SEO Is Not Dead. It Just Has Two New Roommates: AEO and GEO

The SEO industry is facing new challenges.

Story of my life.

Some of the challenge is not new at all. Google has been pushing organic results farther down the page for years. First it was more ads. Then came featured snippets, People Also Ask, knowledge panels, maps, shopping modules, video carousels, and enough SERP furniture to make the traditional “10 blue links” feel like a historical artifact.

Now we have AI Overviews.

Google says AI Overviews and AI Mode are designed to help people get the gist of complicated questions faster, while still surfacing links for exploration. Google also says the same basic SEO best practices still apply and that there are no special technical requirements for appearing in these AI experiences beyond being eligible for Search and snippets.¹

That is both reassuring and slightly annoying.

Because “just keep doing good SEO” is true.

It is also incomplete.

The search page itself has changed. Visibility no longer guarantees traffic. Ranking does not always mean the click. And the buyer’s first impression may now be formed by a summary, not a page visit.

The newer challenge is bigger: discovery itself is becoming AI-mediated. As I argue in B2B Marketing in the AI Era, buyers increasingly learn through AI assistants and AI search layers that summarize, compare, and recommend before a prospect ever reaches your site.² ChatGPT, Gemini, Perplexity, Claude, and other AI-assisted experiences do not behave like traditional search engines. They do not just retrieve links. They shape the first draft of the buyer’s understanding.

That does not mean SEO is dead. SEO has been declared dead more times than most B2B marketing dashboards have been “replatformed.”

It means SEO has expanded.

The modern discoverability problem now has three layers:

Search Engine People framed the distinction clearly: SEO is about optimizing for traditional search engines, AEO is about optimizing for answer engines and single-answer environments, and GEO is about optimizing for AI-powered systems such as ChatGPT, Gemini, and Perplexity. Their conclusion is the right starting point: GEO and AEO are not replacing SEO. They are expanding it.³

The practical question for marketers is not, “Which acronym wins?”

The practical question is:

Where should we invest when clicks are less guaranteed, answers are more compressed, and trust signals matter more than ever?

What Changed: Discoverability Is No Longer Just Search Visibility

For years, discoverability mostly meant ranking well in Google.

If buyers searched the right terms and your pages appeared near the top, you had a reasonable shot at earning the click. That model is still alive, but it is no longer complete.

Discoverability now happens across a wider set of surfaces: traditional search results, AI Overviews, answer boxes, voice-style responses, AI assistants, review sites, social feeds, communities, partner ecosystems, and direct brand mentions.

Buyers are not always discovering companies by clicking through a list of links. Increasingly, they are discovering through summaries, recommendations, comparisons, and synthesized answers.

That changes the marketing job.

The question is no longer only:

Can we rank?

The better question is:

Can we be found, understood, trusted, and recommended wherever the buyer is forming an opinion?

That is where SEO, AEO, GEO, and Proof Ops connect.

SEO helps you appear in search.

AEO helps you become the answer.

GEO helps you appear accurately in AI-generated summaries and recommendations.

Proof Ops gives those systems, and the buyers using them, credible evidence to work with.

In the AI era, discoverability is not just visibility. It is visibility plus interpretation. You are not only trying to show up. You are trying to show up correctly.

That is also the argument I make in B2B Marketing in the AI Era: AI did not merely make marketing faster. It changed how buyers learn, how markets remember, and how organizations decide. Buyers now arrive with points of view already forming, often assembled from AI summaries, stitched comparisons, and recommendations delivered before anyone visits your website or talks to your team.²

That means modern discoverability has to answer four questions:

That last one is the killer.

In AI-mediated discovery, your company may be summarized before it is visited. If the summary is wrong, vague, or missing proof, you are not just losing traffic. You are losing the frame.

The Search Page Is Becoming an Answer Layer

For years, the implicit bargain of SEO was simple: create useful content, rank well, earn clicks, and convert a portion of those visitors.

That bargain is under pressure.

Pew Research Center analyzed Google browsing behavior from March 2025 and found that users who encountered an AI summary clicked a traditional search result in 8% of visits, compared with 15% of visits when no AI summary appeared. Users clicked links inside the AI summary itself in only 1% of visits.⁴

That is a big deal.

