Is GEO a Fad? An Honest Look at What's Hype and What's Real in 2026

GEO is not a fad, but a significant portion of what's being sold under that name is. The underlying behaviour is real: people are asking AI engines questions and acting on the answers. ChatGPT alone has surpassed 800 million weekly active users by late 2025. If your brand isn't appearing in those answers, that's a real business problem. What's hype is the confidence of the playbooks claiming to solve it.

How Old Is GEO, Really?

The term "Generative Engine Optimisation" traces to a research paper submitted to arXiv on November 16, 2023, by a Princeton-led team. That makes the formal concept about 2.5 years old. The actual practice of optimising for live ChatGPT or Perplexity answers is younger than that, because the surfaces themselves are younger.

This matters more than most GEO vendors want to acknowledge. When someone sells you a "proven, multi-year system," do the arithmetic. Google AI Overviews only reached full US rollout in June 2026. Perplexity only hit 10 million monthly active users as of May 2026. These are adolescent platforms. Nobody has a multi-year track record of optimising for surfaces that didn't exist multi-years ago.

That's not a reason to ignore GEO. It's a reason to treat every "guaranteed" playbook with scepticism, including the ones that sound rigorous.

What Is Actually Real About GEO?

The behaviours that GEO tries to influence are real and growing fast. AI-generated answers are becoming the first touchpoint between users and brands across a widening range of queries. According to Searchable's 2026 survey, 84% of marketers recognise GEO as a concept, even if only 42% actually use the term in practice. That gap between awareness and adoption is typical of any emerging discipline, but it also tells you that the underlying reality is outpacing the vocabulary.

What specifically holds up, based on how these engines actually behave:

• AI engines systematically favour third-party earned coverage over brand-owned pages. If you only publish on your own site, you're largely invisible to these systems.
• Structured content, specifically clear heading hierarchies, FAQ blocks, and answer-first paragraphs, gets extracted and cited at higher rates than unstructured prose.
• Recency matters. Engines like Claude (which uses the Brave Search index) and ChatGPT (which pulls live web content via Bing) weight fresh content when queries require current information.
• Different AI engines pull from different sources. ChatGPT leans heavily on Bing-indexed content. Claude relies on Brave Search. Gemini draws from Google's index and its own ecosystem. Optimising for one doesn't guarantee visibility on the others.
• Community platforms, Reddit especially, appear in AI citations at a rate disproportionate to their traditional SEO authority. Ignoring them in a GEO strategy is a real gap.

These aren't theories. They're observable by anyone who runs systematic tests across the major platforms. We test them regularly at BrandPrompts, and the patterns are consistent enough to build strategy around, even if the exact mechanics shift.

What Is Overstated or Outright False?

Three things signal hype immediately. "Guaranteed AI rankings" is the clearest red flag: no one controls how these engines pick sources, and the selection criteria change as models are retrained. "Our proven system" deserves scrutiny given that the oldest meaningful track record in this field is about 18 months. And large confident case-study numbers presented as repeatable outcomes, rather than one-off experiments on a specific brand in a specific category, are almost always cherry-picked.

There's also a murkier category of hype: tactics that sound technical but have no verified effect. The llms.txt file is a good example. Google has confirmed its crawlers don't follow these files. Creating one takes an hour and signals nothing to the engines that matter most. It's the equivalent of writing "please cite me" in invisible ink.

Schema markup is more defensible, but even there, Google has stated explicitly that schema is not required for AI Overview inclusion. It helps with rich results eligibility, which is worth having, but it's not a GEO silver bullet.

And keyword stuffing, the old SEO reflex, actively hurts visibility in AI systems. These models aren't keyword-matching; they're evaluating whether your content actually answers a question with authority.

Is GEO Better Than SEO?

GEO and SEO are not competing strategies, and treating them as alternatives is a false choice that will hurt you on both channels. Strong GEO depends on strong SEO foundations: indexed pages, crawlable structure, authority signals, quality content. The difference is in what each discipline optimises for.

SEO targets a ranking algorithm that returns a list of links. GEO targets a language model that synthesises an answer and either names your brand or doesn't. Both matter, and the good news is they share roughly 80% of the same underlying work. The genuinely new work in GEO, earning third-party citations, building community presence, structuring content for extraction rather than just for ranking, sits on top of a solid SEO foundation.

