AI Optimization Framework: How GEO and AEO Work Together

An AI optimization framework splits brand visibility in AI systems into two jobs. Answer Engine Optimization (AEO) gets your pages retrieved and cited when an assistant searches the web. Generative Engine Optimization (GEO) shapes what models learn during training. AEO moves faster, GEO lasts longer, and the right mix depends on where your brand is missing today.

What does an AI optimization framework cover?

AI Optimization (AIO) covers everything that decides whether ChatGPT, Gemini, Claude, Perplexity, Microsoft Copilot, and Google AI Overviews mention your brand when buyers ask about your category. A working framework has three layers: technical access, retrieval, and training influence.

Technical access comes first because it gates the other two. If AI crawlers cannot read your site, nothing you publish there can be retrieved, and less of it can end up in training data. Retrieval is AEO: the pages an assistant finds and cites when it runs a live search. Training influence is GEO: the descriptions of your brand that a model absorbed from Wikipedia, Reddit, Quora, trade publications, and the wider web before it was released.

The reason to run these as one framework instead of two programs is that the same assets feed both. A review of your product on an industry publication can be retrieved and cited this week, and that same page may be collected for a future training run. Teams that split GEO and AEO into separate silos tend to pay twice for the same outreach, or leave gaps where each assumes the other is handling it.

How do GEO and AEO differ in practice?

AEO targets what an assistant finds right now, so changes can show up as soon as search indexes update. GEO targets what a model already believes, so changes only appear after a new model version is trained and released, on a schedule you do not control.

Layer	What it influences	Where the work happens	How fast changes show	Usual owner
Technical access	Whether AI crawlers can read your pages	robots.txt, CDN and firewall settings, site rendering	Days	SEO or web team
AEO	Which pages get retrieved and cited during live search	Your site, review sites, roundups, comparison articles	Weeks	SEO and content
GEO	What the model says without searching	Wikipedia, Reddit, Quora, publications, analyst coverage	Months or longer, unpredictable	PR, comms, community

You can see the split directly in how crawlers are named. OpenAI uses GPTBot to collect training data and OAI-SearchBot to fetch pages for ChatGPT search. Google uses the Google-Extended token to control whether your content can be used for Gemini model training, separately from Googlebot, which feeds Google Search and AI Overviews. A brand can opt out of training while staying retrievable, or allow both. Your framework should make that choice on purpose, because a blanket block cuts off both levers at once.

How do you tell which gap you have?

You find the gap by sampling answers. Write down the questions your buyers actually ask, run each one several times across the major assistants, and record whether you appear and which pages get cited. AI answers vary with phrasing, context, model version, and chance, so a single run tells you almost nothing. What matters is how often you show up across many runs.

Then read the pattern. Answers that include cited links reflect retrieval. Answers that arrive without any links usually come from what the model learned in training. Comparing the two tells you which lever is broken.

What you see	Likely gap	First move
You are missing even from answers that cite sources	AEO, possibly crawler access	Check crawler access, then study the cited pages and get onto them
You appear in cited answers but rarely in answers without links	GEO	Build presence in the sources models train on
Assistants describe you with old pricing, a former name, or retired products	Training lag	Correct third-party sources and publish clear current pages for retrieval
Competitors show up through roundup articles that omit you	AEO through third parties	Pitch the publishers of those roundups
Assistants put you in the wrong category	Both	Use one consistent category description everywhere

The third row deserves attention. When a model repeats outdated facts about you, fixing your own site helps retrieval-based answers quickly but does nothing for the training-based ones until a newer model ships. You need both moves at the same time.

When should AEO come first?

Prioritize AEO when your brand is new, when your product has changed recently, or when you need results within a quarter. Models trained before your launch cannot know you exist, so retrieval is the only path into answers until newer models catch up.

Try this with a real category. Ask Perplexity for the best payroll software for a restaurant with hourly staff, then open every cited source. You will typically see review platforms, listicles from small business publications, and a few vendor pages. Those cited pages are your AEO target list. If you sell payroll software and appear on none of them, no amount of homepage work will change the answer.

AEO work falls into three buckets. Make your own pages easy to quote, with direct answers near the top, clear comparison pages, and specific facts like supported integrations. Get included in the third-party pages that already get cited. And make sure your site is indexed well in both Google and Bing, because assistants retrieve from search indexes. Structured data helps search engines understand your pages, which supports retrieval, but no markup guarantees a citation.

When should GEO come first?

Prioritize GEO when you are an established brand that shows up in cited answers but disappears when models answer from memory, or when your buyers ask open-ended questions that assistants often answer without searching. Questions like "what should I look for in a CRM for a nonprofit" frequently get answered from training knowledge, and the brands named there are the ones the model has seen discussed repeatedly.

GEO work is slow and relationship-driven. It means earning a Wikipedia article if your company genuinely meets notability guidelines, participating honestly in the Reddit and Quora threads where your category gets discussed, landing coverage in trade publications, and getting cited in analyst reports and long-running comparison articles. Each mention adds to the pattern a future model will learn.

