SEO vs AEO vs GEO: What Actually Changed

The marketing industry loves new acronyms. First it was SEO. Then came AEO. Now someone decided we needed GEO too. Every agency claims to be an expert in all three, and most B2B companies are left wondering if this is real or just repackaged consulting fees.

Here’s my take after spending the last few months building SANscript’s own AI visibility: some things genuinely changed. The tactics evolved. The principles stayed the same. And the difference matters if you’re trying to figure out where to actually spend your time and budget.

The Real Question Nobody’s Asking

Before we dive into SEO vs. AEO vs. GEO, ask yourself this: when was the last time you researched a vendor without checking Reddit, asking ChatGPT or Claude, or looking at AI Overviews before clicking through?

That shift isn’t coming. It already happened.

I’ve been vetting vendors on Reddit for five years. When I need a contractor, I don’t start with Google ads. I search Reddit for honest takes, check what shows up in Google’s AI Overview or ask Claude, and then visit websites to verify details. That’s the buyer journey now, and companies who aren’t showing up in those AI-powered touchpoints are invisible during the research phase that actually matters.

The terminology debate misses the point. Call it whatever you want. The behavior changed, and your content strategy needs to catch up.

What SEO, AEO, and GEO Actually Mean

SEO (Search Engine Optimization): Making your website rank in Google search results. You optimize for keywords, build backlinks, fix technical issues, and try to land on page one. This has been the default since the late 90s.

AEO (Answer Engine Optimization): Optimizing for AI platforms that answer questions directly. Think ChatGPT, Claude, Perplexity, Gemini, and Google’s AI Overviews. Instead of giving you ten blue links, they give you an answer with sources cited. Your goal is to be one of those sources.

GEO (Generative Engine Optimization): Essentially the same as AEO but focused specifically on how generative AI creates answers. Some people split hairs between these terms. In practice, the tactics overlap because both need the same foundation:

Structured, crawlable content – Whether Google’s featured snippets or ChatGPT’s citations, clean HTML and semantic markup matter
Third-party validation – Both weight reviews, forum discussions, and industry publications more than your own marketing claims
Comprehensive information – Thin content doesn’t get cited by answer engines OR generative AI
Transparent details – Pricing, specs, documentation visible without gatekeeping
Authority signals – Site age, backlinks, domain trust still matter across all platforms

The main difference is source diversity. Traditional answer engines relied heavily on your on-page optimization. Generative AI pulls more from community discussions (Reddit, forums, LinkedIn) and synthesizes across multiple sources. But you’re ultimately doing the same work: publish substantial content, build third-party trust, make information accessible.

The Backlinko team (in their comprehensive guide on AI search strategy calls this the “Seen & Trusted” framework. You need to be both mentioned in AI answers (seen) and cited as a source (trusted). Get one without the other and you’re leaving opportunity on the table.

A quick note on Claude: If you’re only optimizing for ChatGPT, you’re missing a huge piece of the puzzle. After some recent government pushback, Claude shot to #1 in the app store, dethroning ChatGPT. A lot of people switched or started using both. Claude, Gemini, Perplexity, and AI Overviews all pull from different (though overlapping) sources. You can’t ignore any of them.

How AI actually finds information: LLMs use information retrieval (IR) systems to pull relevant content before generating answers. Think of it like a two-step process: first the IR system searches and ranks potential sources, then the LLM synthesizes an answer from those sources. Different platforms use different IR approaches, which is why you might appear in one AI’s results but not another’s. The fundamentals are the same though: clean structure, substantial content, third-party validation.

What Actually Changed

Let me be direct: content became way more important. Not “content marketing is good for SEO” important. More like “without substantial content, you don’t exist to AI systems” important.

Here’s what’s different now:

AI systems need context to cite you. Google could rank your homepage based on backlinks and domain authority. ChatGPT and Claude need actual information to pull from. If your site is five pages of marketing copy and a “Contact Us” form, there’s nothing to cite. (This was SANscript until recently – we had to build out substantial content before AI platforms had anything to reference.)

Third-party mentions matter more than your own claims. AI platforms treat Reddit threads, G2 reviews, and industry publications as more trustworthy than your website. When someone asks ChatGPT about manufacturing software, it’s citing customer reviews and forum discussions, not your feature list.

Transparency wins over gatekeeping. Remember when everyone hid pricing behind “Request a Demo”? That worked when buyers had to talk to you eventually. Now AI just cites whoever actually published their pricing. If you don’t, you risk being described as “expensive” based on Reddit speculation instead of facts.

Your documentation becomes your best SEO. The companies winning AI visibility aren’t the ones with the best homepage. They’re the ones with comprehensive support docs, detailed integration guides, and actual answers to technical questions. AI loves that stuff.

Community presence compounds fast. One helpful Reddit comment doesn’t move the needle. Fifty comments over six months where you’re actually solving problems? That becomes the foundation of how AI describes your company.

None of this is magic. It’s just more work than old-school SEO required.

What Hasn’t Changed (And Why That Matters)

Site authority still matters. Wikipedia still dominates AI citations. If you’re trying to rank for “precision machining” and your competitor has been publishing for ten years while you launched last month, they have an advantage – for now. But algorithms change, new platforms emerge, and consistent effort compounds. You’re not locked out forever. You just need realistic expectations about timelines.

