SEO vs AEO vs GEO: What Businesses Actually Need

SEO. AEO. GEO. AI SEO. AIO.

If you work in marketing, you’ve probably heard some version of this lately: SEO isn’t enough anymore. You need a completely new strategy for AI.

I understand why that gets attention. Buyer behavior is changing, and people can now use tools like ChatGPT and Google’s AI experiences to research problems, compare options, and evaluate companies before they ever reach your website.

Underneath all the acronyms, the concern is pretty simple: revenue.

If the way buyers research changes, you need to stay visible throughout that process. You can’t put all your energy into converting demand at the bottom of the funnel while becoming harder to discover earlier in the journey.

But I think the SEO vs. AEO vs. GEO conversation has become more complicated than it needs to be.

My view is simple: AEO and GEO are largely extensions of good SEO.

There are real differences. AI-assisted search gives people more room to ask longer, more contextual questions. Systems may retrieve and synthesize information differently. Measurement is expanding beyond rankings and clicks.

The foundation, though, is still very much alive.

SEO, AEO and GEO: What’s the actual difference?

SEO, or search engine optimization, is the work of improving visibility in search engines.

AEO, or answer engine optimization, generally refers to making information easier for answer-driven systems to understand and use when responding directly to a question.

GEO, or generative engine optimization, generally refers to improving visibility within AI-generated responses.

Those definitions sound neat. In practice, the boundaries are blurry.

Google now says that AEO and GEO are common terms, but optimizing for generative AI experiences within Google Search is still SEO from its perspective. Its AI features rely on the same core Search ranking and quality systems.

That’s why I don’t think most businesses need three disconnected strategies, teams, or budgets.

The more useful question is: What has changed enough that your search strategy needs to evolve?

Good SEO is still the foundation

The rush toward GEO makes it easy to forget how much of the existing foundation still matters.

Your content still needs to be crawlable and understandable. You still need useful, original information, clear site structure, accurate business details, credible evidence, and a strong experience when someone lands on the site.

Google’s current guidance for AI Overviews and AI Mode says its existing SEO best practices remain relevant and that there are no additional technical requirements just to appear in those experiences.

That makes a strong SEO strategy the starting point rather than something you abandon because AI search has arrived.

Google also pushes back on some of the “AI optimization” tactics getting outsized attention. For example, it says creating special AI text files or markup does not improve visibility in its generative search features. Google has also clarified that llms.txt is not used by Google Search.

Other platforms have their own requirements. OpenAI says a site needs to allow OAI-SearchBot if it wants its content eligible for inclusion in ChatGPT Search. Placement still isn’t guaranteed.

That’s a better way to think about this category. There is no universal AI-search switch. Platform details vary, while the underlying search and content foundation still matters.

What has actually changed? The amount of context

Traditional SEO hasn’t been purely keyword-based for years. Google’s ranking systems already use technologies designed to understand concepts, meaning, and intent, rather than relying only on exact keyword matches.

AI search expands the amount of context a person can bring into the search.

A traditional query might be:

Best web design agency

An AI prompt could be:

We’re a mid-market B2B software company moving upmarket. We need a website agency that can help with messaging, UX, and development, understands long sales cycles, and has experience managing complex stakeholder groups. Who should we consider?

That is a much richer information need.

Google says AI Mode is designed for nuanced questions and complex comparisons that may previously have required several separate searches. It can also use “query fan-out,” generating multiple related searches behind the scenes to gather information for one response.

For marketers, that means the content strategy has to move beyond a list of isolated keywords.

What questions surround the buying decision? What constraints might a buyer include? What proof do they need? What comparisons are they making? What would they ask next?

This is where AI search becomes less about inventing a new discipline and more about understanding the customer at a deeper level.

It’s also why the relationship between AI and the broader website experience matters. Getting discovered is only one part of the journey. The experience still has to help the buyer understand, evaluate, and act.

AI search matters across the funnel

I initially think of AI search as a strong top-of-funnel opportunity because it can introduce a company while someone is still researching a problem or considering possible solutions.

But it doesn’t stop there.

