AI is changing how people look for jobs, forcing recruiters to keep up

AI is coming for SEO’s job.

Search engine optimization (SEO) has become an important part of recruiters’ playbooks, dictating how they format their company’s careers site, job postings, and recruitment marketing materials so they surface in search engine results.

But as AI tools reshape how people search for information on the internet, SEO strategy is being upended. AI overviews appear on 21% of Google search results according to a November 2025 analysis by Ahrefs, while certain queries, such as those comprising a long string of words or questions, generated an AI overview at least half the time. And 28% of US adults use AI chatbots and AI search engines to search simple information, according to a survey from content marketing agency Claneo. (To get into the accuracy of the answers provided by these tools would, unfortunately, be to open a can of worms.)

Already for consumer products, companies are adapting their product and website copy to accommodate AI-powered search tools. This strategy, derived from SEO, is referred to by several names, most commonly generative engine optimization (GEO).

Recruiters will have to do the same, experts say.

AI search is already affecting job searches: 11.6% of the more than 1,600 US workers surveyed by employment agency iHire in June 2025 said they’ve used AI tools to research potential employers. Recruitment experts expect that share to grow.

“AI shapes what we decide,” Maria Christopoulos Katris, cofounder and CEO of recruitment platform Built In, said during a panel at Talent Acquisition Week in February. That will apply to job seeking in the not-so-distant future, she added. “Think of a world where, in five years, candidates are starting and stopping their search in the LLMs. You should assume they are starting their search, they’re identifying companies to work for, they're researching you, and they’re making decisions, all without leaving an LLM.”

For employers that don’t tailor their recruitment strategies for AI search tools, experts warned that recruitment costs could increase, as their job postings get ignored or competitors become more frequently recommended by these LLMs. But there are a few areas recruitment teams can focus on to avoid this fate.

Time to clean house. One way recruitment teams can boost visibility with AI tools is by ensuring their ATS and careers site have clean data and clear information about their employer and its jobs.

“Now, if your jobs don’t come out of your applicant tracking system properly, and if your career site isn’t canonically correct, the algorithm will not find your job and you will end up paying more to get them seen,” said Craig Fisher, founder and lead consultant of employer brand and recruitment tech strategy firm TalentNet Media, during another Talent Acquisition Week panel.

An ATS, like all databases, has different kinds of “schema” that define which data should be inputted and how it should be categorized. This may include information such as pay rate and job location. This data also gets picked up by third-party sites like Google, LinkedIn, or Indeed, and other AI tools scanning the internet for job information. It’s important that the information, right down to the metadata level, is accurate and clean, Fisher said, noting that even doing an existing job posting to create a new one can carry over old metadata that can complicate third-party scanning.

“If you’re not buttoned-down at the ATS level, your job ads aren’t even going to get seen,” Fisher warned.

The same goes for a careers site. Job seekers may ask AI tools to recommend employers or jobs. If recruiters want AI to recommend their company, they’ll have to consistently and repeatedly share information about their company—what it does, where it’s based, the average employee tenure and career background—for LLMs. Displaying that information in easily digestible bullet points can help, he added.

“Think of your jobs as eligible inventory, like on a sales site,” he said.

Focus on reputation. Another critical factor that AI tools assess when recommending an employer is reputation.

“The scariest part for an employer is when you're being compared. You’ve spent all this time and money and effort getting to an offer stage with a candidate, and they go into an LLM and say, ‘Should I take this offer or that offer?’” Katris said. “Your reputation, and what the LLMs think about you, is going to drive that decision.”

Employers don’t have a lot of control over reputation, as it’s primarily informed by LLMs’ analysis of information from sources outside their career site, like Glassdoor and Reddit, Katris said. But employers can still try to influence it.

“The more you’re investing in controlled sources, the more your controlled sources will drive your reputation and ultimately what candidates see and hear about you,” she said.

To start, employers should try to understand how they’re showing up in LLM and search results by asking the tools questions about their work culture, career growth, perks and benefits, and so on. This could help recruiters understand their company’s strengths and weaknesses.

Then, Katris said, they should create LLM-friendly content that addresses candidates’ top goals or concerns, and post it to sites that LLMs scan.

“If you haven’t written a lot of positive, proactive content about your company in a controlled way on a third-party trust and site, what you will see is that everything that shows up here is from reviews that have been posted across the digital footprint,” Katris said. “And so, effectively, what you’re saying is, ‘We’re good with our former ex-employees describing our employer brand.’”

Recruitment teams will have to do this frequently to see results.

“The brands that will be cited and mentioned the most are the ones that are consistently refreshing their content,” Katris said.