AI SEO is not a replacement for traditional SEO. It is traditional SEO plus extra work for a new kind of result. The foundations stay the same: pages that can be crawled and indexed, content that genuinely helps, clean site structure, and authority you earn. What changes is the target. Instead of competing for a ranked position on a list of links, you are competing to be cited or named inside an AI-generated answer, so your facts must be easy to extract, consistent everywhere, and backed by sources you don’t control.
This article breaks down what still matters, what’s genuinely different, and how we decide where the next dollar of search budget should go.
What “AI SEO” actually means
The term gets used in two ways, and mixing them up leads to bad decisions.
The first meaning is optimizing for AI search experiences: Google AI Overviews and AI Mode, ChatGPT search, Perplexity, and Copilot. That is the meaning we use in this article, and it overlaps heavily with what others call generative engine optimization (GEO).
The second meaning is using AI tools to do SEO work, such as drafting content, clustering keywords, or writing meta descriptions at scale. That is a workflow choice, not a strategy. Google’s guidance on generative AI content is clear on the risk: using AI to generate many pages without adding value for users may violate its spam policy on scaled content abuse, and AI output should be fact-checked before publishing, including titles, meta descriptions, and structured data. Publishing more AI-written pages is not AI SEO. It is often the fastest way to make a site worse.
What still matters: the foundations don’t change
Google says it directly. Its documentation on AI features and your website states that SEO best practices remain relevant for AI Overviews and AI Mode, and that there are no additional requirements or special optimizations needed to appear in them. To be eligible as a supporting link, a page must be indexed and eligible to show with a snippet. Google also notes that you don’t need new machine-readable files, “AI text files,” or special schema to appear.
The fundamentals Google lists as still worthwhile include:
- Allowing crawling in robots.txt and in your CDN or hosting infrastructure
- Making content easy to find through internal links
- Providing a good page experience
- Keeping important content in text form, supported by quality images and video
- Making sure structured data matches the visible text on the page
- Keeping Merchant Center and Business Profile information up to date
If your technical SEO is broken, AI visibility work is wasted. A page Googlebot can’t index can’t be a supporting link in an AI Overview. That is why we treat technical and content SEO as the base layer of any AI search program, not a separate line item. For Shopify stores, we break the crawl and index checks down in our guide to auditing Shopify crawlability and indexing.
What’s different with AI SEO
The differences are real, but they sit on top of the foundations rather than replacing them.
| Question | Traditional SEO | AI SEO |
|---|---|---|
| Who you’re optimizing for | Googlebot and Bing | Also the crawlers behind ChatGPT, Perplexity, and other assistants |
| What a query looks like | Short keyword phrases | Longer, specific questions with follow-ups |
| What “winning” looks like | A ranked position and a click | Being cited, linked, or named in the answer |
| How sources are gathered | One query, one ranked list | Many related searches combined into one response |
| How you measure it | Rankings, clicks, organic revenue | Those, plus share of AI answers on a fixed prompt set |
More crawlers to allow
Classic SEO mostly worried about Googlebot. AI SEO adds other bots. OpenAI’s crawler documentation explains that OAI-SearchBot surfaces websites in ChatGPT’s search features, and that sites opted out of it won’t be shown in ChatGPT search answers (though they can still appear as navigational links). It is separate from GPTBot, which is used for model training, so you can allow search visibility while opting out of training. Many brands block these bots by accident through firewall or bot-management defaults.
Questions get longer and fan out
Google’s May 2025 post on succeeding in AI search experiences notes that people are asking “longer and more specific questions,” plus follow-ups. Google also describes a “query fan-out” technique, where AI Overviews and AI Mode may run multiple related searches across subtopics to build one response. In practice, a single page targeting one keyword covers less of the answer. Covering the follow-up questions around a topic matters more.
Being named matters, not just being linked
In a list of ten links, a weaker position still gets seen. In an AI answer, a buyer may see three to five brands. That raises the value of clear entity information (who you are, what you sell, who it’s for) and of independent corroboration: reviews, editorial coverage, and accurate marketplace listings that agree with your site.
