AI SEO vs traditional SEO: what is the difference, and which meaning do you need?

The difference depends on which meaning is in play: AI-assisted SEO changes only how the work gets done, while optimising for AI answers changes where you want your pages to appear. In both cases the platforms’ own rules point back to the foundations traditional SEO already covers, though each meaning rests on different evidence and carries different risks.

On this page each claim is labelled as documented (a platform’s own documentation says so), research (a named study, with its limits) or our recommendation (sensible practice, nothing more).

What “AI SEO” can mean: two different things

Meaning one is about process. You use AI tools to help with SEO work: research, drafting, grouping keywords, auditing pages. The goal is the same as before. Only the tools have changed.

Meaning two is about destination. You want your pages found, used and cited when someone gets an answer from an AI system such as Google’s AI Overviews and AI Mode, ChatGPT, Claude or Perplexity. Other names for this include GEO (generative engine optimisation) and AEO (answer engine optimisation).

Much of the confusion comes from mixing the two. A claim that “AI SEO saves time” is about meaning one. A claim that “AI SEO wins citations” is about meaning two. Each needs different evidence, so separate them before you weigh either. The debate over names is covered in what AI SEO is and SEO vs GEO vs AEO.

Traditional SEO in one paragraph: what it is trying to achieve

Traditional SEO makes a site easy for search engines to crawl, index and understand, and worth showing for the searches it targets. Google sums up the foundations as meeting its technical requirements for Search, following its spam policies, and creating helpful, reliable, people-first content (documented). The aim is to be the result a searcher chooses. Everything else is method.

Meaning one: using AI tools to do SEO work

You are still doing SEO, with AI doing some of the work. Google has said clearly how it views that.

• Using AI is allowed. Google’s guidance on generative AI content says these tools can be useful for researching a topic and adding structure to original content (documented).
• Scale without value is spam. Google’s spam policies define scaled content abuse as generating many pages “for the primary purpose of manipulating search rankings and not helping users”, and say this applies “no matter how it’s created”. Using generative AI to produce many pages without adding value for users is one of the listed examples (documented).
• Review is expected. Google warns that generative models predict a likely sequence of words and do not retrieve facts, so their output may contain inaccuracies. It calls manual fact-checking and review of all AI-generated content before publishing “critical”, and says this also covers title elements, meta descriptions, structured data and image alt text (documented).

So the risk with meaning one is publishing a lot of thin or wrong material because it was cheap to make. That risk existed before AI, but the tools make it faster to produce that kind of material. There is more detail in is AI content good for SEO.

Cost, ROI and speed figures attached to AI SEO tools usually come from the companies selling them. Treat them as vendor claims. This page repeats none of them.

Meaning two: optimising to be found and cited in AI answers

Google AI Overviews and AI Mode

Google’s AI features page is the clearest primary source here (documented):

• You can apply the same foundational SEO best practices to AI features as to Google Search overall.
• To be shown as a supporting link, a page must be indexed and eligible to be shown in Google Search with a snippet. Google says there are “no additional technical requirements”.
• Specific optimisation “isn’t required” for AI Overviews and AI Mode, though existing SEO fundamentals “continue to be worthwhile”.
• AI Overviews only appear when Google’s systems judge them to add something to classic Search, and they “often don’t trigger”.
• robots.txt rules for Googlebot control how your site is crawled for Search. Google-Extended is a separate control for training and grounding in some of Google’s other systems.

ChatGPT, Claude and Perplexity

Outside Google, the main thing the platforms document is crawler access. Each one names separate crawlers for different jobs (documented):

Platform	Search crawler	Training crawler	User-triggered fetcher
OpenAI	OAI-SearchBot	GPTBot	ChatGPT-User
Anthropic	Claude-SearchBot	ClaudeBot	Claude-User
Perplexity	PerplexityBot	None listed; Perplexity says PerplexityBot is not used to crawl content for AI foundation models	Perplexity-User

OpenAI says each robots.txt setting is independent. Sites that opt out of OAI-SearchBot will not be shown in ChatGPT search answers, though they can still appear as navigational links. Anthropic says its bots honour robots.txt, and that blocking Claude-SearchBot or Claude-User may reduce your visibility in Claude’s search results. Perplexity says Perplexity-User generally ignores robots.txt because a user asked for the page. Setup is covered in AI crawlers and robots.txt.

