By Chantelle Voss, Founder, Carli.ai

SEO optimises for ranking a page in a list of results. AEO optimises for being the answer a system gives. GEO optimises for being included when an AI model generates a response from multiple sources.

They overlap heavily. They are not replacements for each other. And the difference matters less than most articles suggest, because the practical work of all three converges on the same handful of activities.

This guide explains what each term actually means, where they genuinely differ, and what to prioritise if you only have budget for one.

What is SEO

Search Engine Optimization is the practice of improving a website so it ranks higher in the organic results of a search engine, primarily Google.

The mechanics are well established after twenty-five years: keyword research, on-page optimisation, technical health, content quality, and backlinks. The outcome you are optimising for is a position in a ranked list. A user sees ten blue links and clicks one.

SEO is not going away. Google still processes the majority of searches, and organic results still sit below AI Overviews on most result pages.

What is AEO

Answer Engine Optimization is the practice of structuring content so it gets selected as the direct answer to a question, rather than as one link among many.

The concept predates AI chatbots. Featured snippets, knowledge panels, and voice assistant responses were all answer-engine surfaces. What changed is scale. When Google AI Overviews, ChatGPT, and Perplexity answer a question directly, the user often never clicks through to any source.

AEO work concentrates on:

• Clear, direct answers placed near the top of a section
• Question-formatted headings that match how people actually ask
• FAQPage and HowTo schema markup
• Structured formats such as lists, tables, and short definitional paragraphs
• Factual accuracy that can be verified against other sources

The outcome you are optimising for is being quoted, not being clicked.

What is GEO

Generative Engine Optimization is the practice of increasing how often a brand appears in responses generated by large language models such as ChatGPT, Claude, Gemini, and Perplexity.

This is where the biggest departure from traditional SEO happens. Generative models do not rank pages. They synthesise an answer from many sources, some retrieved live and some absorbed during training. Your own website is one input among thousands.

A Semrush study analysing 230,000 prompts and more than 100 million citations across ChatGPT, Google AI Mode, and Perplexity found that the most frequently cited domains were Reddit, LinkedIn, and Wikipedia. Traditional SEO leaders were largely absent from the top of that list.

That single finding explains why GEO cannot be executed purely on your own domain. If the sources models cite most are community platforms and reference sites, then visibility depends on being discussed accurately in those places.

The practical differences

	SEO	AEO	GEO
Optimising for	Position in a ranked list	Being the selected answer	Being included in a generated response
Primary surface	Google organic results	Featured snippets, AI Overviews, voice	ChatGPT, Perplexity, Gemini, Claude, Copilot
Main lever	Content quality and backlinks	Content structure and schema	Third-party mentions and citations
Success metric	Rankings, organic traffic	Snippet ownership, answer inclusion	Mention rate, citation count, share of voice
Where the work happens	Mostly your own site	Mostly your own site	Mostly off your site
Typical time to results	4 to 9 months	2 to 4 months	3 to 6 months

The row that matters most is the second-to-last one. SEO and AEO are largely things you do to your website. GEO is largely something you do everywhere else.

Where all three overlap

Most of the underlying work is shared. This is the part comparison articles usually miss.

Content quality. Every one of these disciplines rewards accurate, useful, well-organised content. There is no version of this where thin content wins.

Technical foundation. Crawlable, fast, semantically structured pages help all three. If AI crawlers cannot parse your site, nothing else you do matters.

Structured data. Schema markup helps search engines understand your pages and helps language models extract and attribute information correctly.

Authority and trust. Google’s E-E-A-T framework (Experience, Expertise, Authoritativeness, Trust) has direct parallels in how AI systems weight sources. Microsoft Advertising’s published guidance on AI visibility emphasised the same thing: AI assistants prioritise sources they can trust, with signals such as verified reviews and consistent brand information carrying real weight.

If you did nothing but improve content quality, fix your technical foundation, add schema, and build genuine authority, you would improve on all three fronts simultaneously.

What actually changed

Three things are genuinely different now.

The click is optional

For a large and growing share of queries, the user gets their answer without visiting any website. Traditional SEO measured success in clicks. When the answer appears in the interface, the click never happens, but the brand impression does.

This is why mention tracking has become its own discipline. Being named in an answer has value even with zero referral traffic.

Off-site signals became primary

In traditional SEO, off-site work meant backlinks. In GEO, it means being talked about. Research from Ahrefs described the current period as the era of off-page SEO, where brand mentions across trusted community platforms function the way backlinks once did.

Semrush found that Reddit alone accounted for roughly 40% of all citations used by major language models. That is not a channel most SEO teams have ever managed.

Sources you do not control now describe your brand

A Search Engine Land analysis found that AI Overviews heavily prioritise conversational content and real user experiences from high-authority platforms, weighing firsthand anecdotes alongside factual reporting.

The practical consequence is that a single negative thread with enough traction can shape how an AI system summarises your brand to millions of people. Traditional SEO had no equivalent exposure.

What to prioritise if you can only do one

For most brands, the honest answer is: fix SEO fundamentals first, add AEO structure second, then invest in GEO.

If your technical SEO is broken, fix that before anything else. AI crawlers face the same obstacles Googlebot does. A site that cannot be crawled cannot be cited.

If your content is thin, improving it lifts all three at once. This is the highest-return work available to most brands.

If your fundamentals are solid and you are still invisible in AI answers, the gap is almost certainly off-site. That is a GEO problem, and it is solved by earning presence in the places models actually cite.

We see this pattern repeatedly in client work. Brands with strong Google rankings and weak community presence discover they are invisible in AI-generated answers, and no amount of on-site optimisation closes that gap.

Do you need three separate strategies

No. You need one strategy with three sets of outcomes.

In practice that looks like:

• A technically sound, well-structured website with proper schema markup
• Content that answers real questions directly and accurately
• A named expert attached to that content
• Genuine presence in the community platforms where your category gets discussed
• Third-party validation through reviews, media coverage, and original research
• Measurement that tracks rankings, answer inclusion, and AI mentions separately

Splitting this into three competing budgets creates duplicated work and internal confusion. Treat it as one programme with a broader definition of visibility than SEO alone ever had.

Frequently asked questions