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

Here is a number that looks like good news. We checked 556 United States accounting firm websites, and nearly one in five had an llms.txt file. For a standard barely a year old, one in five would be surprisingly fast adoption.

Then we checked who actually wrote them. The good news mostly evaporated.

What an llms.txt file is

llms.txt is a plain text file a website publishes to tell AI agents and answer engines how to read it: what the site is, which pages matter, where the important content lives. Think of it as a front door built specifically for the tools behind ChatGPT, Claude, and Perplexity. As those tools do more of the searching on a client's behalf, a clear front door starts to matter.

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. It is presence without intent, and intent is the part that helps a prospect find the right expert.

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. Across the 464 reachable firms, only 27 had it. A pilot earlier this year suggested the number might be zero; at full scale it is not quite that stark, but 94 percent missing is close enough to change how you think about the vertical.

Here is why the two findings belong together. Even a hand-written, perfect llms.txt cannot help an AI recommend your equity-comp partner if the site never states, in machine-readable form, that the partner exists and knows the topic. The front door does not help if the rooms inside are unlabeled.

It is not that firms are blocking AI

The tidy explanation would be that accounting firms, cautious by nature, are deliberately keeping AI crawlers out. They are not. Only 2.4 percent of the firms block any AI crawler in their robots file. The doors are open. There is simply nothing structured on the other side to read. That is worth sitting with, because a markup gap is fixable in an afternoon, while a strategy of hiding from AI would not be.

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

The uncomfortable takeaway from 556 firms is that visibility to AI has very little to do with how good a practice is. The firms an answer engine names are the ones whose expertise was published as fact, in a format the machine can read. Right now, in accounting, that is a short list, which means the gap is also an opening.

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.