If you still think of AI as something construction firms are trying out, the data has moved past you. A survey released this month says that among construction firms that have adopted AI, most now use it every day, and they use it across the office, not just at the estimating desk.
Who ran the survey, and why that matters
Houzz published its 2026 U.S. State of AI in Construction & Design report in early September 2026, along with an editorial summary of the key findings. The survey covered 601 U.S. construction and design businesses registered on Houzz, fielded in June and July 2026. Roofing Contractor reported on the same figures.
The caveats here are bigger than usual, so they go first.
The sponsor sells AI software to this audience. Houzz sells Houzz Pro, which has built-in AI features for estimates, takeoffs and visualization. The people surveyed are professionals already registered on Houzz's own platform, not a random sample of every construction business in the country. Both of those are reasons these adoption numbers would run higher than the industry as a whole. The sample size and method are disclosed and nothing suggests the figures were invented, but this is a vendor surveying its own users.
The numbers below are the construction breakout. The full survey includes design professionals as well. The figures used here come from Houzz's "construction firms" breakout. The blended industry-wide adoption figure is lower, at 41%.
It's a U.S. sample. Nothing in it is specific to B.C. or the Okanagan.
Past the testing phase
Fifty-two percent of construction firms in the survey now use AI tools for everyday business tasks. That's up 20 percentage points from a year earlier. Another 34% are still exploring, and 14% aren't using it and have no plans to.
The number that matters more is how often the adopters use it. Among construction firms that have adopted AI, 80% use it daily. Not once a month to try something new. Every day, as part of how the business runs.
That changes the conversation. A year ago, AI in construction was mostly framed as an experiment. For the firms in this sample that have adopted it, it's a routine habit.
It isn't just the estimate anymore
When AI first showed up in construction conversations, it mostly meant one thing: faster estimates. That's still the most common project use. Eighty-seven percent of construction firms using AI apply it to estimates and proposals.
But it's no longer the whole picture. Across business functions, construction firms using AI reported applying it in:
- Sales and marketing, 64%
- Planning and design, 61%
- Project and client management, 59%
- Administrative work, 52%
That's four different parts of the business, not one tool bolted onto the bidding process. A firm using AI today is likely using it in the office, in client communication and in scheduling, not treating it as a single-purpose estimating shortcut.
That's a different finding from the one I wrote about in AI Adoption in Construction Doubled. Most Contractors Still Can't Prove It Worked. That survey, from a different source, looked at where commercial contractors could point to a measurable result, and the answer clustered heavily in estimating and bidding. This one measures where firms are using AI at all, and the answer is much broader. Both can be true. Use spreads faster than proof does.
What daily use looks like in a small firm
"Daily use" can sound bigger than it is. In practice, for a small renovation or specialty contractor, it might look like this. The estimator starts a proposal from an AI-drafted scope description built on notes from the site visit, then corrects it. The office manager uses an AI tool to turn a voicemail and a few texts into a clean schedule update for the client. The owner asks an assistant to summarize a long email thread with a supplier before calling them back. Someone drafts the monthly social media posts in twenty minutes instead of an afternoon.
None of those tasks is dramatic. Each one saves a few minutes to an hour. What makes them "daily" is that they've become the normal way that piece of work gets done, instead of an experiment someone tries when they remember. That's the shift this survey is describing, and it's why the time savings add up across a week.
It's also why the risk changes. A tool used once a month gets checked carefully. A tool used every day gets trusted by default, which is fine until it's wrong. Daily use is where review habits matter most.
A dollar figure on the time
Saving time is easy to claim and hard to prove. This survey at least tries to put a number on it.
Construction firms using AI reported saving an average of 4.7 hours a week. Nearly a third, 32%, reported saving eight hours or more, which is a full workday back every week.
Houzz then ran those self-reported time savings against firm revenue and arrived at an estimated $244,000 in annual productivity gains per construction firm, on average.
Treat that figure carefully. It's an estimate built on self-reported hours, it's an average across firms of very different sizes, and it was calculated by a company that sells the software in question. It isn't a guarantee, and it isn't a number to plug into your own budget. What it does show is that firms are reporting time back in hours they can count, which is more grounded than a marketing promise about what AI might someday do.
