I scanned 1,902 local-business websites for AI readiness. One in four already has an llms.txt.

I build a tool that checks whether AI answer engines can read a website. On 12 October I pointed it at 1,902 ordinary local-business sites in the USA and UK: dentists, plumbers, hairdressers, vets, gyms, estate agents and five other trades, in twenty big cities. 1,355 of them could be read and scored.

I expected the story to be "small businesses are blocking AI and do not know it". That is not what the data says. Here is what it does say.

One in four already has an llms.txt, and most did not write it

338 of the 1,355 sites (24.9%) serve an llms.txt file. That is far more than I expected for businesses that mostly do not know the file exists.

The reason is the site builder:

If you are on Wix, you almost certainly have one. If you are on Squarespace, you almost certainly do not. Whether anyone chose that is another matter.

Almost nobody blocks AI crawlers in robots.txt

Only 9 sites (0.7%) have a robots.txt rule that shuts out an AI answer fetcher such as OAI-SearchBot or PerplexityBot. 14 (1.0%) shut out a training crawler such as GPTBot or ClaudeBot.

I counted a block only when the file names the crawler and disallows the whole site. By that measure, local businesses are not opting out of AI. They have not touched the file.

The real gap is that sites do not say who they are

This is the finding that matters most for the businesses themselves.

• 621 sites (45.8%) have no structured data describing the business at all. No name, address, phone number or hours in a form a machine can read without guessing.
• 796 (58.7%) do not give their opening hours in structured data.
• Only 235 (17.3%) state every fact the scan looks for.
• Custom-built sites are worst: 254 of 342 have none. On Wix it is 26 of 121.

An answer engine asked "who is open now near me" has to get that from somewhere. For most of these sites it is not the site.

Seven in ten have no questions and answers

970 sites (71.6%) had no FAQ page and no question-and-answer content on the pages read. Roofers and plumbers do best. Hairdressers and accountants do worst.

The typical score is 58 out of 100

The median readiness score is 58.1. A third of sites score under 50. By platform the medians run from 69.8 (Shopify) down to 47.7 (custom-built), which is mostly the structured-data gap again: builders add it for you, and a hand-built site only has what someone remembered to write.

One listed website in six no longer works

A side finding: 328 of the 1,902 sites I sampled from OpenStreetMap had no working website. 147 domains no longer resolve.

How it was done, and what it cannot tell you

The sample is independent businesses that list a website in OpenStreetMap, chains removed, up to 100 drawn at random per trade per country. Each site was read over plain HTTP, up to five pages, with no browser and no AI model. Twenty were checked by hand against a second reading and fifty were scanned twice.

Limits worth knowing before you quote any of this: five pages is not a whole site; the sample leans towards established premises in big cities; and the scan ran from one connection on one day. It says nothing about whether an AI engine actually recommends any of these businesses. It measures whether a site can be read and what it states, which comes first.

Every count, the method, the infographic and a CSV of the figures are in the full report: How ready are local-business websites for AI answers?

Contains data © OpenStreetMap contributors, available under the Open Database Licence.