1 in 5 Accounting Firms Has an llms.txt. Almost None Wrote It.

We checked 556 US accounting firm websites and found an llms.txt file on nearly one in five. For something this new, that looked like surprisingly fast adoption.

It wasn't. Most of the firms had never written one.

What an llms.txt file is

llms.txt is a plain-text file that identifies a site and points AI systems toward its important content. In theory, it gives those systems a cleaner map of what the business does and which pages explain it best.

Almost none of them were written by the firm

Of the 556 firms, 92 had a valid llms.txt. When we classified where each file came from, only 43 were written by the firm. The other 49 were generated automatically by the platform the site runs on:

• Wix now emits an llms.txt for every site, advertising its Model Context Protocol endpoint. That was 30 of them.
• WordPress SEO plugins (All in One SEO, Yoast, Rank Math) generate their own. Seventeen more.
• Shopify emits one for its commerce protocol. Two.

Strip out the automatic files and the real number is 9.3 percent. Fewer than one accounting firm in ten has chosen to publish an llms.txt. The one-in-five figure was a mirage created by a handful of platforms doing it by default.

Why the auto-generated ones do not count for much

An automatically generated llms.txt is not worthless, but it is not the signal it looks like. It describes the platform, not the practice. A Wix-generated file tells an AI agent that the site supports Wix's protocol. It does not tell that agent that your firm has a partner who handles pre-IPO equity compensation, or a team that specializes in trust and estate work. The file exists, but it contains almost none of the information that would help an AI system understand why someone should hire that firm.

The mirage hides a bigger gap

The llms.txt number is a symptom. The deeper finding in the same study is harder to explain away: 94 percent of these firms publish no Person schema at all.

Person schema is the structured data that connects a named human to a role and an area of expertise in a format a machine can read. It is how an answer engine knows that a specific credentialed person, at your firm, handles a specific topic. Our earlier pilot found none. The full study found 27, but that still leaves 94 percent of reachable firms without Person schema.

Here is why the two findings belong together. An llms.txt file cannot identify an equity-compensation specialist if the site never clearly connects that person, credential, and expertise in the first place.

It is not that firms are blocking AI

Accounting firms are not broadly blocking AI crawlers, either. Only 2.4 percent of the firms blocked even one in robots.txt. The doors are open. There is simply nothing structured on the other side to read. This is primarily an implementation gap, not a deliberate refusal to participate. That makes it much easier to fix.

What to do instead of chasing llms.txt

If you take one thing from this, it is the order of operations. Do not start with llms.txt. Start with the structured data that names your people and your services, because that is what an AI actually needs to recommend you, and it is where almost every firm has a gap.

That means Person schema for each of your named CPAs and their credentials, tied to your firm's Organization or AccountingService data. We wrote the practical version of this fix in Schema Markup for CPA Firms and, for the AI-recommendation angle specifically, in Will AI Recommend Your CPA Firm. Neither requires a redesign or a single new page. Both make expertise you already have legible to a machine.

One thing we do not recommend: adding review or rating schema to your own site. Google's guidelines disallow self-serving review markup, and only 3 percent of the firms we checked used it anyway. Person, identity, and FAQ schema are the honest levers.

The firms that get recommended are the legible ones

AI systems cannot evaluate expertise that a firm never clearly publishes. A highly qualified CPA with an unstructured bio may be harder for a machine to identify than a less experienced competitor whose role, credentials, and specialties are clearly connected.

Right now, very few accounting firms are doing this well. That gives the firms that fix it early a real advantage.

The full study, including the methodology and the open dataset, is The State of CPA Firm Websites 2026. If you want to see what an AI actually reads on your own site, our free DeepAudit scan renders the page in a real browser and checks the structured data an answer engine sees. It takes about a minute.