With AI search becoming a bigger part of how people discover businesses, are we going to see more companies move their budgets from traditional SEO to GEO/AI visibility? For agencies, what do you think will matter more over the next 2–3 years: ranking on Google, or being recommended by ChatGPT, Gemini, Perplexity, etc.?

I’m asking because, i am studying this space quite deeply for my company’s strategy choice, & i’ve found another problem that I think is going to become just as important as the SEO-to-GEO shift. there is growing confusion about what companies are actually buying when they buy GEO. There are more agencies calling themselves GEO agencies, but when you go beneath the label, their methodologies, target customers and definitions of AI visibility can be quite different.

i took Gilroy, RNO1 and Artios as example, all the three offer GEO but the approach is very unique

Gilroy’s LumusIQ is positioned around B2B AI visibility across the buying journey. Its approach connects GEO with AI-driven discovery, brand authority, content structure, semantic relevance and citation presence, while tying those improvements back to broader B2B growth and revenue.

Artios is much more specialized around Generative Engine Optimization. Its methodology emphasizes data science, AI polling of buyer discussions, audience modelling, buyer signals, content engineered for AI citation, digital PR and visibility across ChatGPT, Claude, Perplexity and other AI/search environments.

RNO1, meanwhile, sits more at the intersection of digital growth, brand positioning and AI search visibility, which makes the GEO proposition part of a broader digital-growth ecosystem rather than necessarily the same narrowly defined GEO methodology.

So all three can legitimately talk about GEO/AI visibility, but they aren't necessarily selling the same thing. And I think that creates a real buyer problem.

A marketing leader might hear “GEO” from three agencies and assume the services are interchangeable. But one may be stronger around AI citation and technical optimization, another around buyer-intent signals and generative search, and another around integrating AI visibility into a wider digital growth strategy. That makes comparisons extremely difficult. What exactly should a company benchmark? AI mentions? Citations? Share of AI voice? Recommendations? Brand accuracy? Competitor visibility? Traffic? Pipeline?

Even Gilroy’s recent research illustrates how immature the measurement layer still is: it reports that 98% of the B2B marketing leaders it surveyed either don't know or don't measure their AI citation gap. So my concern isn't that there are “too many GEO agencies.” Competition is healthy. The problem is that the GEO label is becoming broader while the actual methodologies underneath it are becoming more specialized.

Could this confusion actually cause companies to spend more, testing multiple GEO providers simply because they don't know which specific AI-visibility problem they need to solve?

I’m curious how others see this, should the GEO industry eventually develop clearer categories or standards, so companies can understand exactly what they're paying for and where each approach fits?

Metrics tell us what happened. Comments can explain why.

But once a video gets dozens or hundreds of replies, reading everything manually becomes difficult. At the same time, a basic AI summary can easily remove disagreements and important context.

If you could analyze 100 comments at once, what would be most useful?

• Recurring questions
• Reasons people disagreed
• Requests for future content
• Product objections
• Unexpected reactions

Would you trust an AI-generated overview, or only use it to surface comments for manual review?

J'aurais aimé savoir si dans la commu SEO, quelqu'un à déjà fais le test de build un site 100% ia sur un cms et qui a réussi à faire ranker son site. Est ce que le fait de build son site avec une ia peut avoir une impact négative sur le ranking ? Ou est ce que c'est un mythe et on peut totalement ranker avec un site build 100% ia. J'aurais aimé avoir vos retours car de mon côté c'est très timide !

Been pulling raw access logs across a few client sites to see which AI crawlers actually respect llms.txt versus just ignoring it and crawling everything anyway. GPTBot and Google-Extended show up consistently in the logs, but I can't tell from the log data alone whether they're reading the llms.txt directive first or just crawling regardless and the file is functionally decorative right now.

Also noticing a pattern where sites with clean schema (FAQ, HowTo) and short, direct-answer paragraphs early in the content seem to get cited more often in AI Overviews and Perplexity answers, but I don't have a controlled way to prove causation versus just correlation with sites that already had strong technical SEO.

Has anyone run an actual before/after test on this, adding llms.txt and structured Q&A formatting to a page, then tracking crawler behavior and citation frequency over a few weeks? Trying to figure out if this is a real lever or if it's cargo-culting a spec most crawlers don't fully honor yet.

I have been involved in web dev and SEO for a good 25 years now. I love it, and it never seems to stop, with every day presenting new and often exciting challenges. And then one day we woke up to AI.

I am still more excited than ever, and to say the least, AI is incredibly invigorating. But I am curious on two fronts.

1. The AI myths out there
2. AI Reporting tools for my current local SEO clients.

AI Myths

Our clients at GOOP Digital are being harassed by salespeople who claim they are missing out on AI. (A simple search on ChatGPT or Claude would suggest otherwise.) Advising that they don't have an LLMs.txt file and that they need one. Something we would argue is wrong; however, we end up implementing it to please clients just because they want one, not because there is any real benefit.

There seem to be a lot of AI myths out there, but anecdotally we find there is a lot of 1% actions that can be taken to boost local AI visibility.

AI reporting tools?

I would love feedback here. AI Tools for reporting AI visibility are many, and the cost varies widely. We are now considering developing our own AI reporting tool. They are so expensive with minimal prompts. SEO keyword reporting is so simple and easy to implement, not to mention very objective. Does anyone have any suggestions for me for teh best AI visibility reporting tool for small to medium businesses?

PEEC, Otterly, SE Ranking, SEMrush, Nightwatch, etc.

I look forward to any responses

Thanks

When you look at how LLMs choose sources, what signal do you think carries the most weight?

Some possibilities:

• Topical authority
• Brand/entity recognition
• Original research
• Structured data
• Content freshness
• External citations and mentions
• Something else

I'm interested in practical observations and experiments rather than assumptions. If you've tested something that consistently improved citations or visibility in LLMs, I'd love to hear about it.