descriptions, and company details are clearly marked up on the back end for crawlers.
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Address content gaps head-on: If AI summaries are surfacing negative or incomplete reviews regarding compensation or culture, build dedicated landing pages that directly and transparently address those topics.
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Use AI to edit, not invent: Avoid letting generative AI fill job posts with fluff. Instead, use AI to refine and polish real, detailed specifics provided by hiring managers.
