Case study: Gumlet turned ChatGPT mentions into 20% of inbound revenue. Read it →
TL;DR
Google just said the quiet part out loud: for AI Overviews and AI Mode, the hacks are mostly theater, and the foundation is still Search quality.
That is good news for serious SEO teams. It is bad news for anyone who sold “GEO packages” that were mostly llms.txt files and synonym spam.
It is also incomplete if you sell B2B SaaS. Buyers do not only decide inside Google’s generative UI. They ask ChatGPT who to shortlist. They ask Perplexity for alternatives. Google’s guide does not cover that surface, and pretending it does is how CMOs under-invest in the channels that actually steal demos.
This is DerivateX’s operator read of Google’s generative AI SEO guide: what to keep, what to kill, and what still sits outside Google’s definition of SEO.
In Optimizing your website for generative AI features on Google Search, Google answers “Is SEO still relevant for generative AI search?” with a blunt line: “In short, yes!”
Why, in Google’s words:
Two mechanisms Google calls out:
| Mechanism | What Google says it does |
|---|---|
| Retrieval-augmented generation (RAG / grounding) | Uses core ranking to retrieve relevant, current indexed pages, then reviews those pages to generate a response and shows clickable supporting links |
| Query fan-out | Generates concurrent related queries to fetch additional relevant results for the original ask |
On naming, Google is explicit. “AEO” and “GEO” are terms people use for AI-search visibility work. From Google Search’s perspective, optimizing for generative AI search is optimizing for Search, and thus still SEO. Google also points readers at its guidance for evaluating third-party SEO advice.
That paragraph is the part every agency deck will screenshot. The rest of the guide is more useful.
Google’s highest-leverage advice is not a new schema type. It is content quality:
If your “AI content plan” is ten near-identical listicles for every synonym of the same buyer question, Google just told you that plan is both spammy and weak.
To show in generative AI features on Google Search, a page must be indexed and eligible for Search with a snippet, meet technical requirements, and remain included via the Search generative AI control in Search Console.
Crawlability, JavaScript SEO, page experience, and duplicate cleanup remain the boring prerequisites. Generative features do not invent a second index you can hack with a markdown file.
Google points site owners to the Generative AI performance report for impressions in generative features, and warns that no third-party tool has access to Google’s internal ranking or AI systems. That pairs with the measurement gaps DerivateX already covered in the GSC Gen AI report piece: impressions help, they do not prove pipeline.
Google’s mythbust section is a gift to operators and a problem for gimmick vendors:
Read that list carefully. Google is not saying off-site reputation never matters. Google is saying fake mentions and AI-only files are not a Google Search lever.
Google’s guide is scoped to generative AI features on Google Search (AI Overviews, AI Mode, and related Search surfaces).
It does not:
That is why DerivateX’s first-party vs third-party citations and third-party assets for AI search work still matter. Google can correctly say “GEO for Google is still SEO” while your buyers still get vendor shortlists from engines Google does not control.
Agencies that use Google’s guide to declare “GEO is dead, only classic SEO remains” are reading the title and skipping the scope line.
That last point is where SEO-only teams get surprised. Classic competitor research asks who ranks beside you. AI substitution asks who inherits demand when a buyer rules you out. Different graph, different content brief.
Assume you sell a B2B workflow tool and leadership just forwarded Google’s doc with the note “so we can pause GEO.”
Day 1
Day 2 to 3
Day 4 to 5
If Google impressions rise and recommendation share outside Google stays flat, you improved Google generative hygiene. You did not finish AI search.
Most agencies will either:
The durable DerivateX position is harder to copy:
Google is right about Google. Foundational SEO and non-commodity content are the entry ticket for AI Overviews and AI Mode. The hacks Google listed are mostly noise. Multi-engine recommendation share and pipeline proof are still a separate operating system, which is why the 8 GEO metrics we report and Gumlet-style attribution still exist.
If you want a baseline before a retainer conversation, start with the free AI visibility audit. Live options remain on pricing.
Google said that from Google Search’s perspective, optimizing for generative AI features is still SEO. It did not ban the labels. It rejected the idea that Google AI Overviews and AI Mode require a separate hack stack.
Not for Google Search visibility. Google says it ignores those files for Search and generative Search features. Other tools may use them; that is a different decision.
It is necessary for Google generative features that pull from the Search index. It is not sufficient for multi-engine B2B recommendation share.
Search Console generative AI impressions for Google surfaces, plus prompt-panel citation and recommendation share across the engines your buyers use, plus CRM outcomes.
GEO myths covers recurring industry confusion. This piece is a direct operator read of Google’s official generative AI optimization guide and the scope boundary Google draws.
Shivanshi Bhatia is the co-founder of DerivateX, a B2B SaaS SEO and Generative Engine Optimization agency that engineers AI citations in ChatGPT, Perplexity, Claude, and Gemini and connects them to demo bookings and revenue pipeline. She runs operations and delivery, which means every audit, content brief, and published page ships through a system she built. She owns the client relationship from kickoff through reporting, so clients spend their time on decisions instead of chasing updates. She has worked in SaaS since 2019 and reviews client work before it goes live.