A buyer can also ask very specific questions late in the journey: whether a company works with a certain industry, how two providers compare, what a service includes, or whether a product meets a particular requirement.

So the job isn’t simply “get mentioned by AI.”

You want accurate, useful information available throughout the buying journey so the systems your audience uses have something credible to work with.

You can’t fully control what an AI system says about your company. You can improve the quality, clarity, consistency, and accessibility of the information available about your business.

That broader challenge is where a dedicated AI Search strategy starts to become useful.

Think beyond the blog

A strong content strategy matters, but AI search is another reason not to treat “content” as synonymous with “blog posts.”

Your service pages matter. Your videos matter. Third-party coverage can matter. Industry conversations can matter. Your broader digital presence matters.

Google explicitly says its generative search experiences can surface different types of web content, including information from blogs, videos, and forum discussions. It also warns that chasing artificial mentions isn’t a shortcut.

This is where the old idea of omnichannel marketing becomes more practical.

Your brand, website, content, video, PR, third-party presence, and search strategy increasingly need to tell a coherent story.

For teams with the resources to sustain quality, I personally favor a meaningful publishing cadence. I’d rather see a company commit to something like eight well-planned, useful blog posts a month than publish one random article every few weeks.

That’s my operating recommendation, not an AI ranking factor.

The point is consistency and useful coverage, not manufacturing a page for every possible prompt. Google specifically warns against scaled content created primarily to manipulate rankings, regardless of whether the content was produced for traditional or AI-assisted discovery.

What businesses should actually do

If you’re trying to figure out where to start, I’d focus on five things.

1. Understand how your audience researches

Look beyond keyword volume.

What are buyers trying to understand early in the journey? What do they compare? What concerns come up before a purchase? What questions does your sales team answer repeatedly?

Those questions should shape what you publish.

2. Build a content roadmap

Define the topics you need to own, the audience behind them, the message you want to reinforce, the evidence you can bring, and the business action the content should support.

Then create consistently.

Throwing content at the wall and hoping AI picks it up is not a strategy.

3. Get the technical foundation right

Make sure the systems you want visibility in can access the content you intend them to use.

For Google, that means the same crawlability and indexing fundamentals that matter for SEO. For ChatGPT Search, OpenAI says publishers should allow OAI-SearchBot.

4. Strengthen the broader information environment around your brand

Keep your website accurate. Build useful content. Maintain consistency across the places where your company is described. Earn credible third-party coverage where it makes sense.

5. Measure business impact, not citation vanity

AI visibility matters when it contributes to business outcomes.

OpenAI automatically adds utm_source=chatgpt.com to ChatGPT referral URLs, so that traffic can be identified in analytics.

From there, measure what matters.

Did those visitors engage? Did they reach relevant service or product pages? Did they convert? Did they become qualified leads? Did they become pipeline?

But referral traffic won’t capture every form of AI influence. Someone may see your company recommended, then search for you later or return through another channel.

That’s why newer visibility metrics have a place too. Microsoft’s AI Performance reporting in Bing Webmaster Tools includes metrics such as citations, cited pages, grounding queries, and visibility trends across supported AI experiences.

Microsoft also makes an important distinction: citation counts don’t automatically equal rankings, authority, or prominent placement within an answer.

Track those signals separately from traditional rankings and traffic.

So, should you invest in SEO, AEO or GEO?

Keep investing in SEO.

Then broaden what you mean by search.

Understand the richer questions your audience is asking. Build useful content around buyer decisions. Make your expertise accessible to the platforms your customers use. Strengthen the information surrounding your brand. Measure traditional search, AI visibility, referral traffic, and qualified business outcomes without collapsing them into one number.

AEO and GEO are useful names for how search is evolving.

They don’t require you to throw away everything you already know about SEO.

The companies that handle this well will be the ones that avoid both extremes: pretending nothing has changed and chasing every new AI-search tactic that shows up.

Build the foundation. Create the strategy. Measure what happens. Then keep adapting.

If you’re already investing in search but aren’t sure how your website and content should evolve for AI-assisted discovery, explore our AI Search services and SEO services to identify the gaps and build the right roadmap.