If you work in B2B marketing, there's a decent chance somebody has told you recently that you need an AEO strategy, a GEO strategy, or both. There is also a decent chance that the explanation you got sounded suspiciously like SEO with a few new acronyms attached.
That skepticism is justified. A lot of what gets sold as Answer Engine Optimization and Generative Engine Optimization is familiar work: technically sound websites, useful content, clear positioning, strong authority signals, digital PR, third-party validation, and a brand that is easy to understand.
But dismissing AEO and GEO as nothing more than repackaged SEO would be a mistake too.
The way buyers find and evaluate information is changing. Search engines increasingly answer questions directly. Generative AI platforms synthesize information from multiple sources and recommend vendors, products, approaches, and next steps. For B2B companies, that means visibility is no longer just about whether your page ranks. It's also about whether your company appears in the answer, whether the AI describes you accurately, whether it recommends you, and whether the buyer has a reason to click through when it does.
That matters because more of the B2B buying process is happening before a prospect ever talks to sales. In a 2026 Gartner survey, 45% of B2B buyers said they used generative AI during a recent purchase, primarily to gather information on vendors and products. Forrester has reported even broader adoption across the buying journey. At the same time, Google's AI Overviews now reach billions of users and AI Mode has passed one billion monthly users.
So, yes, some of the terminology is overhyped. But the underlying change isn't.
Answer Engine Optimization and Generative Engine Optimization are related, but they are not exactly the same thing.
Answer Engine Optimization is the practice of making your content more likely to be selected as a direct answer inside traditional search and assistant experiences. Think Google Featured Snippets, People Also Ask results, voice assistants such as Siri or Alexa, and other search experiences that try to answer the question without requiring the user to sort through ten blue links.
Generative Engine Optimization is the practice of improving how your company, expertise, products, services, and content appear inside conversational and generative AI systems such as ChatGPT, Claude, Gemini, Perplexity, and Google AI Mode.
The goal is not simply to rank a web page. Ideally, you want the system to use you as a source, cite your content, represent your company accurately, recommend you when you are relevant, and create an opportunity for the user to visit your website or continue the buying journey.
In practice, the lines blur. Google Search itself now moves fluidly between classic results, AI Overviews, and conversational AI Mode. That is why it's often useful to use the broader phrase AI search optimization once the distinction is clear.
No. Good AEO and GEO depend on strong SEO fundamentals. They simply expand what you are optimizing for.
If search engines cannot crawl your site, your content is thin, your pages do not clearly explain what you do, or your company has little authority around the topics you want to own, adding FAQ schema or rewriting a few paragraphs for AI is not going to rescue you.
This is where some of the current AEO/GEO hype becomes unhelpful. There are vendors selling AI optimization as though the old rules disappeared overnight. They didn't. Technical SEO still matters. Search intent still matters. Useful content still matters. Links, mentions, subject-matter expertise, and brand reputation still matter.
What changed is the environment in which those signals are being interpreted.
Traditional SEO primarily asks: can this page rank for the query? AEO adds: can this page provide the clearest direct answer? GEO adds another layer: when an AI system synthesizes information from across the web, does it understand who you are, trust what you say, see corroborating evidence elsewhere, and consider you relevant enough to cite or recommend?
That last question is why GEO is broader than SEO. Your website matters enormously, but your website is only one part of the evidence an AI system may encounter about your company.
B2B buyers have always done research before talking to sales. AI is making that research faster, more conversational, and easier to do without ever visiting a vendor website.
A buyer no longer needs to search for five different phrases, open a dozen tabs, and build a comparison manually. They can ask an AI system to explain a category, identify potential vendors, compare approaches, summarize tradeoffs, suggest questions for a sales call, and then refine the answer with follow-up questions.
The behavior is already mainstream enough that it should not be treated as an edge case. Google says AI Overviews now has more than 2.5 billion monthly active users and AI Mode has surpassed one billion monthly users. Gartner found that B2B buyers used an average of seven information sources during a recent purchase, with 45% using generative AI, primarily for information about vendors and products.
For a B2B company, the pipeline implication is straightforward: if AI is helping a buyer build the shortlist before they speak with sales, your visibility inside that research process can affect whether you ever get the conversation.
This is relevant across B2B, but information-intensive, higher-consideration products and services may have even more to gain. The more questions a buyer needs answered and the more comparisons they need to make, the more opportunities there are for an answer engine or generative system to shape the decision.
The biggest mistake is treating AEO or GEO as a checklist of new tricks. The practical changes are broader and more strategic.
Important pages should answer the core question quickly and plainly before expanding into nuance. That doesn't mean turning every page into an FAQ but rather reducing the amount of work a search engine or language model has to do to understand your point. Clear definitions, explicit comparisons, descriptive headings, well-labeled tables, and concise summaries all help.
A page that mentions a phrase repeatedly is not the same thing as a company demonstrating expertise. Build connected coverage around the questions buyers actually ask, the tradeoffs they evaluate, the use cases they care about, and the language they use. Good AI search optimization makes the relationship between your company, your expertise, your category, and the buyer problem easier to understand.
Generic content is easy to reproduce and hard to justify citing. Original research, proprietary data, first-party experience, expert commentary, useful frameworks, clear definitions, practical examples, and a defensible point of view create stronger reasons for another source, human or machine, to reference you.