What the research adds

The main academic reference is Aggarwal et al., “GEO: Generative Engine Optimization”, accepted to KDD 2024 (research). The authors built GEO-bench, a benchmark of 10,000 queries. They tested ways of rewriting source content on their own generative engine, which wrote answers from the top five Google results for each query. Adding citations, quotations from relevant sources and statistics raised visibility by up to 40% on the measures the authors defined. They also ran the methods on Perplexity.ai.

The limits matter. The engine, benchmark and measures were the authors’ own, the paper says how well the methods worked varied by subject area, and live AI products change over time. Treat the paper as a guide to where to experiment. It does not show that any change will work on a given platform today.

Side-by-side comparison of traditional SEO, AI-assisted SEO and optimising for AI answers

	Traditional SEO	AI-assisted SEO (meaning one)	Optimising for AI answers (meaning two)
What it is	A discipline with a target	A way of working	A target
Goal	Rankings and clicks from search results	The same goal, with AI tools in the workflow	Being used, cited or described accurately in AI answers
Platform rules that apply	Search technical requirements, spam policies, helpful content	The same, plus Google’s guidance on AI content and scaled content abuse	Google: the same as Search. Others: crawler access through robots.txt
Main risk	Pages that are not indexed or not useful	Volume replacing value, and errors nobody checked	Blocking the wrong crawler, or expecting control no platform offers
How you see progress	Search Console, rankings, traffic	The same as traditional SEO	Google: Search Console’s Generative AI performance report shows impressions in AI Overviews and AI Mode (clicks stay within the overall Web search figures). Other assistants: you check the answers yourself or with a tracking tool

The middle column changes only the method. The real difference is in the last column: a different target, and a less direct way to see whether you are reaching it.

What stays the same across all three

Pages that can be crawled and indexed. Content that is accurate and answers the question properly. Internal links a crawler can follow. Important content available as text, and structured data that matches what is visible on the page. Google lists each of these as still worthwhile for its AI features (documented).

If you have been doing traditional SEO well, that work carries straight over. If you have not, adding AI on top will not make up for it. The home guide’s GEO vs SEO section covers where they overlap in more depth.

What is documented, what is research, and what is practice

Kind of claim	Examples on this page	How much weight to give it
Documented	Google’s AI features page, its AI content guidance, spam policies and Search Console help; the OpenAI, Anthropic and Perplexity crawler pages	The platform’s own statement. Check the page date, because these change
Research	Aggarwal et al., KDD 2024	Evidence under stated conditions, with stated limits
Practice	The order of work suggested below	A recommendation. Useful, never a guarantee

If a claim fits none of these, such as an unattributed percentage on a sales page, treat it as marketing.

Which one should you spend time on first?

We recommend the same order in both situations: the foundations first, then your workflow, then visibility in AI answers.

1. Small business with little time: check that your key pages are indexed and can show a snippet, then make them genuinely useful. Use AI tools only where a person reviews the output before it goes live. Make one deliberate decision about which AI crawlers your robots.txt allows.
2. In-house team with some capacity: keep traditional SEO as the base. Use AI tools to speed up research and drafting, with editorial review as a fixed step. Then start checking how AI assistants answer your buyers’ questions, using how to measure AI visibility as the method.

What nobody can promise

Google’s AI features page explains what makes a page eligible. It does not promise inclusion, and AI Overviews often do not appear at all. None of the crawler pages from OpenAI, Anthropic or Perplexity says that allowing their bots will get you cited. The GEO research reports results on its own benchmark and tells you nothing certain about your site.

So anyone promising citations, a fixed timeline or a return on investment is promising something the platforms themselves do not. What you can do is make your pages eligible, accessible and useful, test changes carefully, and read research with its limits in mind.