Not because every query is suddenly zero-click. It is not.

But because the old assumption – ranking equals traffic – is becoming less reliable.

Semrush’s 2025 AI Overviews study found that AI Overviews appeared for 6.49% of tracked keywords in January 2025, peaked near 25% in July, and settled around 15.69% in November. More importantly, the types of queries triggering AI Overviews expanded beyond purely informational searches into commercial, transactional, and navigational territory.⁵

Translation: this started in the “what is X?” zone, but it is moving closer to “which vendor should I consider?” territory.

For B2B marketers, that is where things get spicy.

Top-of-funnel content was always easy to overvalue. It made dashboards look healthy. It filled attribution reports. It gave everyone the warm feeling of “educating the market,” which is often marketing-speak for “we got traffic but have no idea whether it mattered.”

AI search makes that weakness more visible.

If your content only answers generic questions that an AI system can summarize in two paragraphs, you may still be useful, but you may not get the visit.

That does not mean the content has no value. It may train, inform, or influence the answer layer.

But it does mean the measurement model has to change.

SEO, AEO, and GEO Are Different Outcomes, Not Different Universes

The mistake is treating SEO, AEO, and GEO as three separate strategies.

They are not.

They overlap heavily. Clean structure, helpful content, schema, technical crawlability, topical authority, brand consistency, expert authorship, credible third-party validation, and clear proof all matter across the three.

But the desired outcome is different.

SEO wants the page to rank.

AEO wants the answer to be extracted.

GEO wants the brand, concept, or source to be included accurately in the generated response.

That difference matters because it changes how content should be built.

Traditional SEO often rewarded depth, keyword coverage, internal linking, backlinks, and strong page experience. Those still matter.

AEO rewards crisp, answerable passages.

GEO rewards clarity, credibility, specificity, freshness, consistency, and corroboration across sources.

In other words, the machine needs to understand you, trust you, and find enough supporting evidence elsewhere to include you without feeling like it is taking a flyer on some random marketing page.

And yes, this is where marketing gets uncomfortable.

Because the answer is not:

Publish 40 more blog posts with slightly different H2s.

The answer is:

Become more credible.

Rude, but fair.

This is why discoverability has to be managed as an ecosystem, not a channel. A buyer may first encounter your category in an AI answer, validate you through a review site, check your Trust Center, ask a peer, and only then search your brand directly.

If you only measure the final click, you miss the system that created the decision.

Start by Segmenting Keywords by Search Behavior

Not every keyword deserves the same strategy.

Search Engine People makes an important point: some searches are less likely to trigger AI answers. Local and service-based queries often behave more like a digital Yellow Pages experience. If someone searches for “plumber near me” or “managed IT services Boston,” they are usually looking for a provider, not a lecture on the history of pipes or endpoint management.³

That means marketers should stop treating the keyword universe as one big spreadsheet of interchangeable opportunities.

Segment it like this:

This is where the operator work starts.

Do not ask only:

What keywords have volume?

Ask:

• Which keywords can still produce qualified visits?
• Which ones are likely to be answered without a click?
• Which ones influence how buyers frame the category?
• Which ones need third-party proof before an AI system or buyer will trust the answer?
• Which ones are tied to revenue, not just traffic?

If resources are limited, prioritize the keywords closest to buying intent and category framing.

Top-of-funnel content still matters, but generic educational content is no longer the safest place to hide.

On-Page Work: Make Your Content Easy to Extract, Cite, and Trust

On-page SEO is still the foundation.

Google’s own guidance says SEO fundamentals remain relevant for AI features in Search. Pages still need to be crawlable, indexable, technically sound, and useful.¹

But the structure has to evolve.

For AEO and GEO, your content should include concise answer blocks, clear definitions, comparison tables, FAQs, schema markup, author credentials, update dates, and strong internal links to supporting proof.

A good AI-era page should do three things quickly:

1. Answer the question clearly.
2. Explain why the answer should be trusted.
3. Point to evidence that supports the claim.

That means fewer vague claims like:

We help companies transform their growth with AI-powered solutions.

