The Agentic Readiness Index: Home Services Edition

An AI agent can read almost every home services website in America. It can tell you what the company does, where it works, and roughly what it charges. What it cannot do — for one contractor in three — is book them.

We scanned 623 US home services contractors — plumbing, HVAC, electrical, mechanical and multi-trade — on 14 August 2026, checking whether an AI agent can read a site, understand what it offers, and act on it. Every company was scanned three separate times, and a site is only recorded as unreadable if it failed in at least two of those three passes. That gate matters more than it sounds; the section on what we got wrong explains why.

Before you read this

Neural Partners sells websites and agent-readiness work to home services businesses, and this data comes from a free readiness scan we offer as part of that business. The sample is our own first-party contact list for this industry — not a neutral census or a stratified sample (full caveats in the Methodology section below). An earlier cut of this study reached different conclusions; we found the defect ourselves, re-ran everything, and the section “What we got wrong” below lists what we retracted and why. Weigh the source before the rest of the report.

Executive summary

Four numbers carry the story:

Readability is not the problem here. 89% of these sites can be read by an agent and discovery averages 82 out of 100. By the usual measures this industry looks fine.

It is not fine, because reading is not the job. A home services business exists to be booked, and when an agent finishes reading a contractor’s site there is almost nothing it can act on: no machine-readable way to book, and in a third of cases no contact route at all except a telephone number.

The one-line version

The industry spent a decade optimising its booking path for a human with a mouse. That is precisely the layer an agent cannot traverse.

The shape of the industry: states, not one score

A company an agent cannot see is not a low score — it is a different state, and averaging the two together hides the thing you want to know. [Denominator: all 623 companies]

Among the 556 scored, the average is 60, the median 63, the range 20–76. Not one company in this cohort scored above 80. The agent-blind causes split three ways: an empty page shell (31), an active bot wall (24), and a JavaScript-only shell (3). Only two companies opted out deliberately through robots.txt. Invisibility in this industry is overwhelmingly unintentional.

Five findings

Finding 1 — Readable, and completely unable to transact

[Denominator: 556 scored] All four agentic protocols we check for — the standards that would let an agent negotiate directly with a business’s systems — return exactly 0%. Not a low number. Zero, across every company an agent could read.

This one is as solid as anything in the study: the readable subset grew by 45 companies when we re-ran it, and the number did not move a point. The agentic protocol landscape explains what each standard does and which are worth building on today.

Finding 2 — The booking button is right there, and an agent cannot press it

[Denominator: 545 sites the booking overlay could probe] This is the report. Of the sites an agent can read:

One in three home services businesses is reachable only by telephone as far as an AI agent is concerned. Another one in six has built a booking button that an agent can see on the page and cannot use, because pressing it runs JavaScript rather than following a link.

Forms do not rescue it. We found 423 forms across the cohort, and only 189 of them (45%) carry enough labelling for an agent to know what to type. Spot-checking the largest operators showed why the raw count flatters the picture: at one national brand, the only two forms on the homepage are the site search box. At another, a newsletter field and a zip-code field. A third serves 224KB of HTML containing no structured data, no forms and no links at all.

Why we trust this one most

Every figure in this table moved by a point or two between our first cut and our re-run — while the denominator grew by 38 sites. A number that stays put when its sample changes underneath it is measuring something real. The findings we retracted did not behave that way.

Finding 3 — Private equity buys legibility. It does not buy readiness.

We expected consolidation to make no difference. It makes a large one, on every dimension except the one that matters.

Backed operators are seven times less likely to be invisible to an agent, and materially more legible on every other measure. The reason is unglamorous: they buy a field-service management suite, and that suite ships structured data and a booking URL. Inherited, not built.

But the ceiling is identical. Both groups sit at 0% on all four agentic protocols. Capital bought a better website. It did not buy anyone an agent interface, because nobody is selling one yet.

Finding 4 — Electricians are the least agent-ready trade, at the worst possible moment

[Denominator: 545 probed]

An electrical contractor is less than half as likely to have a booking endpoint an agent can follow as any other trade — 14% against 34–46% — and the most likely to be reachable only by phone.

The timing is unfortunate. The trade facing the largest incoming demand shock — EV chargers, panel upgrades, heat-pump electrification, all of it researched online before anyone picks up a phone — is the least prepared to be found and booked by the software doing the researching.

An earlier cut of this study made the same claim using invisibility rather than bookability. That version was wrong, and we explain why below. This one rests on the booking data, which is measured only on sites an agent could read and was unaffected by the defect.

Finding 5 — Scale helps, and then it stops

Read the sample sizes on this one before the percentages.

Multi-location groups are the sweet spot — big enough to buy good tooling, small enough to still look like a local business to a machine. The national brands have the worst bookability in the entire study and publish LocalBusiness structured data on 10% of sites; they publish Organization instead, which is correct for a franchisor and useless to an agent asked to find a plumber in Burlington tonight.

The enterprise tier is n=21 — the smallest cell in the study. Treat it as a hypothesis worth testing, not a finding.

Two industries, two different ways to be invisible

We ran the same three-pass test over our July lighting cohort, so these two figures were produced by identical logic and can be read side by side.

A lighting company that an agent cannot see has usually decided that — 53 of its 64 agent-blind sites sit behind a captcha or challenge page that refuses automated clients by design. A home services company that an agent cannot see is usually just misconfigured: a page shell that renders nothing without JavaScript.

That difference matters more than the gap between 32% and 10%. Lighting has a door with a lock on it. Home services has an open door and nothing behind it. The second is easier to fix and, on the evidence in this report, much less likely to be fixed on purpose.

