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<\/a><\/p>\nThe AI visibility report runs a full technical audit of a site and shows the measured result behind every check. Open the AI visibility report<\/a>.<\/p>\n
Marketers are funding AI search visibility at a level that signals real commitment, with 24% of total search or content budgets now going to the category on average, even though most of them still describe the work as plain SEO. A new survey of 343 U.S. marketing decision-makers also found that two-thirds have already used AI tools such as ChatGPT, Perplexity, and Gemini to research marketing vendors, which is reshaping how buyers discover and evaluate the agencies pitching them.<\/p>\n
The research was designed to separate the vocabulary circulating inside the SEO industry from the vocabulary buyers actually use to solve a problem. Earlier work tracked how new terms were being adopted on social platforms and among influencers. This round surveyed U.S. marketing decision-makers to learn how they describe, fund, and evaluate AI search optimization.<\/p>\n
Only 27% of marketing teams have formally adopted a term beyond SEO to describe their AI search activities. Another 42% have decided against it, and 31% are still undecided. Half of marketers said they have researched a term they did not know after seeing it used by a peer or competitor. Senior leaders are more likely to adopt new terminology, with 36% of directors and C-suite executives saying their teams have moved past SEO, yet C-suite leaders were also the most likely to report looking up unfamiliar terms, at 56%.<\/p>\n
When asked how they react to terms like GEO or AEO in a vendor pitch, 42% said it depends on how much context is provided, 30% saw the language as innovative, 22% said it had no impact, and 7% said it made the vendor seem less trustworthy. The opportunity for agencies and platforms is to make AI search easier to understand, budget for, and act on, rather than to win the naming debate.<\/p>\n
Up to 82% of marketing teams have committed at least some of their budget to AI search visibility, and 43% are allocating more than 20% of their search or content budgets to it. SEO and performance marketing teams allocate a higher share than content and brand teams, which fits their position closest to impressions, rankings, traffic quality, attribution, and assisted conversions.<\/p>\n
The biggest challenge cited was the speed of change, at 28%, ahead of measuring performance in AI-generated results at 17%, identifying which AI platforms to prioritize at 15%, and the absence of industry standards or best practices at 13%. Platform focus is fragmented: ChatGPT leads with 34% of marketers prioritizing it, followed by Gemini at 16%, Claude at 6%, and Copilot or Bing AI at 5%, with Perplexity at 1% and 14% saying no target platform has been picked.<\/p>\n
Start by identifying where AI search is already influencing the category. Audit the prompts buyers are likely to use. Track how the brand, competitors, and publishers are represented across ChatGPT, Gemini, Google AI Overviews, Claude, and Perplexity. Then look for the recurring sources, citations, comparisons, and entity signals shaping those answers.<\/p>\n
Case studies with measurable, verifiable results were the top credibility signal, selected by 34% of marketers. Clear methodology followed at 22%, and team expertise or a demonstrated track record came in at 15%. Combined, 71% of decision-makers ranked case studies, methodology, or team track record as their top credibility signal. Terminology fluency ranked at just 9%, about a quarter of the weight given to case studies.<\/p>\n
The red-flag data reinforces the same point. The biggest turnoff was heavy use of buzzwords without a clear explanation, cited by 36% of marketers. Another 21% pointed to a lack of case studies or trackable results, 20% flagged vague or unsubstantiated performance claims, and 16% flagged repackaged SEO services with new AI branding.<\/p>\n
The strongest pitch is not a vocabulary play. It is a clear proof chain: here is how AI search represents the category, here is where the brand is missing or misrepresented, here is what influences those answers, and here is the work required to improve visibility, along with what changed after the work was done.<\/p>\n
Two-thirds of marketers said they have personally used an AI search tool to research 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%. AI search tools and peer recommendations are now tied as marketers’ first stop when researching AI search solutions or partners, with each selected by 34% of respondents. Traditional discovery channels such as Google Search, LinkedIn, industry publications, and trade media followed at 22%, and agency review platforms like G2 and Clutch came in at 8%.<\/p>\n
A prospect may search Google, ask peers in a Slack community, and prompt ChatGPT before ever filling out a form. Those surfaces are no longer separate; they reinforce each other. Auditing the full discovery path, including what AI tools say, which third-party sources those answers rely on, how peers describe the agency, and whether case studies are visible enough to support the claims being made, is now part of the work.<\/p>\n
The data points to a clear gap between the language circulating inside SEO circles and the language buyers use to fund and evaluate work. Eighty-one percent of marketers still refer to their internal AI search visibility strategy as SEO, and 70% would search for either AI search optimization (46%) or SEO (24%) when looking for help with AI search visibility online. C-suite marketers use GEO (28%) and AEO (17%) at roughly three times the rate of individual contributors (9% and 3%).<\/p>\n
The practical takeaway is straightforward. Define the term if it helps, but anchor the pitch in measurable proof: which prompts were tested, where the brand and competitors appeared, which sources influenced the answer, and what changed after the work was done. The agencies that win the next phase will be the ones that make themselves easy to find, easy to understand, and easy to evaluate across Google, AI search tools, and the peer networks marketers already rely on.<\/p>\n
According to the survey, 81% of marketers still refer to their internal AI search visibility strategy as SEO, and only 27% of marketing teams have formally adopted a term beyond SEO. C-suite marketers adopt the newer acronyms at roughly three times the rate of individual contributors.<\/p>\n
Marketers allocate an average of 24% of their total search or content budget to AI search visibility. Up to 82% of marketing teams have committed at least some of their budget to it, and 43% are allocating more than 20%.<\/p>\n
Case studies with measurable, verifiable results were the top credibility signal, selected by 34% of marketers, followed by clear methodology at 22% and team expertise or track record at 15%. Terminology fluency ranked at just 9%, while heavy use of buzzwords without explanation was the top red flag, cited by 36%.<\/p>\n
The AI visibility report runs a full technical audit of a site and shows the measured result behind every check. Open the AI visibility report<\/a>.<\/p>\n<\/a><\/p>\n