And more specific claims like:

We help B2B marketing teams identify which search queries are still likely to produce clicks, which are more likely to produce AI summaries, and which require proof assets such as case studies, third-party mentions, comparison pages, or implementation guides.

One is a brochure sentence.

The other gives a machine, and a buyer, something to work with.

The same principle applies to content formatting. Use short answer sections. Use descriptive H2s. Include examples. Define terms. Use tables where useful. Add schema where appropriate. Keep pages updated. Make authorship visible.

The goal is not to “write for robots.”

Please do not do that. We have enough robot-adjacent writing already.

The goal is to write for humans in a way that machines can parse accurately.

Off-Page Work: Authority, Experience, and Trust Are the Hard Part

The most important AI-era SEO work may not happen on your website.

Search Engine People’s conclusion lands on three words that should matter to every marketer:

Authority. Experience. Trust.

They argue that these are the hardest areas to build, which is exactly why they deserve focus.³

I agree.

Most on-page recommendations can be implemented by a competent marketer with a CMS, a schema plugin, and enough caffeine.

The hard part is proving that your company deserves to be believed.

That is off-page work.

It includes backlinks, yes. But it also includes brand mentions, analyst references, review sites, communities, podcasts, YouTube, LinkedIn, partner pages, customer stories, third-party directories, and credible niche publications.

In an AI-mediated discovery world, the web around your website matters.

A generative answer does not only look at what you say about yourself. It looks for corroboration.

That means your proof surface needs to expand.

For B2B companies, off-page authority should include:

This is where SEO becomes a company-wide operating system.

The content team cannot fake authority on its own. Demand gen cannot buy experience. Product marketing cannot invent trust after the fact.

Customer success, sales, product, security, and leadership all have to contribute evidence.

That evidence becomes the raw material for SEO, AEO, and GEO.

B2B Marketers Need a Proof Inventory

Here is the uncomfortable truth: most companies do not have a content problem.

They have a proof problem.

They have claims everywhere and evidence scattered nowhere.

A proof inventory fixes that.

A proof inventory is a structured library of credibility assets mapped to the way buyers evaluate a company. It should include customer stories, metrics, testimonials, implementation examples, security documentation, review snippets, analyst mentions, partner validations, product screenshots, original research, webinars, and executive points of view.

But do not just dump everything into a folder called “Sales Stuff Final FINAL.”

Tag the proof by:

• Persona
• Industry
• Use case
• Objection
• Funnel stage
• Competitor
• Product line
• Region
• Compliance or risk concern
• Business outcome

This matters because AI search compresses evaluation.

If a buyer asks, “Which platforms help B2B teams improve pipeline quality without relying on MQL volume?” the winning brand will not be the one with the most content.

It will be the one with the clearest, most credible, most corroborated answer.

That is why Proof Ops is becoming a real marketing discipline.

In B2B Marketing in the AI Era, I define Proof Ops as the operating system for credibility: the disciplined practice of capturing proof, packaging it into usable formats, organizing it so it can be retrieved quickly, and deploying it deliberately across the buyer journey.⁶

In plain English:

Stop treating proof like decoration. Start managing it like inventory.

Not more content.

Better evidence.

GEO and Proof Ops Belong Together

GEO without proof is just visibility theater.

You might get mentioned. You might even get summarized. But if the answer layer cannot verify why you belong in the shortlist, your visibility is fragile.

Proof Ops gives GEO something to work with.

It creates the structured evidence that makes your company easier to classify, easier to cite, and easier to recommend.

The deeper shift is that trust assets are becoming distribution assets.

Security pages, comparison pages, implementation guides, proof stories, FAQs, and trust centers do more than help late-stage sales. They help AI systems and skeptical buyers verify whether your company is credible enough to include, cite, recommend, or shortlist.

That is why GEO and Proof Ops belong together:

In B2B Marketing in the AI Era, I describe GEO as the discipline of making your company easy to understand and hard to misrepresent. That means defining your category clearly, stating what you are and are not, attaching proof to claims, and publishing assets that skeptical buyers and AI systems can both use.⁷

That is the operator version of GEO.

Not prompt tricks.

Not acronym bingo.

Not “we added FAQ schema, please clap.”

It is the work of building a public evidence surface around your company so both people and machines can understand you correctly.