We are comparing observability only. The two volumes’ 0–100 scores were produced by different versions of the scoring code and are not comparable; presenting a movement between them would imply an industry change we cannot evidence.

What we got wrong

We published research limitations as a matter of course. This time there is something larger to report: our first cut of this study was wrong in three specific ways, we caught it before publication, and we re-ran the entire cohort.

The defect. Our scanner treated any failed request as a permanent verdict. If a single fetch failed for any reason — a momentary network blip, a slow DNS response — the company was recorded as unreachable, with no second attempt. Run hundreds of scans concurrently and a certain number of transient failures are guaranteed. Every one of them became a finding.

How we found it. Re-scanning a sample by hand, sites recorded as dead answered immediately with full pages. One company returned two different verdicts minutes apart. That is not a site changing; that is a measurement that does not hold still.

The fix. Every company in this report was scanned three separate times, spaced apart. A company is only recorded as unreadable if it failed in at least two of the three. 34 companies (5.5%) changed state between runs — so any single pass, including our first one, was going to be wrong somewhere.

Three claims from the earlier cut are withdrawn:

• “17% of the industry is invisible to agents.” The real figure is 10%. The earlier number counted first-attempt failures as fact.
• “One website vendor blocks agents on every site it builds.” Verified over three spaced rounds, it is 3 of 12 — a normal rate, not a policy. The original figure came from a single request racing another. We had this in a draft of this report. It was wrong, and it would have been unfair to a named vendor.
• “Your website vendor determines whether you are visible to AI.” This held strongly in our July lighting study. In home services the spread across vendor types collapsed to 2–7%, resting on four invisible sites out of 55 — too thin to carry a finding. Ownership separates this industry, not vendor (Finding 3).

One more, in our favour and equally worth stating: we had reported that 3.9% of these businesses publish DNS in a way that made them look offline. On re-check, zero of the 623 do. That claim came from the same class of error, in our own DNS code, and we withdraw it too.

Methodology & what this data can — and can’t — support

• Sample frame. 623 real companies drawn from Neural Partners’ own first-party contact list for this industry — our prospect list, not a neutral census or a stratified sample. Every figure describes this cohort, not a certified industry rate.
• Reproduction gate. Three spaced passes per company; a non-readable state is only recorded when it reproduces in at least two of three. Hard blocks — sites that serve a browser and refuse an agent — were verified across three rounds with both user agents, sequentially. 16 companies (2.6%) do this consistently.
• Denominators. Four populations appear here and mixing them would flatter the numbers, so every table states which it uses. Companies is all 623. Scored is the 556 an agent could read. Probed is the 545 the booking overlay could assess. Vendor analysis uses the 487 companies whose website vendor we could identify.
• Why we don’t lead with our own Completion score. Our standard scan produces a Completion score alongside Discovery. In this industry it does not tell you much: two of its inputs pass on almost every site (99% and 97%), one measures product data that a service business structurally does not have, and the agentic-protocol inputs are at zero across the entire cohort. A score where nearly everyone lands in the same place cannot rank anyone. So for home services we report bookability, which does separate the field. If you run our free scan you will still see a Completion score; treat it as a checklist, not a ranking.
• Small subgroups. The enterprise tier is n=21 and the vendor-type breakdown rests on as few as four invisible sites in a bucket. Both are reported with their sample size attached and neither carries a headline.
• No per-vendor rates. We measured hard-blocking by vendor. No individual vendor’s sample is large enough to publish a rate against, so we publish the 2.6% cohort figure and nothing more granular.
• Anonymised by design. No company and no vendor is named anywhere in this report. The patterns are the point; naming individual businesses that did not choose their situation is not.
• What we compare across volumes, and what we don’t. Our July lighting volume has now been re-scanned under this same three-pass gate, so the two volumes’ observability figures — whether an agent can see a site — are measured identically and are comparable. Their 0–100 scores are not: the scanner’s scoring code changed between the two runs, so any movement would mix instrument change with real change. We compare the first and not the second.
• Point-in-time. Scanned 14 August 2026. Bot-facing behaviour changes. Read a snapshot as a photo, not a trend.

What this means for you

If you run a home services business, three things follow directly from this data:

• Give an agent a URL it can follow. The single highest-leverage change in this entire report is turning a JavaScript booking modal into something with a real link behind it. 16% of this industry is one attribute away from being bookable by an agent.
• Check which state you are in. Readable, agent-blind and unreachable are three different problems with three different fixes. If you are agent-blind, it is almost certainly a platform default you did not choose, and it is usually fixable without touching your website.
• Nobody has done the deliberate work yet. Zero percent, across 623 companies, on every agentic protocol. That is not a gap you are behind on — it is one nobody has closed. The window where this is a differentiator rather than table stakes is open right now.

As disclosed at the start of this report

Neural Partners builds websites and agent-readiness infrastructure for home services businesses, and offers the free scan this data comes from. Full methodology and sample caveats are in the Methodology section above.

Want your own score? Run the free Agentic Readiness Check to see exactly where your site lands — it is the same scan behind this report.

What to read next

This report measures the gap. These cover what closes it:

• The agentic protocol landscape — every standard on one page, with a plain verdict on whether it is safe to build on. Re-verified quarterly.
• MCP, A2A, and the agent interoperability stack — the protocols sitting at 0% in this study, and what implementing them actually involves.
• The Agentic Readiness Index: Lighting Industry Edition — our July volume, covering a different industry. Re-tested in August under the same three-pass gate described above — its findings held.
• AI marketing for home services — what we build for contractors, including the booking layer this report says almost nobody has.