State of
Home Services
2026

We surveyed 32 home services operators in May 2026. Respondents were owners, executives, directors, and managers at companies ranging from owner-operated shops to private-equity-backed platforms doing more than $100M in revenue. Trades represented include roofing, HVAC, plumbing, pest control, restoration, landscaping, electrical, and multi-trade operators.

A few things to know before you read the numbers.

With 32 respondents, a finding like "78% expect higher revenue" carries a real margin of error — on a 50/50 split, roughly ±17 points at 95% confidence, and even a near-universal figure like 91% carries about ±10. We round throughout, and where a cut of the data gets too small to defend, we describe the direction — "most," "more than half" — rather than pretend to a precise percentage. Sub-group figures come from very small cells and are flagged as directional wherever they appear.

Respondents were reached through a professional outreach campaign, which skews the group toward operators who are larger, more digitally engaged, and more likely to have already met a private equity suitor than the industry as a whole. We lean on outside research throughout to put these numbers in context; where a figure comes from somewhere other than our own survey, it is cited.

Read this as the view from the front of the adoption curve — the operators making deliberate decisions about AI, talent, and scale right now — not as the median home services business.

The home services market is big and getting bigger. Industry estimates put it on track to reach roughly $842 billion in 2026. Demand is unusually durable: with most homeowners holding mortgage rates below 4%, fewer are moving and more are investing in the homes they already own — renovations, repairs, and the deferred maintenance that keeps the trades busy.

So the pressure operators feel isn't about demand drying up. The work is there. The question is whether their operations can keep pace with what's changing around them — and the loudest of those changes is AI, arriving in the front office faster than anyone has figured out how to manage it. This report maps who's handling that well, who isn't, and what separates them.

Everyone assumes the biggest, best-capitalized operators — the platforms with innovation budgets and dedicated technology teams — are furthest ahead on AI. It's a reasonable guess. It's also wrong.

In our data, the largest operators use AI the least broadly of anyone, and they're posting the strongest margins of any revenue band. That pairing is the most important thing this survey found — and the least intuitive.

Start with adoption, which looks like a settled question. 91% of operators told us they use AI. But look at how.

More than half — 55% — described their use as an internal chatbot: ChatGPT or Gemini, open in a browser tab. The median operator has just two AI use cases; the most common number is one. Among AI users, only 17% quote with it and only 31% schedule with it. The tool is everywhere. The operating model is not. Nearly everyone has bought a smarter assistant; almost no one has rebuilt the work around it.

Now split that by size, and the surprise appears. The operators using AI most broadly are the smallest ones — owner-operators average about 3.6 use cases and $10–25M shops about 3.8. The largest operators average roughly 2.1, and private-equity-backed operators just 1.8. The companies with the most resources to deploy AI are deploying it in the fewest places.

Where are the eager adopters pointing all that AI? Increasingly, at the front line — the inbound phone. It's an understandable instinct, because the phone is visibly leaking. The next pages show why that's the riskiest place to aim it.

78% of operators are not "very confident" they capture and convert inbound calls, and the outside data is worse than the mood: the average home services company books just 42% of its inbound call leads, and providers miss or mishandle an estimated 15–25% of calls. So 41% of AI users have aimed AI at call answering, hoping to plug the hole.

That's the gamble. The inbound call is the single highest-stakes moment a home services customer has — a flooded basement, no heat, a roof opened up to the weather — and it is exactly the moment customers least tolerate an AI.

A Hire Bloom analysis of more than 10,000 home services reviews found that, among the reviews that mentioned AI, sentiment ran 69% negative, with the worst reactions clustered on automated phone systems gatekeeping an emergency. The national mood backs it up: Morning Consult's 2026 AI Trust Report found 63% of US adults trust AI only a little or not at all, with distrust highest among the older and rural homeowners most likely to call a contractor.

The easiest AI to deploy — a bot on the phone — is the AI customers punish hardest. That single mismatch is the hinge of this whole report.

Hold that against the margin data. Margins are mostly improving across the field — 59% of operators say theirs got better last year — but the gains are not evenly spread. The largest operators, the ones using AI the least broadly, improved margins more than any other band. The pain concentrates one tier down, in the $25–100M middle, where half of operators saw margins decline.

Put the two together and the logic resolves. The largest operators aren't behind on AI; they're selective about it — declining to throw it at the customer-facing front line, where the downside is a one-star review and a lost lifetime account. The smallest shops can experiment broadly because a misstep is cheap and personal. The middle gets the worst of both.

Best Choice Roofing is a useful proof of the deliberate model, precisely because it is large — a top-five US residential roofer operating in two dozen states. Rather than racing to automate its estimating team, it ran the AI playbook on the workflow, discovered the custom agent alone couldn't close the gap, and added human capacity alongside the AI instead of betting on the agent to replace it. CEO Bryce Barnett frames every AI decision as a choice between whether AI can replace a job or make a person more efficient — and lands, repeatedly, on "and," not "or."

