AI search is not a separate marketing strategy

The rush to AI search has created a new category of marketing advice, and some of it makes AI visibility sound like a completely separate discipline. I am skeptical of that framing.

There are AI-specific things worth checking. Your site needs to be accessible to the crawlers that matter. You should understand where your company is appearing in AI-generated search experiences. Measurement is getting better. But the biggest levers are still familiar: a technically sound website, clear service pages, useful expert content, credible third-party authority, and information that is specific enough to be worth citing.

If those pieces are weak, a new “GEO checklist” will not fix the larger marketing problem.

Google is saying this more directly now

In July 2026, Google updated its official guide to optimizing for generative AI features in Search. The guidance is unusually clear: traditional SEO best practices still apply because Google’s generative AI experiences rely on its core search and quality systems. Google also says there is no special schema required for generative AI search, no need to create an llms.txt file for Google, and no requirement to break content into tiny chunks for AI systems.

More important, Google keeps coming back to the quality of the underlying material. It recommends unique, useful content with real perspective and experience, rather than pages that simply summarize information already available elsewhere.

That matters for B2B companies because expertise is usually the real product. The company knows things its buyers care about. The marketing job is to get that knowledge out of sales calls, internal documents, and a few people’s heads and turn it into something discoverable and credible.

Start with technical access, because great content still has to be found

The technical layer is not glamorous, but it is the first place I would look.

Google says pages must be crawlable, indexed, and eligible to appear in Search before they can show in its generative AI features. OpenAI likewise says in its publisher and developer guidance that any public website can appear in ChatGPT search, and that sites should avoid blocking OAI-SearchBot if they want content to be available for summaries, snippets, citations, and links.

That gives you a very practical starting point: check robots.txt, indexing, page accessibility, canonical issues, JavaScript rendering problems, site speed, and whether your important pages can actually be reached by the systems you expect to find them.

This work supports traditional search too. That overlap is a feature, not a problem.

Then look at the pages that explain what you actually do

A lot of B2B websites have spent years adding blog content while leaving core service and industry pages thin, generic, or outdated.

That is a weak foundation for any kind of search visibility. If a buyer, search engine, or AI system lands on a service page, it should be able to understand who the service is for, what problem it addresses, what the work includes, what makes the approach credible, and where the company has relevant expertise.

Those pages also need to reflect how the business is positioned now. AI optimization cannot compensate for messaging that no longer matches the company.

Before creating ten new articles, I would usually make sure the highest-value pages on the existing site deserve to be surfaced.

Refresh useful old content before assuming everything has to be new

Older content can still be valuable if the underlying topic matters to buyers. It may simply need better structure and stronger evidence. Useful updates can include:

None of those tactics are particularly exotic. Most are good content and SEO practices. They also make the material easier for humans to scan and for search systems to interpret.

Create more material that only your company could credibly publish

This is where AI search should push B2B content in a better direction.

The internet does not need another generic article on “five ways to improve cash flow,” “seven tips for choosing software,” or “the future of professional services.” Those are exactly the kinds of topics AI can summarize without needing your company at all.

A stronger content program starts with what the business actually knows: patterns across client work, recurring questions from buyers, proprietary data, original research, market observations, benchmarks, decision frameworks, and informed opinions from the people closest to the work.

This does not mean every company needs to commission a large research study. A useful dataset, a recurring market analysis, an anonymized pattern from dozens of conversations, or a specific point of view can all be more valuable than another broad explainer.

Authority should exist outside your own website too

PR, contributed articles, industry associations, podcasts, partnerships, and executive thought leadership still matter. I would not treat outside mentions as an AI-search hack. Google explicitly warns against chasing inauthentic mentions.

The better reason to build an external presence is simpler: expertise is more credible when it shows up in multiple legitimate places. A strong bylined article, a respected industry citation, a useful conference presentation, or a subject-matter expert who consistently publishes thoughtful commentary can reinforce what the company says about itself.

For expertise-driven B2B firms, that has always been good marketing. AI search gives companies another reason to take it seriously.

AI visibility is also becoming easier to measure

On June 3, 2026, Google announced dedicated generative AI performance reporting in Search Console, and it says the reports were rolled out to websites worldwide by August 31, 2026. The reporting shows impressions in generative AI features, the pages appearing, countries, devices, and performance over time.

That gives marketers a better baseline than trying to reverse-engineer visibility from a handful of manual prompts.

I would still look beyond one dashboard. Track referral traffic from AI tools when it is available. Watch which pages earn visibility. Look at lead quality, branded search, direct traffic, and whether sales conversations increasingly mention AI-driven discovery. Search behavior is fragmenting, so the measurement model should get broader rather than chasing one new vanity metric.

What I would prioritize now

1. Make sure your important pages are crawlable and indexable, including access for the search crawlers you care about.
2. Strengthen core service and industry pages before producing large volumes of new content.
3. Refresh high-value existing content with current evidence, clearer structure, authorship, and stronger internal linking.
4. Create expert-led material that adds something genuinely specific: original data, research, frameworks, patterns, or informed points of view.
5. Build credible visibility beyond your own site through PR, industry participation, contributed content, partnerships, and expert voices.
6. Measure AI visibility alongside traditional search, referral traffic, engagement, and business outcomes.

AI search deserves a place in the marketing plan. It does not need its own universe.

The companies most likely to benefit are the ones doing the fundamentals well and adapting them thoughtfully as search changes. That is less exciting than a brand-new optimization playbook, but it is a much more durable place to invest.