AI search is changing how marketers plan and spend, but most of them are still calling it SEO. A new survey of 343 U.S. marketing decision-makers found that 81% describe their internal AI search visibility strategy as SEO, and 24% of the average search or content budget is now allocated to AI search work. Marketers reward case studies, clear methods, and visible proof, not new acronyms.
What the survey covered
The study surveyed 343 U.S. marketing decision-makers about how they describe, fund, and evaluate AI search optimization. The findings show a gap between the language used inside industry circles, where terms like GEO, AEO, and LLM optimization compete for attention, and the language buyers actually use to describe the work and search for help.
Half of marketers are still learning the vocabulary
Only 27% of marketing teams have formally adopted a term beyond SEO to describe their AI search activities, while 42% have decided against it and 31% are still undecided. Half of the marketers surveyed said they have researched a term they did not recognize after seeing a peer or competitor use it.
Senior leaders are more likely to use the new labels. Among C-suite executives, 36% say their teams have moved past SEO, and 28% use the term GEO, with 17% using AEO. Individual contributors use these terms at far lower rates, 9% for GEO and 3% for AEO. The pattern extends to learning. C-suite leaders were the most likely to report looking up unfamiliar terms, at 56%, which suggests executives are adopting the category before their organizations have built a shared operating model for it.
When asked how they respond to terms like GEO or AEO in a pitch, 42% said it depends on the context, 30% saw the language as innovative, 22% said it had no impact, and 7% said it made the vendor seem less trustworthy.
AI search budgets are real, even if strategy is still taking shape
On average, marketers are now putting 24% of their total search or content budget toward AI search visibility. Up to 82% have committed at least some of their budget, and 43% are allocating more than 20%.
SEO and performance marketing teams direct a higher share of their budgets to AI search visibility than content and brand teams, which lines up with their day-to-day exposure to changes in impressions, rankings, traffic quality, attribution paths, and assisted conversions.
The biggest challenge cited was keeping pace with the speed of change, at 28%, ahead of measuring performance or visibility in AI-generated results (17%), choosing which AI search platforms to prioritize (15%), and the absence of industry standards or best practices (13%).
Which AI platforms marketers are prioritizing
Platform focus remains fragmented. ChatGPT leads, named by 34% of marketers, followed by Gemini at 16%, Claude at 6%, and Copilot or Bing AI at 5%. Perplexity was named by 1%, despite heavy attention in SEO and AI circles, and 14% said their team had not picked a target platform yet.
For teams still building a strategy, the first step is identifying which sources the answer engines in your category pull from: listicles, Reddit threads, analyst pages, trade media, YouTube transcripts, your own site, or competitor-owned content, and which of those sources can realistically be influenced.
Case studies beat acronym fluency by 4 to 1
When marketers evaluate vendors, the signals they trust are familiar. Case studies with measurable, verifiable results were the top credibility signal at 34%. Clear methodology followed at 22%, and team expertise or a demonstrated track record came in at 15%. Combined, 71% ranked case studies, methodology, or team track record as their top signal. Terminology fluency ranked at 9%.
On the red-flag side, 36% of marketers said excessive buzzword use without clear explanations was their top vendor concern. Another 21% pointed to a lack of case studies or trackable results, 20% flagged vague or unsubstantiated performance claims, and 16% were wary of repackaged SEO services with new AI branding.
The strongest pitch, the data suggests, is a clear proof chain: how AI search represents the category, where the brand is missing or misrepresented, what influences those answers, and what changed after the work was done. The terminology used to label the work matters far less than the ability to show it.
AI search is now part of the vendor discovery loop
Two-thirds of marketers have used an AI search tool, including 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 at 89%, performance marketers at 84%, and C-suite leaders at 81%.
Vendor discovery no longer starts and ends with Google, LinkedIn, trade media, review platforms, or referrals. AI search tools and peer recommendations are now tied as the first stop when researching AI search solutions or partners, each selected by 34% of respondents. Traditional discovery channels, including Google Search, LinkedIn, industry publications, and trade media, followed at 22%, while agency review platforms such as G2 and Clutch came in at 8%.
For agencies and platforms, the practical implication is that a prospect may search Google, ask peers in a Slack community, and prompt an AI tool before ever filling out a form. Auditing that full path, from AI answers to peer chatter to the case studies that back up the claims, is now part of how visibility is built and evaluated.
How marketers search for help with AI search
When marketers look for help with AI search visibility online, 46% would search for “AI search optimization” and 24% would search for “SEO.” Together, the two familiar terms account for 70% of the language buyers use to find help. The newer acronyms are not driving discovery at the same volume.
What this means in practice
Vocabulary is not strategy. Marketers are still using familiar terms, evaluating familiar proof points, and rewarding vendors that can explain the work clearly. What is changing is where they discover and validate those vendors and how the budget is allocated. Teams investing in this work should match the budget reality, 24% of search or content spend on average, with a strategy that can evolve as answer engines and AI Overviews continue to change.
One practical way to start is to track which prompts buyers in your category are likely to run, then see how your brand, your competitors, and the publishers in your space are represented across ChatGPT, Gemini, Google AI Overviews, Claude, and Perplexity. Visibility in AI search is now part of the same discovery loop as search results, peer recommendations, and review sites, and it benefits from being measured the same way.
FAQ
What do marketers call AI search optimization?
81% of the 343 U.S. marketing decision-makers surveyed still describe their internal AI search visibility strategy as SEO. Only 27% of teams have formally adopted a term beyond SEO for this work, while 42% have decided against it and 31% are still undecided.
How much of the marketing budget is going to AI search?
Marketers allocate 24% of their total search or content budget to AI search visibility on average. Up to 82% have committed at least some of their budget, and 43% are allocating more than 20%.
What do marketers look for in an AI search vendor?
Case studies with measurable, verifiable results were the top credibility signal at 34%, followed by clear methodology at 22% and team expertise or track record at 15%. Terminology fluency ranked at 9%. The top vendor red flag, cited by 36%, was excessive buzzword use without clear explanations.
Related coverage
- Google’s AI Search Guide Isn’t Reassuring. It’s a Warning About Generic Content – BizScoreAI
- Google’s AI Search Guide Isn’t Reassuring. It’s a Warning About Generic Content – BizScoreAI
- DuckDuckGo’s Traffic Surge Proves Users Want Control Over AI in Search, What This Means for AEO – BizScoreAI
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