The Greater Vancouver Board of Trade released an AI adoption report this year that should have every contractor in the Okanagan paying attention. Most haven't read it.
The headline: 68% of B.C. businesses haven't considered AI at all. Construction sits at the bottom of every sector breakdown, roughly 11% below the Canadian average. Regional data in the same report suggests Interior businesses are meaningfully behind Lower Mainland firms on adoption, though the gap varies by sector and firm size.
For trades and construction companies in Vernon, Kelowna, and across the Okanagan, the adoption gap is a competitive position. Not a talking point. Whether your business is ahead of or behind the shop bidding against you on the next job.
Why the Okanagan trails on construction AI adoption
A Vernon excavator and a Burnaby excavator are often bidding the same scope, in the same labour market, for the same kind of client. If the Vancouver firm turns proposals around in 90 minutes and the Interior firm is still on three-day cycles, that gap shows up directly in win rates and quarterly revenue.
A few things keep the Interior behind.
The examples don't translate
Most national AI coverage comes from tech and professional services firms. Those companies look nothing like a sheet metal shop or a framing crew. When trades owners read about AI, the examples don't translate and they tune out. A case study about a software company cutting support tickets in half doesn't tell a plumbing contractor anything useful about his own bid process.
The vendor pitches are generic
Vendor pitches reaching the region are mostly generic software rebranded as "AI for construction." A 20-minute chatbot demo doesn't solve a trades problem. An owner sits through the pitch, asks how it handles his actual estimating process, gets a vague answer, and goes back to what he was doing before. That happens enough times and "AI" starts sounding like a sales pitch instead of a tool.
Few people understand both sides
People who understand both how a job site runs and how to implement these tools are rare in the Interior. Most AI consultants come out of software backgrounds and have never stood on a foundation pour. Most trades owners have never worked with a consultant of any kind, let alone one who speaks their language. So the technology stays theoretical, discussed at industry meetings and trade shows, rarely touching the actual bid process.
Owners are already stretched thin
Trades and construction owners in the Interior tend to run lean. Fewer administrative staff, more owner-operators than the coastal firms carry, tighter margins because the local market doesn't support big-city pricing. Learning a new system, however good it might be, competes directly with running the business today. That's not laziness. It's triage. When the choice is fixing the AI workflow or fixing tomorrow's schedule, tomorrow's schedule wins every time, which is exactly why adoption needs to be designed around minimal disruption instead of asking an already-stretched owner to find spare hours that don't exist.
The pattern isn't limited to construction
The Okanagan's manufacturing shops face the identical gap. Fabrication, cabinetry, agri-processing, the mid-size manufacturers scattered through Vernon's industrial areas and out toward Armstrong and Lumby run the same kind of document-heavy, judgment-dependent operations as a general contractor. Quoting a custom fabrication job isn't that different from estimating a build. Both live and die on someone's ability to price uncertainty correctly and get the proposal out before the client moves to the next supplier.
The GVBOT numbers are broken out by sector, and manufacturing shows the same pattern as construction: behind the provincial average, and behind the Lower Mainland on top of that. A Kelowna machine shop competing against a Richmond one is running the same math as the excavator example, just with different equipment on the floor. None of this requires retooling a shop floor or ripping out existing software. The same principle that applies to a contractor's proposal cycle applies to a manufacturer's quoting cycle: map where the delay actually lives, then decide whether AI closes that specific gap.
What "AI adoption" actually means for a construction business
Ask ten contractors what AI adoption looks like and most will describe a chatbot. That's not wrong, exactly. It's just a small slice of what the term covers, and usually the least useful slice for a trades business.
For a construction or trades company, adoption tends to show up in four places: how fast and how well proposals get written, how project documentation gets captured and organized, how scheduling and dispatch decisions get made, and how the knowledge that lives in your best people's heads gets preserved instead of walking out the door when they retire.
None of those four require a data science team. They require someone who understands the workflow well enough to know where a tool actually removes work, instead of adding a new task on top of the old one. The adoption reports don't measure that piece, but it's the piece that decides whether a rollout sticks.
Take documentation as an example. A punch list walk that used to mean an hour of note-taking by hand, followed by another hour transcribing it into a report that afternoon, can become a photo-and-voice-note capture on site that turns into a formatted closeout document by the time the truck pulls out of the parking lot. Nobody had to learn a new discipline. The way the information gets captured changed, and the two hours of transcription disappeared.
What AI looks like in a trades business that's already moving
I work with contractors in the Okanagan who are past the experimentation phase. Proposals get drafted in the time it takes to drink a coffee, reviewed by the estimator, and sent before the lead goes cold. Project closeout documentation gets built as a byproduct of the work instead of a four-hour task at the end of the job. The senior estimator's pricing judgment gets captured in a format the team can actually query, instead of staying locked in his head until he retires.