Why the average can mislead
An average productivity gain across hundreds of firms hides a wide spread. A firm that uses AI to draft every proposal and client update will report very different savings from one that occasionally asks a chatbot to tidy up an email. The useful question for any individual business isn't what the average firm saved. It's how many hours your own team spends on work that looks like the work these firms automated.
Counting your own hours first
Before comparing yourself with a survey average, it helps to know your own baseline. For a couple of weeks, have the people in the office note roughly how long they spend on proposals, client updates, scheduling changes and admin. It doesn't need to be precise. Even rough numbers usually surprise people, because office work in a construction firm tends to be spread across many small interruptions rather than a few big blocks.
That baseline does two jobs. It tells you whether the kind of time savings these firms report is even possible in your business, since you can't save four hours a week on work that only takes two. And it gives you something to measure against later, so any savings you claim are your own numbers, not a vendor's estimate.
Clients notice before you tell them
The client-facing results are the part of this survey I find most interesting.
I spent 18 years in construction before this work, and clients judge a firm on two things quickly: how put-together the proposal looks, and how fast you get back to them. Both show up in this data.
- 58% of construction firms using AI say it helps them produce more professional proposals.
- 52% say it lets them show clients visuals faster.
- 39% say it speeds up how quickly they respond to clients.
None of that is about cutting corners internally. It's about the parts of the job a homeowner or a general contractor actually sees, and forms an opinion on, before any work happens. A clean, consistent proposal that arrives in two days instead of a week tells a client something about how the job will be run, whether or not that's fair.
If proposal speed is the bottleneck in your shop, this walkthrough on proposal turnaround covers what an AI-assisted workflow looks like in practice.
The riskiest place is the middle
Houzz's construction data sorts firms into three groups: 52% using AI, 34% exploring it, and 14% not using it with no plans to. The middle group deserves more attention than it gets.
A third of firms are spending time and attention on AI without it being built into how they run the business. That's cost without much payoff: time spent on trials, demos and subscriptions that don't settle into a routine.
Meanwhile, concern about AI's reliability and accuracy is rising across the whole survey, from 33% of professionals last year to 37% this year, even as more of them use it. More exposure isn't automatically producing more confidence.
Put those together and firms stuck in an open-ended testing phase get the downside of both worlds: the cost of experimenting and the doubt that comes from not seeing it pay off. Firms that have settled into daily use, at least in this sample, report the time savings. Firms that haven't started are at least not spending anything. The middle is where money and attention go without a clear return.
Signs a firm is stuck in the middle
The exploring stage usually doesn't feel stuck from the inside. It feels like progress, because people are trying things. A few signs suggest it has turned into a holding pattern:
- Several people have tried different AI tools, but nobody could say which one the business actually relies on.
- Subscriptions exist that nobody has evaluated since they were purchased.
- There's no agreement on what AI is allowed to see, such as client files, pricing or financials.
- The same conversation about "doing more with AI" has come up in more than one meeting without a decision attached.
None of that means the firm is behind in any permanent way. It means the effort hasn't been pointed at anything specific yet. That's usually a scoping problem, not a technology one.
What to take from this, carefully
Because Houzz sells AI software to the firms it surveyed, I'd read the adoption level as an upper bound rather than a description of the typical contractor. The 41% blended figure and the 34% still exploring are reminders that plenty of firms are not there yet.
The direction is still useful. AI use in construction offices is spreading from estimating into marketing, client management, design and admin. The firms using it regularly report hours back each week. And clients are seeing the difference in proposals and response time, whether or not they know what produced it.
For a firm in the exploring group, the useful move isn't more open-ended testing. It's deciding which part of the business would benefit first, what success would look like, and whether the data and the people are ready to support it.
Moving out of that middle with an actual plan is what the AI Discovery and Readiness Assessment is for. It's a paid engagement: a discovery call and a scored look at your workflows, data and team, ending in a written roadmap that tells you which department to start with and what it would take.