AI Search Visibility for B2B: What to Optimize and What to Ignore

Google states that its existing SEO fundamentals remain relevant for AI features and that no special AI schema or machine-readable file is required. That is a useful filter: fix discoverability and evidence before buying exotic GEO tactics. These product requirements concern Google's AI Overviews and AI Mode; the framework below is GrandMa's editorial approach, not a universal specification for every AI service or a guarantee of citations.

Put the answer in visible HTML, link it from relevant hubs and keep the page eligible for snippets. Use self-referencing canonicals on preferred pages where appropriate, but treat canonical declarations as optional signals, not AI eligibility requirements: Google can choose a canonical itself. A PDF, gated deck or social post can support authority, but our recommendation is that it should not be the only place where the answer exists. This does not mean PDFs cannot appear in Search; Google also documents canonical HTTP headers for non-HTML files.

For Google's AI features, the page must be indexed and eligible for a Search snippet. Check robots.txt, CDN or hosting blocks and the HTML Google receives through URL Inspection. Google's July 2026 optimization guide also says the site must be included in Search generative AI features in Search Console. This adds a condition absent from its December 2025 AI-features guide, which says there are no additional technical requirements. Use the newer eligibility guidance; meeting the requirements still does not guarantee crawling, indexing or display.

Answer the core question early, then add conditions, method, examples, limitations and source context. Use headings that reflect real subquestions. Keep numbers tied to a named case, period and definition.

This checklist is our editorial method. Google recommends original, useful content and readable organization, but prescribes neither tiny chunks nor an ideal page length. Preserve useful depth. Ignore pressure to manufacture a page for every prompt variation or seek inauthentic mentions; Google's guide warns against both tactics.

Use one company name, service vocabulary, author identity, contact set and market description across the site and trusted profiles, allowing accurate local-language versions and genuine alternate names. Where used and applicable, Organization, Service, BreadcrumbList and BlogPosting markup should match visible content rather than invent claims.

Google documents Organization markup as a way to clarify administrative details and distinguish organizations, including names, contacts and sameAs profile links. That supports identity clarity, not a promise of AI citations. The markup types above are examples, not a required AI bundle; structured data is not required for Google's generative AI search.

Track a fixed set of commercial and expert prompts by market and language. Record whether the brand is mentioned, cited and positioned correctly, plus the source URLs used. This panel is our editorial sampling method: also record the service, mode, date, exact prompt and session conditions, and repeat under comparable conditions. One screenshot is an anecdote; a repeated panel can show direction within the sample, not total market visibility or proof that an edit caused a change.

Pair the panel with Search Console and analytics. Google's dedicated Generative AI performance report documents AI Overviews and AI Mode link impressions. Google says its worldwide rollout was completed as of August 31, 2026. Review pages, countries, devices and dates. These impressions are also included in Web performance data, so do not add the two reports together as separate audiences. The dedicated report measures displayed links, not all brand mentions or your sampled prompts; Search Labs experiments are excluded.

For assisted conversions, use GA4's key event attribution paths to inspect recorded channels that initiate, assist and close a chosen key event, such as a lead form submission. Credit depends on the attribution model and available data. This report does not establish that an unclicked AI mention generated a lead.

Hypothetical worked example: a B2B software company tests 20 German-language buying prompts twice in one service and mode, producing 40 responses. Eight responses contain a link to its site: 8 ÷ 40 = 20% of sampled responses with a citation. Count each response once even if it contains several company links, and record unlinked brand mentions separately. Repeat the same panel after improving a relevant comparison page. A higher percentage would be a sample observation, not a Google impression metric, a benchmark or proof of incremental leads.