TL;DR
- Treat your About page as an entity resolution document, not a marketing pitch — it's where AI engines confirm who you are, not why you're great.
- Include founders with full names, founding date, legal entity name, headquarters location, and sameAs links to your verified profiles (LinkedIn, Crunchbase, Wikipedia, Wikidata if you have one).
- State what you are not — the category boundary you don't compete in — because disambiguation reduces the chance of being cited for the wrong query.
- Keep facts in plain prose near the top of the page; don't bury them inside a hero animation or a scrolling "our story" carousel.
- Pair the page with Organization schema so the structured data and the visible text say the same thing.
An About page written for AI search is a disambiguation tool. Large language models and retrieval systems don't read your About page to decide if they like you — they read it to figure out which entity you are, how you relate to other entities (founders, investors, competitors, parent companies), and whether you're the same "Acme" as the twelve other Acmes in their training data or index. Most About pages are written for humans who already know roughly what the company does and just want a trust signal. That's the wrong job for the page in 2026. The job now is entity resolution: name, form, people, place, time, and boundaries.
Why AI engines read About pages differently than SEO treats them
Search engines rank About pages. AI engines use them to populate a knowledge graph node. When a model is deciding whether to cite your brand in an answer about "project management tools for agencies," it isn't reading your About page for persuasive copy — it's cross-referencing whether you are a distinct, verifiable entity with a track record, or an ambiguous shell that could be confused with a similarly named competitor. This is the same underlying mechanic discussed in the 7 signals LLMs use to pick which brands to cite: consistency of identity across sources matters as much as any single page's content. The About page is the canonical place that consistency gets tested, because it's the one page every company has, and the one page crawlers expect to contain identity facts.
The checklist: what actually belongs on the page
Legal name and trading name. If your legal entity is "Acme Software Inc." but you trade as "Acme," state both. Mismatches between legal and trading names across your site, Crunchbase, and state filings create ambiguity that a model has to resolve by guessing — or it just won't cite you.
Founding date. A specific year (or month/year) anchors your entity in time and helps distinguish you from similarly named companies founded in other decades. "Founded in 2019" is a fact a model can use; "we've been doing this for years" is not.
Founders and current leadership, named. Full names, not just "our team of experts." If a founder has a public professional profile (LinkedIn, a personal site, a Wikipedia page), link it. This is also one of the few places person-entity and organization-entity data overlap, which helps both resolve.
Headquarters location. City and country minimum. This matters more than it seems — location is a disambiguating field for any company with a common name, and it's a field structured data (PostalAddress in Organization schema) expects to match.
sameAs links. LinkedIn company page, Crunchbase profile, X/Twitter, Wikipedia or Wikidata entry if one exists, G2 or Capterra listing. These aren't just backlinks — they're corroborating references a model can triangulate against. The relationship between sameAs and other identity properties is covered in more depth in sameAs vs knowsAbout: which Schema.org property when and in the organization schema backbone piece, but the point for the About page specifically is that the visible links and the schema-coded links should be identical.
What you are not. This is the most commonly skipped item and arguably the highest-leverage one. A sentence like "We are not a general-purpose CRM — we are a scheduling layer built specifically for field service teams" does more disambiguation work than three paragraphs of mission statement. It tells the model which query clusters you should and shouldn't surface in, which protects you from being cited (and then penalized in trust) for the wrong intent.
Ownership and funding status, if relevant. Bootstrapped, VC-backed, acquired, subsidiary of a parent company — state it plainly if true. Parent/subsidiary relationships are exactly the kind of structured fact a retrieval system struggles to infer from narrative copy but can lift instantly from a direct sentence.
Formatting: make the facts extractable
Write the identity facts in short, declarative sentences near the top of the page, before the narrative. A good pattern: a two-to-four sentence opening paragraph that reads almost like a Wikipedia infobox in prose form — name, founded, headquarters, what category you operate in — followed by the founder story, product narrative, and values further down. This mirrors the advice in evidence-dense writing for GEO: front-load the facts an extraction model can lift cleanly, then let the brand voice come after. Avoid putting founding date or location only inside an image, a timeline graphic, or JavaScript-rendered carousel — if the bot can't parse it without executing complex client-side rendering, treat it as invisible, a problem covered more technically in the SSR vs CSR rendering discussion.
Keep schema and prose in sync
Organization schema with sameAs, foundingDate, and address fields should restate — not contradict — what's on the page. If your schema says founded 2018 and your About page copy says "for over a decade," that's a conflict a careful system may resolve by ignoring both. The schema is the machine-readable layer; the About page prose is the human-readable layer that a language model reads directly when schema is absent, malformed, or ignored. Redundancy here isn't wasteful, it's the whole point.
FAQ
Does the About page actually get crawled by AI bots?
Yes — About pages are commonly among the first few pages crawled by bots like GPTBot, ClaudeBot, and PerplexityBot because they're a predictable, low-cost way to resolve entity identity before deeper crawling.
Should I include customer logos and awards on the About page?
Keep them, but below the identity facts. Social proof helps human trust but doesn't help disambiguation, which is the About page's primary job for AI systems.
How often should the About page be updated?
Update it whenever a material fact changes — new funding round, HQ relocation, leadership change, acquisition. Stale identity facts (wrong founding date, departed founders still listed) actively hurt entity resolution rather than just looking outdated.