Your Website Becomes a Verification Hub

A lot of companies still treat the website like a brochure with a demo form attached.

That is not enough anymore.

In an AI-mediated buying journey, your website has to do more than introduce the company. It has to verify the company.

Buyers may arrive with a story already in their heads, assembled from AI summaries, review sites, peer conversations, analyst content, and internal debate. When they land on your site, they are not always asking:

Who are you?

They are asking:

Are you real? Are you safe? Will this work here? Can I defend this decision internally?

That means the website needs to function as a verification hub.

A minimum viable verification hub should include:

This is not about adding pages for the sake of content volume.

It is about reducing uncertainty at the exact moments when buyers, committees, and AI systems are trying to decide whether you belong in the conversation.

Measurement Has to Change Too

Traditional SEO measurement is not going away.

Rankings, impressions, clicks, CTR, conversions, and assisted pipeline still matter.

But they are no longer enough.

AI-era visibility needs additional metrics:

Bain has argued that AI search and zero-click behavior require marketers to rethink customer acquisition because answers are increasingly delivered without site visits. Its research found that many consumers already rely on zero-click results frequently, reducing organic web traffic by an estimated 15% to 25%.⁸

For B2B, the issue is not just lost traffic.

The bigger issue is lost framing.

If AI systems summarize your category without you, compare vendors without your proof, or describe your company using stale information, you may lose before a buyer ever reaches your site.

That is why GEO is not just an SEO problem.

It is a positioning, proof, and reputation problem.

What I Would Do Now

If I were running this inside a B2B marketing organization, I would not start by forming an “AI Search Tiger Team,” because nothing good has ever come from naming a team like a failed consulting initiative.

I would start with a practical operating plan.

1. Audit your keyword universe by AI exposure

Take your current keyword set and classify each term by intent, SERP layout, AI Overview presence, local behavior, commercial value, and funnel relevance.

Do not treat all traffic loss as equal.

Losing low-intent traffic may hurt the dashboard but not the business. Losing visibility on comparison, category, or problem-aware searches is much more dangerous.

2. Rebuild priority pages for extraction and evidence

Update category pages, comparison pages, use-case pages, pricing pages, implementation pages, and “what is” explainers.

Add clear definitions, concise answers, schema, FAQs, proof blocks, author credentials, updated dates, and links to supporting assets.

Make every important page answer this question:

Why should a human buyer or AI system trust this?

3. Build a proof inventory

Inventory all customer evidence, third-party validation, reviews, implementation examples, security assets, and original points of view.

Then tag it by buyer need and search intent.

This becomes the fuel for content, sales enablement, AI visibility, analyst relations, customer marketing, and executive thought leadership.

4. Strengthen off-page authority

Earn mentions where buyers and machines look for validation.

That includes review platforms, partner pages, industry publications, podcasts, analyst notes, communities, YouTube, LinkedIn, and credible niche media.

If your only source of truth is your own website, your trust surface is too small.

5. Track AI visibility manually before buying tools

Before adding another platform to the martech junk drawer, manually test your most important prompts across ChatGPT, Gemini, Perplexity, Claude, and Google AI Overviews.

Ask questions buyers would actually ask:

• “Best tools for…”
• “Alternatives to…”
• “How do I solve…”
• “What should I consider when buying…”
• “Compare [your company] vs [competitor]”
• “Who helps companies with…”

Record whether you appear, how you are described, which sources are cited, what competitors appear, and what proof is missing.

Then decide whether tooling is needed.

Radical, I know.

The Real Shift: From Traffic Acquisition to Trust Distribution

SEO used to be mostly about traffic acquisition.

That world is not gone, but it is shrinking in some areas and changing in others.

The next version is about trust distribution.

Can your company be found?

Can your answer be extracted?

Can your brand be cited?

Can your claims be verified?

Can your market reputation survive compression into a three-paragraph AI summary?

That is the work.

SEO still matters. AEO matters. GEO matters. But the companies that win will not be the ones chasing every acronym like a squirrel on espresso.

They will be the companies that make themselves easy to understand, easy to verify, and hard to misrepresent.

Which, inconveniently, is what good marketing should have been doing all along.

References

Photo by Johannes Blenke on Unsplash