E-E-A-T still matters. Google’s framework – Experience, Expertise, Authoritativeness, Trustworthiness – predates AI search, but it’s more relevant than ever. AI systems evaluate these same signals when deciding which sources to cite. Demonstrable experience (real case studies, not hypotheticals), documented expertise (credentials, certifications), third-party authority (backlinks, mentions), and established trust (reviews, longevity) all influence whether ChatGPT, Claude, or AI Overviews cite you as a source.

Technical SEO fundamentals haven’t changed either. If your site is slow, has broken links, or hides content behind JavaScript that AI crawlers can’t read, you’re invisible. All the Reddit engagement in the world won’t fix that.

The biggest thing that hasn’t changed? It’s still a long game. SANscript published consistently for a couple of months before we started showing up in AI Overviews. Perplexity found us before the major platforms did. We had to build actual authority through real content that answered real questions.

Any agency promising instant AI visibility is selling the same BS they used to sell with “first page in 30 days” SEO guarantees.

Bonus: The Accessibility Connection

Here’s something the Backlinko framework touches on but doesn’t emphasize: accessibility fixes often help AI visibility as a side benefit.

Why? Because the things that help screen readers also help AI systems parse your content.

Clean HTML structure. When you use proper heading tags (H1, H2, H3) instead of just styling text to look big, screen readers can navigate your page. AI systems can too. They understand hierarchy and can extract the information they need.

Semantic markup. Properly marked-up tables, lists, and data structures help assistive technology. They also help AI understand what information you’re presenting and how to cite it accurately.

Fast load times and minimal JavaScript. Pages that work well for users with cognitive disabilities also work well for AI crawlers. Heavy JavaScript that delays content rendering hurts both.

Alt text done right. Descriptive image alt text helps vision-impaired users. It also gives AI context for understanding diagrams, product photos, and technical illustrations.

The overlap isn’t 100%, but it’s substantial. Companies who fix accessibility issues often see improved AI visibility as a side benefit. That’s not a coincidence.

What This Means for B2B Companies

If you’re running a B2B operation with a limited marketing budget, here’s my honest recommendation: focus on both, but prioritize differently based on where you are.

If you have zero web presence: Start with SEO fundamentals. Get your site fast, technically sound, and structured correctly. You can’t win AI visibility if your site isn’t even crawlable.

If you have a decent site but low traffic: Start creating content that answers real questions. Not “Why Choose Us” pages. Actual technical documentation, comparison guides, and implementation details. This serves both SEO and AEO. (For example, if you’re a manufacturer, publish your technical specs on web pages – not just PDFs that AI can’t easily parse. If you’re a SaaS company, document your API. If you’re a service provider, create detailed process guides.)

If you’re already publishing but not seeing AI citations: Look at where the conversations about your industry are happening. Reddit? Industry forums? LinkedIn? That’s where you need to be, answering questions and building the third-party presence AI systems trust.

If you have good content but hidden information: Publish your pricing. Document your processes. Make your support knowledge base public. Transparency builds trust with both humans and AI systems.

The companies winning AI visibility aren’t choosing between SEO and AEO. They’re doing both because the fundamentals overlap more than the acronyms suggest.

The Long Game (What We’re Learning in Real Time)

I’m going to be transparent about timelines because I think the industry needs more honesty about what “success” actually looks like.

SANscript has been publishing consistently for a few months. Articles about accessibility, search optimization, and B2B marketing. LinkedIn engagement. Detailed service descriptions. Following the “Seen & Trusted” framework from Backlinko and applying proven SEO fundamentals to AI platforms.

What’s working:

We show up in AI Overviews for niche accessibility and search optimization queries
Perplexity found us as sanscript.agency
Our LinkedIn content gets engagement from our target audience
We’re building authority in our specific niche
We’re tracking what works and iterating quickly

This aligns with traditional SEO timelines. Most experts will tell you 3-6 months for meaningful traction. AI visibility follows similar patterns – consistent execution, proven frameworks, realistic expectations.

The lesson isn’t “be patient and it magically works.” The lesson is consistent work compounds, proven frameworks accelerate results, and nobody wins this overnight.

We’re following established strategies, tracking metrics, and seeing progress. This is a new frontier, but the fundamentals that worked for SEO still apply to AI visibility.

What This All Means

Understanding SEO, AEO, and GEO helps you see how search evolved. The terminology isn’t just marketing speak – it reflects real shifts in how buyers find information.

What changed: AI platforms need more content, trust third-party sources more than your claims, and reward transparency over gatekeeping.

What didn’t change: Authority still matters, technical fundamentals still matter, and it’s still a long game that rewards sustained effort.

What most agencies won’t tell you: You can’t just “optimize for AI” as a one-time project. This is ongoing work across multiple channels — your website, review platforms, community forums, and industry publications.

The companies winning AI visibility are the ones treating it like a marathon, not a sprint. They’re publishing real content, engaging in real communities, and building real authority.

The ones who lose are waiting for the “AI SEO hack” that makes this easy.

There isn’t one. There never was with traditional SEO either.

Focus on being helpful, transparent, and consistently present where your buyers are researching. That worked before AI, and it works now. The channels changed. The fundamentals didn’t.