SEO vs GEO: A Misframed Debate and the Real Answer

For Google, the debate has an official answer. Google’s guide to optimizing for generative AI search says that from Google Search’s perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO. Its generative AI features are rooted in its core Search ranking and quality systems. Where the question is real is outside Google: other AI assistants retrieve and cite sources their own way, and Google’s guidance doesn’t speak for them. So a more useful answer than picking a side is to start from one set of fundamentals and measure each surface you care about separately.

What Google says changes, and what doesn’t

The same guide includes a list of things you can ignore for Google Search:

• llms.txt and other “special” markup. You don’t need new machine-readable files, AI text files, markup or Markdown to appear in Google Search, including its generative AI features, because Google Search itself doesn’t use them.
• Rewriting content just for AI. Google says its AI systems understand synonyms and general meaning, so you don’t need to chase every long-tail variation or write in a special way.
• Inauthentic mentions. Seeking fake mentions across the web isn’t as helpful as it might seem; Google’s core ranking systems focus on high-quality content and other systems block spam.
• Special structured data. Structured data isn’t required for generative AI search, though Google recommends continuing to use it for rich results.

What the guide does ask for is content that people find unique and useful. It contrasts commodity content, based on common knowledge, with non-commodity content that offers a first-hand or expert view, and says a first-hand review provides a unique perspective where a summary restates what’s already available.

Where “good SEO is good GEO” stops

Google’s answer covers Google. Other AI assistants choose and cite sources with their own systems, and Google’s documentation doesn’t cover how they work. Pages that appear for a question in one assistant may not appear in another, and a page cited in Google’s AI Mode isn’t guaranteed a citation elsewhere. Even within Google, its AI features documentation says AI Mode and AI Overviews may use different models and techniques, so the responses and links they show will vary.

That’s the grain of truth in “GEO”: visibility is now spread across several surfaces, and each one has to be checked on its own. It argues for measuring each one; it isn’t evidence that each needs different writing.

Question every statistic

Precise figures circulate in AI-search discussion: overlap percentages between engines, citations per answer, conversion multipliers. Before planning around one, ask four questions:

1. Which queries? Informational, local and commercial queries behave differently. A study built on one says little about another.
2. Which platform? Results measured in one assistant are not evidence for another.
3. What sample and method? Small or selected query sets, and undisclosed measurement windows, can produce very different numbers that sound equally authoritative.
4. When? AI systems change their models and retrieval, so a rate measured this quarter may not hold next quarter.

Plan against what the documentation says and what you measure yourself, not against a quoted percentage.

Measure each surface separately

For Google, Search Console’s Generative AI performance report shows your impressions in AI Overviews and AI Mode, rolled out to all sites as of August 31, 2026. Google’s guide also warns to be wary of third-party tools that claim to use internal Google metrics, since no third-party tool has access to Google’s internal ranking or AI systems.

For other assistants there is no equivalent report from Google. Track referral traffic your analytics can attribute to them, knowing it may undercount, and run a fixed set of prompts on a regular schedule, recording whether and how your pages are cited.

How to split the effort

Because Google says generative AI search on Google is still SEO, the core work serves both: useful, original, well-structured content on a site Google can crawl and index. The separate slice is measurement and testing on the other assistants your audience uses. Size that slice by how much of your audience uses them, and resize it as your own data comes in, rather than borrowing a percentage from someone else’s study.

Frequently asked questions

Should I implement llms.txt?

Not for Google. Its generative AI guide lists llms.txt among the things you can ignore, because Google Search doesn’t use such files. Other AI systems have their own policies, which Google’s guide doesn’t cover.

Is GEO a separate discipline from SEO?

For Google Search, no: Google says optimizing for generative AI search is still SEO. For other AI assistants, the fundamentals are a reasonable starting point, but Google’s guidance doesn’t cover them, so you measure each one separately.

Does optimizing for one AI engine optimize for all of them?

Partly. Results vary even between Google’s own AI Mode and AI Overviews, and more so across different companies’ assistants. Check each surface you care about.