None of that requires a six-figure platform. It requires mapping the existing workflow, finding where AI fits, building governance, and training the team.
There's a labour angle here too, one that doesn't come up enough. The skilled labour shortage across the Interior isn't easing. Every hour AI gives back to an estimator or a project coordinator is effectively capacity you didn't have to hire for, in a market where hiring that person might take six months and a wage nobody budgeted for at the start of the year.
Say a 15-person mechanical contractor is losing two days on every proposal because the same three people have to review it before it goes out. Map that workflow and you usually find the delay isn't the writing, it's the waiting. AI drafting the first pass doesn't remove the review step. It removes the blank page, so the reviewers are editing instead of starting from scratch. A two-day cycle collapses to same-day without anyone skipping a check they used to do.
Objections worth taking seriously
Every owner I talk to has a version of the same three worries, and none of them are unreasonable.
"We tried something like this and it didn't stick." Usually because the tool got handed to the team without a workflow behind it. A subscription isn't an implementation. If nobody mapped where it fit into the actual proposal or scheduling process, the team tried it twice, hit friction, and went back to the old way. That's not a failure of AI. That's a rollout with no plan.
"My crew won't use it." Some of them won't, and that's fine. The goal isn't universal enthusiasm. It's building the workflow so the people who touch proposals, scheduling, or documentation have a tool that makes their specific task faster, with enough training that using it isn't its own obstacle.
"What about our data?" This is the right question, and it's the one governance is supposed to answer before anything goes live. Client information, pricing history, and project data need clear rules about where they can go and what tools can touch them. Skip that step and a business can end up with sensitive information sitting in a tool nobody vetted.
"We're not ready for this yet." This one is rarely true in the way people mean it. What they usually mean is that nobody has sat down and mapped where the highest-friction points in the business actually are, so "ready" feels like a future state instead of a decision available right now. Readiness isn't about having modern software already in place, or a tech-savvy office manager, or extra budget sitting around. It's about knowing, specifically, where the delay in your business costs you money, and whether an AI-assisted workflow closes that gap without creating new risk. Most businesses that think they're "not ready" turn out to have one obvious use case sitting in plain sight once someone walks through the operation with them.
What compounding looks like over two years
Picture two firms of similar size, same trade, somewhere in the Interior. Firm A starts now, with one workflow, proposal drafting say, done properly with governance in place from the start. Firm B waits, for the tools to mature, or for a slow season, or for someone else to prove it out first.
Eighteen months later, Firm A isn't just faster at writing proposals. They've iterated twice, expanded into documentation, trained the team to spot where AI helps and where it doesn't, and built the habit of asking "could this step be faster" into how they run the business day to day. Firm B is starting exactly where Firm A started a year and a half earlier, except now there are more AI-literate competitors in the same bid pool, and the vendors themselves have moved on to a different pitch.
The gap doesn't close by waiting for the technology to settle down. It closes, if it closes at all, by starting before you feel fully ready and correcting course as you go.
Why moving imperfectly still beats standing still
Plenty of Lower Mainland firms are jumping in without proper governance. Wrong outputs will land in front of clients. Data will end up where it shouldn't. Decisions will be made that nobody can explain. That's coming for some of them.
The firms iterating now will still be 18 months ahead of the ones starting then. Messy progress beats a clean start line.
Moving imperfectly doesn't mean skipping the review step. It means accepting that the first version of a workflow won't be perfect, treating early mistakes as information instead of proof the whole approach is wrong, and fixing the process as you go instead of waiting for a flawless plan that never quite arrives.
If you're in construction or trades in the Okanagan and waiting for AI to mature before you engage with it, the math is moving against you. Waiting doesn't freeze the gap in place. The firms already moving keep compounding their head start while the ones waiting stay exactly where they started.
How to start
The starting point is a clear picture of where AI fits in your specific operation and what governance needs to be in place before any rollout.
That picture looks different for a five-person excavation outfit than it does for a 40-person mechanical contractor running three offices. Company size, how standardized your jobs are, and how much of your competitive edge already lives in one person's head all change where the first use case should be.
The categories worth scoring against are the same three that determine whether any rollout works: whether there's a clear strategic starting point, whether governance is defined before anything touches client or pricing data, and whether the team has the training and process support to make an implementation stick past the first month. Miss any one of the three and even a good tool underperforms.
The free AI Readiness Assessment is 15 questions and takes about 10 minutes. It produces a score across the areas that determine whether an AI rollout succeeds or stalls, and surfaces the use cases already hiding in your current workflows.
If a real fit exists, you'll see it. If you're better off waiting, the assessment will tell you that too.
Either way, you'll know where you stand.