That's the deliberate advantage in one example: test AI honestly, find the line where it stops adding value, and staff the other side of that line with people. The biggest operators are likelier to do this not because they're visionary but because they have the most to lose from getting it wrong.

Two things keep this an argument rather than a proof. First, these are small groups — 14 operators in the $100M+ band, eight in the squeezed middle — so the margin contrast is directional, and we can't claim that restraint causes the better margins rather than simply traveling alongside scale, recurring-revenue mix, and pricing power.

Second, the largest operators' narrow AI use might be discipline, or it might be drag — more departments, more approval layers, more governance slowing every rollout. The survey can't fully separate the two. What Best Choice shows is that the deliberate version is real and that it works; the open question is how many of the big, slow-moving operators are deliberate by design rather than by inertia.

The practical lesson shows up in where the confident operators are putting their money. Asked about back-office investment for 2026, operators named two priorities tied at the top: Training and SOPs (53%) and AI tools (53%). The winners aren't choosing between people and AI. They're funding both — the tool, and the people and process it takes to run it.

The deliberate advantage plays out against a particular backdrop: operators who are, all at once, bullish and nervous. 78% expect higher revenue in 2026 than in 2025, a quarter expect growth above 20%, and 59% say their margins are improving. That optimism tracks the broader market — Jobber's 2026 Home Service Trends Report found 75% of operators expecting revenue growth.

But ask what's actually on their minds and the mood turns. The most common answer wasn't revenue or hiring — it was AI, named by 44% of respondents, with industry consolidation close behind at 41%. Operators are confident about their businesses and uneasy about the forces reshaping the industry those businesses live in.

Consolidation isn't a someday story in home services. It's a quarterly inbound. More than half of the operators we surveyed (53%) had been approached by a private equity firm or consolidator in the past 12 months, and 28% had been approached three or more times.

The capital behind those calls is substantial. There are 27 active HVAC-led roll-up platforms competing for deals, and in February 2026 Blackstone acquired Champions Group for roughly $2.5 billion — an implied 18.5× EBITDA. Valuations climb sharply with scale, which is part of why the largest operators can afford to be patient about everything else, AI included.

What's telling is where the anxiety goes once the pitch becomes routine. Among operators approached three or more times, AI has overtaken consolidation as the thing most on their minds. The group is small, so read it as a signal — but an intuitive one. Once you've heard the consolidation story enough times, the question stops being whether you'll be bought and becomes what your operation needs to look like, with or without an exit. And increasingly, that's a question about AI.

Underneath the AI question is the reason it's urgent: there aren't enough people. Labor anxiety is nearly universal — 88% of operators are at least somewhat concerned about technician turnover, and 44% are very concerned or call it their single biggest concern. Only four said they weren't worried at all. Everyone else was.

But the same tight market shows up as two different problems by size. Smaller operators are still fighting to fill the truck. Larger operators have largely solved hiring and hit a different wall — leadership depth.

The pressure is structural. Industry estimates put the HVAC technician deficit around 110,000 and the plumbing trade on track for a shortage of roughly 550,000; in restoration, annual turnover runs about 28%.

This is where the labor story and the AI story meet. The larger operators who can't find managers are the same ones reaching for AI as a force-multiplier — but AI doesn't run itself. Someone has to implement it, document it, and supervise it. The deliberate operators understand that the AI problem and the people problem are, in the end, the same problem.

AI ran through every section of this report. That part was no surprise. The useful part is what the data showed once you looked past adoption: the dividing line isn't AI versus people, and it isn't big versus small. It's deliberate versus hasty.

None of this is a forecast. It's a field reading from today's operators, set against the broader market wherever we could. The numbers will move. The direction — toward operators who treat AI as an operating decision, not a quick purchase — looks durable.

Hire Bloom surveyed 32 home services operators in May 2026 and set the findings against current third-party research on the home services market. Survey figures without a citation come from that survey (N=32); external figures are cited inline and listed at the end.

Two features of this sample shape how the findings should be read. First, recruitment. Respondents were reached through a professional outreach campaign rather than a random draw of the industry, which selects for operators who are digitally engaged and marketing-aware. That almost certainly lifts the AI-adoption numbers above the true industry rate, which independent estimates put closer to 60–75%.

Second, composition. The group skews large and institutional: about 53% are private-equity-backed (against an industry reality in the single digits), 44% are above $100M in revenue (a sliver of the real population), and roofing is overrepresented at roughly a third of responses. None of this invalidates the findings — but it does define them. Read this as the state of the larger, PE-aware, digitally-engaged operator, not the median home services business. The clearest, most defensible cut in the data is the contrast between bigger and smaller operators; the smallest sub-groups, reported from single-digit cells, are flagged as directional throughout.