The worst outcome is abandoning proven SEO investment for untested GEO tactics. The practical approach is to treat GEO as an extension of content and authority strategy, not a replacement for it.

How Do GEO, SEO, and AEO Actually Differ?

AEO is worth investing in. Google AI Overviews now appear across a meaningful percentage of search queries, and the optimisation tactics, answer-first content, FAQ schema, clear heading hierarchies, are the same tactics that improve GEO performance. You're not running separate programs. You're running one content quality program that benefits all three disciplines.

What Does GEO Actually Cost?

The cost question is genuinely complicated because GEO doesn't have a standardised market rate yet. That's partly because the discipline is new, and partly because so much of what gets sold as "GEO services" is traditional content or PR work with different labelling.

On the tooling side, GEO monitoring platforms vary widely. Some run on monthly subscriptions in the hundreds of dollars; enterprise-grade platforms go greatly higher. The upstream problem, figuring out which prompts to track in the first place, is where teams routinely waste 40 or more hours on manual research before a single tracking run begins. That's avoidable with the right approach to prompt research. BrandPrompts exists specifically to solve that problem: generating research-backed prompt sets from real search data rather than educated guesswork, starting at $29 for a one-off purchase.

On the strategy side, the most expensive GEO investment is usually content and digital PR, earning the third-party mentions that AI engines actually cite. That's not new budget; it's existing content and PR budget redirected toward placements and formats that AI engines can extract from.

Be cautious of any vendor quoting large monthly retainers for "AI ranking guarantees." Given the age of this field, what they're really selling you is activity, not proven outcomes.

How to Tell Good GEO Advice From Bad

This is the practical filter that the maturity question leads you to. Good GEO advice looks like this: it cites specific platform behaviours with dates, it acknowledges what isn't known yet, it encourages measurement and iteration rather than prescription, and it builds on existing SEO and content fundamentals rather than dismissing them.

Bad GEO advice looks like this: it promises rankings on platforms where rankings don't exist in any traditional sense, it presents single case studies as universally applicable, it uses urgency ("if you don't act now") as a substitute for evidence, and it sells proprietary frameworks as if two years of data supports them the way twenty years of SEO data supports core search principles.

Treat your own brand as the experiment. Run a set of test prompts across ChatGPT, Perplexity, Claude, and Gemini. Note where you appear and where you don't. Make one change at a time and measure whether it shifts your visibility over 30 to 60 days. That's slower than a vendor's pitch deck, but it produces information you can actually act on. Tracking the right prompts matters here: a prompt set that's too narrow or too brand-focused won't show you where the real discovery gaps are. See our guide to building a prompt strategy that reflects how users actually search.

Frequently Asked Questions

Is GEO a legitimate marketing discipline or just rebranded SEO?

GEO is a legitimate discipline with genuinely new elements, but it shares roughly 80% of its foundations with good SEO and content strategy. The new 20%, earning citations on third-party platforms, building community presence, and structuring content for AI extraction, is real and worth investing in. The risk is paying a premium for the remaining 80% that's just SEO with different terminology.

How important is GEO right now?

It depends on your category and audience. For brands whose buyers are actively using AI search tools as a research step, GEO visibility is already a real gap. For categories where traditional search dominates the research process, GEO is worth monitoring but probably doesn't need dedicated budget yet. The honest answer: start measuring before you start spending.

Is AEO worth it?

Yes, because it's largely the same work as strong content strategy. Optimising for Google AI Overviews and featured snippets means writing clear, structured, answer-first content, and that content also performs better in GEO contexts. There's very little investment here that doesn't pay off across multiple channels.

Can I guarantee my brand appears in AI answers?

No. Nobody can. The selection criteria these engines use are not fully public, change as models are retrained, and vary across platforms. What you can do is make your brand a more credible, more extractable, more widely cited option, which increases the probability of appearing without guaranteeing it.

What's the minimum viable GEO investment?

Start with measurement. Set up a structured prompt set across your key topic areas and run it across two or three platforms monthly. From there, prioritise earning third-party coverage in publications and communities that AI engines actually cite in your category. That's a lower cost starting point than most vendors suggest, and it gives you actual data to justify further investment.