Sean Walsh
Sean is a Director at Intelligency heading up our digital marketing and client services operations. Sean has 15+ years experiencing working both in-house and agency with brands including Lloyds, Alstom, Hitachi, Lufthansa, Viaplay, DFDS Seaways and Mercedes-Benz.
A survey of 343 marketing decision-makers published this month by Fractl contains one finding that cuts through all the noise about what to call AI search optimisation: 81% of marketers still describe their AI search visibility strategy as SEO. Not GEO. Not AEO. Not LLM optimisation. Just SEO.
This matters, but probably not in the way the commentary usually suggests. The reaction from most of the industry has been to frame this as a problem – a gap between where search is heading and where practitioner vocabulary has got to. But the data tells a more nuanced story, and the practical implications for anyone managing digital marketing in 2026 are worth reading carefully.
What the data actually says
The headline number – 81% still calling it SEO – sits alongside several others that are worth considering together. Marketers are allocating an average of 24% of their total search or content budget to AI search visibility. Up to 82% have committed at least some budget to it. 43% are allocating more than 20%. This is not a situation where the vocabulary gap reflects an investment gap. The money is moving. The terminology hasn’t caught up.
The terminology gap is also unevenly distributed. Senior leaders use newer terms like GEO and AEO at roughly three times the rate of individual contributors. C-suite marketers are more likely to have encountered these acronyms in board decks or conference presentations and to have adopted them into their own language. The people actually doing the work – the SEO specialists, the content managers, the performance marketers – are largely still working within the SEO frame. That’s a meaningful distinction for anyone trying to have a coherent conversation about strategy across a mixed team.
Half of marketers surveyed said they had researched a term they didn’t know after seeing it used by a peer or competitor. Only 27% of marketing teams have formally adopted a term beyond SEO. 42% have actively decided against it. 31% haven’t decided. This is not the profile of an industry that has broadly accepted a new vocabulary. It’s the profile of an industry where the vocabulary is being imposed top-down and hasn’t bedded in.
What this means for how clients and internal teams behave
The most commercially useful finding in the research is about vendor credibility. When decision-makers evaluate a supplier or agency for AI search work, the credibility signals they trust are strikingly familiar. Case studies with measurable, verifiable results were the top signal, selected by 34% of respondents. Clear methodology came second at 22%. Team expertise and track record came third at 15%. Terminology fluency ranked at just 9%.
The red flag data is equally direct. The biggest single turnoff when evaluating a vendor was heavy use of buzzwords without a clear explanation of what each term means – cited by 36% of respondents. Another 21% pointed to a lack of case studies or trackable results. 20% flagged vague or unsubstantiated performance claims. And 16% specifically raised concerns about repackaged SEO services with new AI branding.
The practical implication is clear. Clients and internal decision-makers want to understand what has changed, what you are doing about it, and what happened as a result. The shift from rankings to recognition in how AI systems surface brands is a real and significant change. But calling it GEO in a pitch deck and not explaining what that means in practice is actively counterproductive. The acronym doesn’t do the work. The explanation does.
The platform prioritisation problem
Platform focus among marketing teams is currently fragmented in a way that reflects the broader unsettled state of the category. ChatGPT leads, with 34% of marketers naming it as their primary AI search visibility priority. Gemini is second at 16%. Claude is at 6%, Copilot and Bing AI at 5%. Only 1% named Perplexity, despite the significant attention it receives within SEO and AI professional circles. 14% of teams haven’t picked a target platform at all.
This matters in context of something we looked at earlier in the year: 91% of AI citations appear in only one engine. If you’re cited on ChatGPT, the odds are you’re not being cited on Perplexity or in AI Overviews. A single-platform AI visibility strategy is almost certainly leaving material gaps. But the research suggests most teams haven’t yet developed a multi-platform approach, and a significant minority haven’t even committed to a primary platform to focus on first.
The research authors’ advice is sensible here: avoid both extremes. Don’t dismiss AI search because your traffic hasn’t collapsed. But don’t overcorrect by chasing every new answer engine separately. Start by identifying where AI search is already influencing discovery in your category, then build outward from there.
The feedback loop that changes what visibility means for agencies
The most practically significant finding for agencies is buried toward the end of the research. Two thirds of marketing decision-makers said they had personally used an AI tool – ChatGPT, Perplexity, or Gemini – to research or evaluate a marketing vendor or agency. Adoption is highest among the groups most likely to influence search investment: SEO specialists (89%), performance marketers (84%) and C-suite leaders (81%).
This creates a feedback loop that redefines what agency visibility means. A prospective client may search Google, ask peers in a Slack community, and then prompt ChatGPT before they ever fill out a contact form. Those surfaces are not separate. They reinforce each other. If an agency is recommending AI search visibility to clients but is not itself visible in AI search answers about marketing agencies, that is a credibility problem that will compound over time.
The practical audit for any agency is to run the prompts your prospective clients are likely to run. Ask which agencies specialise in AI search visibility, which SEO firms have credible case studies, how a specific agency compares with competitors, and which vendors are trusted for this kind of work. Then look at the sources shaping those answers, and identify where you are and aren’t present.
The useful takeaway from the naming debate
The argument about what to call AI search optimisation has consumed a remarkable amount of industry energy for something the data suggests buyers largely don’t care about. The research is direct on this: vocabulary fluency ranked at 9% as a credibility signal, while case studies, clear methodology, and track record together accounted for 71%.
What the naming debate does reveal, though, is something more useful. The fact that 81% of practitioners still default to SEO is not just a vocabulary lag. It reflects a genuine continuity in what the underlying work involves. The content has to be specific and authoritative. The technical accessibility has to be right for crawlers and AI systems alike. Third-party credibility signals still matter. The entities – brand, people, place – need to be correctly understood and associated. These are things SEO has always been about. What has changed is where the work surfaces and how it gets measured.
The teams that are doing well in AI search are not necessarily the ones that adopted GEO terminology earliest. They are the ones that understood what changed in how AI systems decide what to cite, built their content and credibility accordingly, and can demonstrate the results. That is a methodology problem, not a naming problem. And it is the one worth spending time on.
