This article was written with the assistance of an AI writing program and was researched, fact checked and edited by the SearchAxe team.

Some quick definitions so the split makes sense. SEO is ranking pages in classic Google and Bing results. GEO, or generative engine optimisation, is getting your brand named and cited inside answers from ChatGPT, Perplexity, Gemini and Google AI Overviews. AEO is the narrower craft of shaping a page so an engine can lift a direct answer from it.

Why does the split matter for a SaaS team right now?

It matters because the two channels reward different work, and most teams assign all of it to one person who optimises for rankings. The data from 2026 makes the gap hard to ignore.

In a June 2026 panel of 100 commercial B2B software queries, DerivateX found that 67.4% of sources cited in Google AI Overviews did not appear in the organic results for the same query. Citera, looking at roughly 350,000 B2B SaaS articles across 52 categories, found that only 14% of AI cited URLs also sat in Google's top 20.

So a team that ships good SEO and stops there is measuring one channel and guessing about the other. A team that chases GEO tactics on a weak domain gets very little back. The fix is not a new hire for every acronym. It is a clear owner for each layer and a shared baseline.

What should engineering own?

Engineering should own everything that decides whether a crawler or an AI engine can read and trust your site. That is classic technical SEO, and it is still the base layer for AI visibility.

The strongest evidence comes from a large arXiv study this year covering around two million citations from ChatGPT, Claude, Google AI and Gemini across 10,000 pages from B2B SaaS workspaces. Domain level authority outweighed the strongest non alignment page feature by roughly six times. Engines cite domains they already trust, and trust starts with a site that works.

Here is the engineering backlog we would hand over first.

1. Indexation hygiene. Make sure the pages you want cited are indexable, canonicalised correctly and listed in your sitemap. Check that marketing pages are not hidden behind client side rendering a crawler skips.
2. Clear site architecture. Product, use case, comparison and docs pages should each have a predictable home. Engines and people both struggle with marketing sites where the same feature is described on six different URLs.
3. Accurate schema. Use structured data to describe your organisation, product and capabilities plainly. Treat it as a way to be described correctly, not as a citation trick.
4. Fast, stable pages. Keep Core Web Vitals healthy because users and search engines care, while knowing it is not a GEO lever on its own.

That last point needs honesty. The same arXiv study found that FAQ blocks, structured data and Core Web Vitals showed effects that collapsed to roughly zero once domain differences were controlled for. Engineers should still do this work, but nobody should promise that adding schema will put you inside ChatGPT answers.

What should content and growth own?

Content and growth should own prompt alignment, citation ready writing and off site presence. These are the parts of GEO that classic SEO rarely plans for.

Prompt alignment. The arXiv study found that the strongest page level predictor of citations was how closely a page's language matched the prompts buyers type. Keyword research shows what people search. Prompt research shows what they ask. A buyer typing "best accounts receivable software for a 50 person finance team" needs a different page from someone searching "AR automation".

Citation ready writing. Citera found AI cited B2B SaaS articles averaged 4.2 statistics and 1.6 expert quotes, compared with 1.2 and 0.2 for articles that were never cited. Engines quote pages that contain something worth quoting. That means specific numbers with named sources and a direct answer near the top of each section.

Off site presence. In the DerivateX panel, 63.4% of AI Overview citations were third party "best X" style list pages, and only 12.2% pointed at the recommended product's own site. Citera's figure is a little kinder, with brand owned content holding 29% of AI citations in B2B SaaS, mostly because buyers ask feature specific questions that vendor docs answer well. Either way, most citations live off your domain, so growth needs to work on the comparison articles, review sites, communities and publications that engines already trust for your category.

Where do the two teams overlap?

They overlap on your docs, your homepage and your measurement, so those three need joint ownership. Each one is technical and editorial at the same time.

Docs. Feature specific prompts are where your own content has the best chance of being cited, which helps explain why brand owned pages still earn 29% of citations in Citera's data. Docs need to be crawlable, which is engineering, and need to answer real questions in plain sentences, which is content.

Homepage. If an engine describes your product wrong, the fix usually starts with a homepage that explains what you sell in one plain sentence, plus schema that agrees with it. Copy and markup should be shipped together.

Measurement. Rankings and AI visibility move on different schedules, so they need separate dashboards. Citera found citation overlap between engines of only 8% to 17%, which means a win in ChatGPT says little about Perplexity or Gemini. Track mention rate and citation rate per engine against a fixed baseline.

What does this split look like in a real project?

It looks like engineering clearing the foundation first while content and growth build on it in sequence. Monk, a finance automation platform SearchAxe worked with, is a useful example.

At the December 2025 baseline Monk had zero AI citations across seven answer engines and a thin link profile. The first phase was technical, covering schema and indexation. The second was a content standard built around direct answers and real numbers. The third was authority work. Over eight months, referring domains grew from 469 to 1,326, measured in Ahrefs against the fixed baseline, and Monk is now cited in five of those seven engines.

The order mattered. None of the GEO gains would have shown up without the technical and authority layer underneath. The full breakdown is in the Monk case study.

How should a small team sequence the work this quarter?

Start with a shared baseline, then let each team run its backlog in parallel. Here is a sequence that works for a Seed to Series B SaaS company without a large marketing department.

1. Week one, joint. Record current rankings and traffic. Then run the 20 to 30 prompts your buyers really ask through ChatGPT, Perplexity, Gemini and Google AI Overviews. Log who gets named, who gets cited and how your product is described.
2. Weeks two to four, engineering. Fix indexation gaps, consolidate duplicate feature pages and ship schema that matches the homepage description.
3. Weeks two to six, content. Rewrite comparison, alternative and use case pages so each opens with a direct answer and includes sourced numbers.
4. Ongoing, growth. Identify the list articles, review platforms and communities that engines already cite for your category, and earn a credible place in them.
5. Monthly, joint. Rerun the prompt set and compare against the baseline per engine, separately from organic reporting.

Skipping the baseline is the most common mistake we see. Without it, nobody can tell whether the engineering or the content work moved anything.

How do you keep the split honest?

Keep it honest by refusing to promise outcomes nobody controls and by reporting the two channels separately. No team or agency can guarantee a ranking or a citation, because engines change their sources constantly.

At SearchAxe we run SEO and AI visibility as one programme for B2B SaaS teams, with a shared baseline and separate reporting, because the data above shows that splitting the budget without coordinating the work wastes both. If you want to see how that approach is structured, our GEO agency service page lays it out.

Frequently asked questions

Should engineers or marketers own schema markup?

Engineers should ship it and marketers should write what it says. Schema helps engines describe your product correctly, but research this year suggests it is not a strong citation lever by itself once domain authority is accounted for.

Is GEO replacing SEO for SaaS companies?

No. AI engines lean heavily on domain authority, which is built through classic SEO work. GEO extends that foundation into AI answers rather than replacing it.

Do we need different content for each AI engine?

You need separate measurement more than separate content. Citera found only 8% to 17% overlap in what different engines cite, so track each engine and adjust where you are missing.

How long before the split shows results?

It depends on your starting authority. Monk started from zero citations and a thin link profile and reached five of seven engines over about eight months. Expect to read direction in the first quarter.

If you want a clear view of where your product shows up in AI answers today and which team should fix what first, talk to SearchAxe.