GEO vs AEO vs AI SEO: What the Terms Actually Mean

Three acronyms keep showing up in marketing conversations: GEO, AEO, and AI SEO. They sound different, they get separate conference talks, and agencies sell them as distinct services. But when you strip away the branding, these terms describe overlapping responses to the same shift: buyers now research software categories through AI-powered tools before they ever visit a website or talk to sales. If your company doesn’t appear in those AI-generated answers, you’re not on the shortlist.

The confusion is real. A head of marketing at a £5M ARR SaaS company shouldn’t need a glossary to figure out what their agency is actually doing. So here’s a plain breakdown of what each term means, where they overlap, and which ones matter for B2B tech companies trying to grow pipeline.

The short answer: GEO, AEO, and AI SEO are different labels for work that mostly converges on the same set of tactics. The differences are more about emphasis and origin than about fundamentally different disciplines. Understanding the nuances helps you ask better questions of agencies and internal teams, but no single acronym should dictate your strategy.

Let’s get specific about each one.

What is GEO?

GEO stands for Generative Engine Optimisation. The term emerged as AI tools like ChatGPT, Perplexity, and Gemini became significant research channels for B2B buyers. GEO focuses on making your brand visible and accurately represented in the outputs these generative AI tools produce.

Traditional SEO cares about ranking in a list of ten blue links. GEO cares about whether an AI model mentions your company when a buyer asks “what’s the best observability platform for mid-market SaaS?” That’s a fundamentally different challenge because you’re not optimising for a search algorithm’s ranking factors. You’re trying to influence how a large language model synthesises information about your category and your brand.

The work itself involves several practical steps. Teams run a GEO audit to see how ChatGPT, Perplexity, Gemini, and Claude currently describe the company, what sources they pull from, and where competitors get cited instead. From there, the focus shifts to content architecture: building topic clusters around the questions buyers ask AI tools and closing the gap between what the company says and what AI tools synthesise. Entity and authority building also plays a role, with consistent brand descriptions, third-party citations, and review coverage helping AI tools verify a credible picture from multiple independent sources.

GEO is not a replacement for SEO. Strong SEO foundations are an input to GEO. What GEO adds is deliberate work on how AI models learn about a company. AI search usage in the UK has grown significantly, with over 30% of knowledge-based queries now receiving AI-generated responses across major platforms. For B2B SaaS companies in the £2M to £20M ARR range, this shift directly affects how potential customers discover and evaluate vendors.

What is AEO (answer engine optimisation)?

AEO predates GEO as a concept. It originally described the practice of optimising content to appear in featured snippets, Google’s “People Also Ask” boxes, and voice assistant answers. The goal was to be the single answer a search engine surfaced, rather than one of ten results a user might click.

The term has evolved. As AI-powered answer engines like Perplexity and Google’s AI Overviews have grown, AEO now also covers optimisation for these newer formats. The core idea remains the same: structure your content so that machines can extract a clear, authoritative answer and present it directly to the user.

AEO practitioners tend to focus heavily on structured data, schema markup, and concise question-and-answer formatting. If GEO is about shaping how an LLM understands your brand across its entire training corpus, AEO is more narrowly focused on winning specific answer boxes for specific queries. A useful comparison of these approaches highlights that AEO typically targets queries with clear, definitive answers, while GEO addresses more complex, conversational queries where AI tools synthesise from multiple sources.

For B2B SaaS marketers, AEO matters most for bottom-of-funnel queries. When a buyer searches “what is [your category]?” or “how does [your product] compare to [competitor]?”, you want your content to be the answer. This means maintaining well-structured FAQ pages, comparison content, and product explainers that machines can parse easily. Teams that fix their structured data and use proper schema markup get cited more often in these answer formats.

What is AI SEO?

AI SEO is the broadest and loosest of the three terms. It gets used in two distinct ways, which causes most of the confusion.

The first meaning: optimising your content so it performs well in AI-mediated search experiences. This includes Google’s AI Overviews, Bing’s Copilot answers, ChatGPT’s search features, and standalone tools like Perplexity. In this sense, AI SEO is essentially an umbrella term that covers both GEO and AEO, plus any other work aimed at visibility in AI-powered discovery channels.

The second meaning: using AI tools to do SEO work more efficiently. This includes using LLMs for keyword research, content briefs, technical audits, and content generation. This meaning is about process, not about where you’re trying to appear.

Most agencies and publications use AI SEO in the first sense. The distinction between traditional SEO and its AI-focused variants is becoming more important as search behaviour fragments across multiple platforms. Google still holds roughly 90% of UK search market share, but the nature of those search results is changing fast. AI Overviews now appear on a large proportion of informational queries, which means even traditional Google traffic is increasingly mediated by AI.

For a B2B SaaS company, the practical difference between AI SEO and GEO is minimal. Both involve creating authoritative, well-structured content that AI systems can understand, cite, and present to users. The main distinction is that AI SEO tends to keep one foot in the traditional search world, while GEO focuses more exclusively on generative outputs.

How the three terms overlap

If you’ve read the sections above and thought “these sound like the same thing with different names,” you’re mostly right. The Venn diagram has a very large centre.