This is one of the most important differences between a narrow SEO mindset and a broader GEO strategy. What other credible sources say about you matters. Digital PR, relevant media coverage, industry publications, expert mentions, partner pages, reviews, community discussions, video, podcasts, and other third-party references can help validate that your company is a real and credible entity. You cannot build all of your authority by publishing more claims about yourself on your own domain.
AI systems shouldn't have to guess what you sell, who you serve, how your products relate to one another, or why your company is relevant to a category. Consistent naming, clear product and service descriptions, structured data where appropriate, strong About and author information, and consistent third-party references all reduce ambiguity.
Rankings and organic traffic still matter, but they no longer tell the whole story. A useful AI-search scorecard should also look at whether you appear in answers, how often you appear relative to competitors, the sentiment and context of those mentions, whether the system describes you accurately, whether you are cited, and whether the visibility results in click-throughs or downstream pipeline.
Because AEO and GEO are still new enough to attract hype, it's easy to overcorrect. A few common reactions are more likely to waste time than improve visibility:
AI can absolutely help research, draft, restructure, and optimize content. But using AI to produce more undifferentiated content is not a GEO strategy. If anything, the ability to generate average content cheaply makes original expertise, strong opinions, proprietary data, and real-world credibility more valuable.
Start with the data you already have before buying anything new.
Google has begun giving site owners more direct visibility into generative search. Search Console now includes a Generative AI performance report for supported Search features, including AI Overviews and AI Mode, showing impressions by page and other dimensions. Google also counts clicks from AI Mode and AI Overviews as Search Console clicks under its standard reporting rules.
That is an improvement, but measurement is still immature. Google reporting only covers Google. ChatGPT, Claude, Perplexity, Gemini, and other systems have different levels of referral visibility and no universal reporting standard. Even where you can detect a citation or referral, connecting it cleanly to a closed B2B deal can be difficult.
You may also see odd patterns in your broader search data before you can confidently explain them. On our own site at 10cubed, we have seen pages generate patterns of impressions, low click-through, unusual average-position behavior, and long conversational queries that do not look like classic keyword search. Those patterns are worth investigating, but they are not enough on their own to claim that a particular impression came from an AI Overview or AI Mode.
There's no single perfect GEO metric yet. For B2B teams, a combination of measures is more useful than trying to invent one magic score.
The important part is to avoid false precision. GEO attribution is still messy. A prospect may discover you in ChatGPT, search your name on Google, read three pages on your site, return through a direct visit two weeks later, and then book a call. Your analytics may credit the conversion to branded organic search or direct traffic even though generative AI influenced the shortlist.
You don't need to rebuild your website or buy a pile of new software to start. A small B2B marketing team can learn a lot in 30 days by focusing on one important buying question and one important page.
Don't start with every page on the site. Start where AI visibility could realistically influence a buying decision.
For lean teams, that;s usually a better use of time than trying to GEO-optimize hundreds of old blog posts.
If there is one idea worth taking away from this article, its that GEO isn't simply an on-page optimization discipline.
An AI system trying to answer a buyer question may encounter your own website, but it may also encounter news coverage, analyst content, review sites, partner pages, industry publications, forums, videos, podcasts, social content, and other sources that either reinforce or contradict the story you tell about yourself.
That means brand authority and third-party validation are not nice-to-have extras around the edges of GEO. Strategically, they are part of the work.
This is also why the companies that approach GEO as "SEO for ChatGPT" are likely to miss a large part of the opportunity. You can optimize the page perfectly and still lose the recommendation if the broader information environment gives the model stronger evidence for someone else.
The point of AEO and GEO isn't to collect AI citations like trophies. For a B2B company, the work should ultimately improve your ability to enter and influence buying journeys.
A citation matters because it can establish authority. A recommendation matters because it can put you on the shortlist. A click matters because it gives you an opportunity to continue the conversation on your own site. Accurate brand representation matters because buyers may form an opinion about you before you ever know they exist.
That is the business case for AI search optimization. Not that every buyer suddenly abandoned Google. Not that SEO is dead. And not that you need a brand-new marketing department dedicated to a pair of acronyms.
It is that the systems buyers use to research their options are changing, and B2B marketers need to make sure their companies remain visible, understandable, credible, and recommendable inside those systems.
If your SEO fundamentals are weak, fix those. If your content does not demonstrate expertise, improve it. If the only evidence that your company is credible exists on your own website, invest in authority beyond your domain. Then start measuring how your brand appears in the answer environments your buyers increasingly use.
At 10cubed, we approach Search & AI Engine Optimization as part of a broader B2B growth system, connecting technical SEO, content, authority building, AI visibility, and measurement to the outcome that actually matters: pipeline.
If you want a second opinion on how your company currently appears in AI search, what the data is telling you, and where the highest-leverage opportunities are, contact 10cubed.
Jake Finkelstein is the Founder and CEO of 10cubed, a Durham, NC-based digital marketing agency helping B2B companies grow through strategy, AI, and automation. A veteran B2B marketer and demand generation specialist, he has spent more than 20 years helping growth-stage and enterprise brands build pipeline, drive revenue, and operationalize modern marketing programs.
