The search marketing industry has spent the past two years debating what to call the next era of discoverability: GEO, AEO, LLM optimization, or AI search optimization. Every few weeks, a new acronym gains traction on LinkedIn, appears in an agency sales deck, or gets debated at conferences.
While language certainly shapes how teams hire and budget, there is a massive divide between the jargon agencies use to signal expertise and the language buyers use to solve problems.
A recent research survey conducted by Fractl evaluated 343 U.S. marketing decision-makers to understand how they actually describe, fund, and vet AI search optimization initiatives. The results reveal that artificial intelligence is changing the mechanics of visibility far faster than the vocabulary of the executives paying for it.
Here are five shocking truths about how brands are approaching AI search optimization today.
1. 81% of Marketers Still Call It “SEO”
Despite relentless industry hype around new terminology, the vast majority of marketing decision-makers have not abandoned traditional naming conventions:
- 81% of marketers still describe their internal visibility strategy as “SEO.”
- 70% of marketers state they search for either “AI search optimization” (46%) or simply “SEO” (24%) when looking for external agency support.
- Only 27% of teams have formally adopted a newer term (like GEO or AEO) to define their AI search activities.
Interestingly, C-suite executives use terms like GEO (28%) and AEO (17%) at roughly three times the rate of individual contributors. However, 56% of C-suite leaders admit to looking up unfamiliar acronyms after seeing them in board decks. The takeaway for agencies is clear: don’t let buzzwords carry the pitch—ground the work in clear visibility and measurable revenue impact.
2. Real Budgets Are Already Flowing to AI Search Optimization
While operational frameworks remain unsettled, financial commitments are already established. Marketers now allocate an average of 24% of their search or content budgets directly to AI search optimization and brand visibility.
Up to 82% of surveyed marketing teams have committed at least some portion of their annual budget to generative visibility, with 43% allocating more than a fifth of their spend. Performance and technical SEO teams lead this investment because they are the first to notice algorithmic shifts in impressions, attribution paths, and organic referrals.
As digital marketing budgets shift toward automation—such as adopting ChatGPT Ads automated bidding to capture intent—organic and paid teams are heavily aligning their strategies around these conversational interfaces.
3. Platform Priorities: ChatGPT Leads, But Landscape Is Fragmented
When asked which platform matters most for AI search optimization, marketer focus is heavily distributed:
- ChatGPT: 34%
- Google Gemini: 16%
- Claude: 6%
- Microsoft Copilot / Bing AI: 5%
- Perplexity: 1%
- Undecided / No Target Yet: 14%
Rather than chasing every emerging engine with isolated tactics, marketing teams should analyze which third-party websites, Reddit discussions, review directories, and authoritative publications feed the answers across these major models.
4. Case Studies Beat Acronym Fluency 4 to 1
Agencies that rely on heavy jargon are alienating potential clients. According to the research, 36% of marketers cited excessive buzzwords without clear explanations as their primary vendor red flag.
When evaluating an agency for AI search optimization, decision-makers prioritize proven credibility:
- Measurable Case Studies: 34%
- Clear, Transparent Methodology: 22%
- Demonstrated Team Track Record: 15%
- Terminology Fluency: Only 9%
Clients want to see a verifiable proof chain: which prompts were audited, where the brand was missing or cited incorrectly, and what concrete technical or content optimizations produced ranking improvements. For broader industry insights on digital marketing trends, you can review analysis reports on Search Engine Land.
5. AI Search Has Become the New Vendor Discovery Loop
The marketers being pitched generative visibility services are already using AI tools to vet the agencies pitching them.
Two-thirds (66%) of marketing decision-makers report using tools like ChatGPT, Gemini, or Perplexity to research and evaluate potential marketing vendors. In fact, AI search tools and peer recommendations are now tied as the number-one first stop for enterprise partner discovery (34% each), outpacing traditional Google searches and review directories.
If an agency fails to optimize its own digital footprint for AI-driven discovery, prospective clients will quickly notice the absence.
Conclusion
Success in AI search optimization depends on genuine visibility, structural authority, and clear proof chains—not trendy vocabulary. The winners of the next search era will not be the practitioners who invent new acronyms, but those who build trusted, authoritative brands that AI models and human buyers can easily recommend.
Frequently Asked Questions
What is AI search optimization?
AI search optimization refers to the practice of optimizing digital content, brand citations, and technical architecture so that generative search engines (like ChatGPT, Perplexity, and Google AI Overviews) cite and recommend your brand in user queries.
How does AI search optimization differ from traditional SEO?
While traditional SEO focuses primarily on ranking blue links within standard search engine results pages (SERPs), AI search optimization focuses on entity authority, contextual citations, and structured data to ensure language models reference your business during conversational syntheses.
Why do most marketers still refer to AI search optimization as SEO?
Because the underlying objective remains identical: driving qualified traffic, establishing brand authority, and earning customer trust through digital discoverability. Most enterprise buyers view AI engines as an evolution of search rather than an entirely separate discipline.