Be honest with stakeholders about timing. Nobody outside the AI labs knows exactly when the next training run happens, what data it includes, or how heavily a given source is weighted. GEO is a bet on accumulated presence, and the payoff arrives on an unknown schedule.

How should you split effort between GEO and AEO?

Lead with whichever gap your diagnosis showed, and run a smaller amount of the other in parallel. The split shifts as your brand matures: newer brands lean heavily on AEO, while established brands with outdated or missing training-based mentions shift toward GEO.

Situation	Lead with	Run alongside	Why
New brand or new category	AEO	Light GEO through early press and community	Models trained before launch cannot know you
Established brand, outdated AI descriptions	GEO and AEO together	Technical cleanup	Retrieval fixes current answers, training fixes future ones
Consumer category with heavy forum discussion	GEO	AEO on review sites	Forums shape both training and live retrieval
Local service business	AEO	Directory and review consistency	Local queries usually trigger live search
B2B with long sales cycles	AEO on comparison content	GEO through analysts and trade press	Buyers research with search on, but trust named authorities

The budget lines differ too. AEO spending mostly shows up as content and SEO hours. GEO spending shows up as PR retainers, community management time, and event or analyst relationships. When you plan, look for work that serves both. A well-placed guest article on a respected publication can be cited in live answers now and absorbed into training later, so it usually earns more than a piece built for one lever alone.

How does AIO fit into your existing marketing operations?

AIO works best when it is assigned to the teams that already own the relevant channels, with one person coordinating. Very few companies need a new department for it.

SEO team: Owns crawler access, indexing, and AEO on your own site.
Content team: Writes answer-first pages and comparison content built to be quoted.
PR and comms: Owns GEO through publications, analysts, and Wikipedia accuracy.
Community or social: Handles honest participation on Reddit, Quora, and industry forums.
Product marketing: Keeps category language and product facts consistent across every channel.

Reporting needs adjusting because AI answers cannot be tagged to report back to you. What you can measure is how often you appear across sampled prompts and which pages get cited, plus referral visits in your analytics from sites like chatgpt.com and perplexity.ai when people click a cited link. nonBot AI runs your buyers' questions across ChatGPT, Gemini, Perplexity, Claude, and Google AI Overviews and shows where you appear, which pages get cited, and whether AI crawlers can read your site. Review those numbers monthly alongside your SEO reporting so the same people see both.

Mistakes that cost the most

Treating one screenshot as a rank: An executive sees the brand missing from a single ChatGPT answer and orders a rewrite. Answers vary from run to run, so decisions based on one sample waste effort chasing noise.
Blocking AI crawlers by accident: Some CDN and security settings block AI crawlers by default. A site can quietly disappear from retrieval for months before anyone checks.
Astroturfing forums: Fake Reddit accounts get spotted, banned, and called out. The resulting threads about your brand's behavior can outlast the posts themselves and become part of what models learn.
Expecting schema to buy citations: Structured data helps indexing. It does not change what a model learned, and it cannot force an assistant to quote you.
Editing your own Wikipedia page: Conflict-of-interest edits get reverted and can draw scrutiny to the article. Correct errors through talk pages and independent sources instead.
Rewriting only the homepage: Most citations go to specific pages, often third-party ones. Homepage copy rarely moves either lever.

What to do this week

Start with a diagnosis you can finish in a few hours.

Write down the questions your buyers ask before they contact sales, using their wording.
Run each question several times in ChatGPT, Perplexity, Gemini, Claude, and Google, and record whether you appear and which URLs get cited.
Check your robots.txt and CDN settings for GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot, and Google-Extended, and confirm the rules match what you intend.
Sort what you found into the gap table above.
Pick one AEO target and one GEO target and assign each an owner.

Your first AEO target should be the single most-cited third-party page in your category that leaves you out. Find its author and send a specific, useful pitch before Friday.

FAQ

How long does GEO take to show results?

There is no reliable answer, because results depend on when AI companies train and release new models, and they do not publish those schedules. Expect months at minimum. Track training-based answers over time and treat any improvement as a lagging signal of work done well before it.

Do I need separate content for AI assistants and Google?

Usually not. Pages that answer questions directly, state specific facts, and are well indexed serve Google Search, AI Overviews, and assistant retrieval at the same time. The bigger difference is off-site, since AI answers lean on third-party sources more than a traditional results page does.

Should I block AI crawlers to protect my content?

Decide crawler by crawler. Blocking training crawlers like GPTBot limits future GEO influence, while blocking search crawlers like OAI-SearchBot or PerplexityBot removes you from live answers. Many brands allow search crawlers even when they restrict training, because being cited sends visitors.

Is optimizing for one assistant enough?

No. Each assistant searches differently and relies on training to a different degree, so your visibility can vary widely between them. Prioritize the assistants your buyers use most, but sample all of them so you catch gaps before customers do.