Measurement is messier
Google says traffic from AI Overviews and AI Mode is included in Search Console’s Performance report under the “Web” search type, not broken out separately. Other assistants don’t offer an equivalent report. So AI SEO reporting usually adds a manual or tool-based prompt tracker on top of standard SEO metrics.
The SAMA Keep, Extend, Add framework
When a brand asks us whether to “switch” from SEO to AI SEO, we don’t start with a new budget line. We sort every existing SEO activity into three buckets.
Keep: work that serves both classic and AI search unchanged. Technical health, indexability, site speed, internal linking, helpful category and product content, and earning real links. Cutting these to fund “AI SEO” is the most common mistake we see.
Extend: work you already do that needs a wider scope. Robots.txt and CDN rules now cover AI search crawlers. Keyword research now includes the full questions and follow-ups buyers ask. Structured data and product feeds now need to match your site, Merchant Center, and marketplaces exactly. Reporting now adds a fixed prompt set.
Add: genuinely new work. Monthly testing of buyer prompts across ChatGPT, Google AI Mode, and Perplexity. Entity cleanup so your brand is described the same way everywhere. A deliberate plan for corroboration through reviews, PR, and comparison content.
In most audits, the “Add” bucket is the smallest. The biggest wins usually come from “Extend”: fixing what’s already in place so it serves both kinds of search. That’s also why a well-run SEO program rarely needs a doubled budget to cover AI search. It needs a reallocation, starting with blocked crawlers, inconsistent product data, and missing answers to obvious follow-up questions.
How to split your search budget
There’s no universal ratio, and we’d be skeptical of anyone who quotes one. Use these rules instead:
- If technical SEO is unhealthy (indexing errors, slow pages, blocked crawlers), fix that first. Nothing else compounds until it’s done.
- If your buyers research with long, comparative questions (considered purchases, B2B, health, high price points), shift more effort toward question coverage and corroboration.
- If you sell through marketplaces or retail, prioritize data consistency across your site, feeds, and listings. Conflicting prices and specs hurt you in both kinds of search.
- Measure against business outcomes. Google notes that clicks from results pages with AI Overviews tend to be higher quality, so judge search on conversions and contribution margin, not raw click counts.
For a deeper look at the scope of work and what to expect from a partner, see what an AI SEO agency actually does.
Frequently asked questions
Is traditional SEO dead because of AI search?
No. Google states that SEO best practices remain relevant for AI Overviews and AI Mode and that pages must be indexed to appear as supporting links. Traditional SEO is the entry ticket for AI search, not a competing approach.
Do I need an llms.txt file or special schema for AI SEO?
Not for Google. Its documentation says you don’t need new machine-readable files, AI text files, or special schema.org markup to appear in its AI features. Structured data still helps for rich results, as long as it matches the visible page.
Is AI SEO the same as generative engine optimization?
In practice, mostly. Both describe making your brand visible and citable in AI-generated answers. “AI SEO” tends to be used by teams extending an SEO program; “GEO” comes from academic research on generative engines.
Can I use AI to write my SEO content?
You can use it for research and structure, but Google warns that generating many pages without adding value may violate its scaled content abuse policy, and that AI output must be fact-checked. Original expertise is what both classic and AI search reward.
The bottom line
Traditional SEO and AI SEO aren’t competing budgets. Keep the foundations that serve both, extend your crawler rules, research, data, and reporting to cover AI answers, and add only the genuinely new work: prompt tracking, entity cleanup, and corroboration. Brands that do this in order usually find AI search visibility is cheaper than they feared and more connected to revenue than they expected.
At SAMA Labs, we run search alongside paid, retention, marketplaces, and creative, and we judge it on contribution margin and payback rather than traffic alone.
Not sure which bucket your SEO spend belongs in? Our AI search optimization team will audit your site and AI visibility, sort your current work into Keep, Extend, and Add, and show you where to reallocate first. Book your AI visibility audit.