All three approaches share the same core tactics:

• Creating clear, well-structured content that answers specific buyer questions
• Building entity consistency across the web so AI tools can form an accurate picture of your brand
• Earning third-party citations, reviews, and mentions that serve as trust signals for both search engines and LLMs
• Using structured data and schema markup to help machines parse your content
• Monitoring how AI tools describe your company and category, then closing gaps

The differences are mostly about emphasis. AEO leans toward structured answers and featured snippets. GEO leans toward LLM training data and generative outputs. AI SEO tries to cover everything. A 2026 guide to these optimisation strategies notes that the practical work for all three converges on the same activities for most companies.

Where real differences exist, they’re at the margins. GEO practitioners might spend more time analysing LLM training data sources and citation patterns. AEO specialists might focus more on schema markup and voice search formatting. But for a B2B SaaS marketing team with limited resources, the work is functionally the same: make your brand easy for AI systems to understand, trust, and recommend.

The fragmentation of terminology is partly an industry problem. Agencies and consultants benefit from having a distinct service name. But the buyer doesn’t care whether you call it GEO, AEO, or AI SEO. They care whether their company shows up when a prospect asks an AI tool about their category.

Which term should B2B marketers use?

Pick one and be consistent. That’s genuinely the most practical advice here.

If you’re briefing an agency, “GEO” is probably the most precise term for the work that matters most to B2B SaaS companies right now. It specifically addresses how generative AI tools represent your brand, which is the fastest-growing channel for buyer research. AI search is rewriting how brands get discovered, and GEO captures that shift most directly.

If you’re talking to your board or CEO, “AI SEO” is probably easier to explain. It connects to something they already understand (SEO) and adds the AI qualifier that signals this is about new channels and behaviours.

If you’re evaluating agencies, pay less attention to which acronym they use and more attention to what they actually do. Ask these questions:

• Can they show you how ChatGPT, Perplexity, and Gemini currently describe your company?
• Do they audit your entity consistency across third-party platforms like G2, Capterra, and Crunchbase?
• Do they build content specifically around the queries buyers ask AI tools, not just traditional keyword volume?
• Can they track changes in your AI visibility over time?

At Gripped, we run GEO audits as part of our work with B2B SaaS and tech companies. The audit covers how major AI tools describe the company and its category, what sources they pull from, and where competitors are cited instead. The label matters less than whether the agency actually does the work.

Why the naming matters less than the work

The real risk for B2B SaaS marketers isn’t picking the wrong acronym. It’s ignoring the shift entirely.

Buyers in the £2M to £20M ARR segment are already using AI tools to build shortlists. They ask ChatGPT “what are the best [category] tools for mid-market companies?” and they trust the answers enough to skip the first three pages of Google results. If your company isn’t mentioned in those AI-generated responses, you’ve lost the opportunity before your sales team even knows it existed.

The work that fixes this is straightforward, even if it’s not easy. Recent data on AI search and SEO trends shows that companies with consistent entity descriptions across multiple authoritative sources are cited significantly more often by AI tools. This means aligning your company descriptions, categories, and value propositions across LinkedIn, G2, Capterra, Crunchbase, your own website, and any other public profile.

Monthly monitoring matters too. Run manual prompt tests: category queries (“best project management tools for SaaS”), comparison queries (“Product A vs Product B”), and problem queries (“how to reduce churn in B2B SaaS”). Track whether your brand appears, how accurately it’s described, and how your competitive share changes over time. This isn’t glamorous work, but it’s the work that moves pipeline.

None of this replaces traditional SEO. Google still sends the majority of referral traffic, and strong organic rankings remain a primary input for how AI tools evaluate authority. The companies that perform best in AI-generated answers are typically the ones that already have strong SEO foundations, authoritative backlink profiles, and consistent third-party coverage.

Common questions

Is AEO the same as GEO?

Not exactly, but the practical overlap is significant. AEO originated around featured snippets and voice search answers, focusing on structured, extractable content. GEO focuses specifically on visibility within generative AI outputs like ChatGPT responses and Perplexity citations. The tactics are similar: clear content structure, entity consistency, third-party authority signals, and schema markup. For most B2B SaaS companies, the distinction doesn’t change what you’d actually do day to day. If your agency says they do AEO, ask whether they also monitor and optimise for generative AI tools. If they don’t, the work is incomplete.

Is AI SEO just a buzzword?

It’s a broad term, but it describes real work. The growing body of evidence around AI-mediated search shows that buyer behaviour is genuinely shifting. People are using AI tools for research, and those tools are forming opinions about brands based on publicly available information. AI SEO as a label might be vague, but the underlying challenge is concrete: making sure AI systems can find, understand, and accurately represent your company. The buzzword risk comes when agencies use the term without doing anything different from traditional SEO. If someone sells you “AI SEO” but only delivers keyword research and blog posts, you’re paying for a rebrand of existing services.

The naming debate around GEO, AEO, and AI SEO will likely settle over the next year or two as the industry standardises. What won’t change is the need for B2B SaaS companies to actively manage how AI tools represent their brand. Start with an audit of your current AI visibility, fix your entity consistency, and build content around the questions your buyers actually ask these tools.

If you’re a SaaS or tech marketing leader who wants to understand where your brand stands in AI-generated results and what to do about it, Gripped can help. We work exclusively with B2B SaaS and tech companies, and our approach tracks pipeline and revenue rather than vanity metrics. Get your free growth audit to see where the gaps are and what to prioritise first.