Your estimators, project managers and coordinators spend hours every week reading, searching and retyping documents. That is where AI pays off first in construction, and it only sticks when your people change how the work gets done, not just which tools they have open.
Construction is one of the last industries in Canada to put AI to work. In Statistics Canada's spring 2026 business survey, 9.2% of construction businesses said they had used AI to deliver their work in the past year, against 19.2% of all businesses. Only agriculture and wholesale trade were lower. The intent has moved faster than the use: the share of construction businesses planning to use AI in the next year went from 3.2% in 2024 to 18.3% in 2026 (Statistics Canada).
Your peers already believe the case: 90% of Canadian construction leaders agree tools like AI can lift efficiency, and 53% call AI a priority (CCA and KPMG). But belief is cooling into realism. Autodesk found the share of construction leaders expecting AI to improve the industry fell from 80% to 68% in a year, as firms hit the hard part: making it work on real projects (Autodesk).
The pressure behind all of this is people. BuildForce Canada projects the industry needs to hire 306,200 workers by 2034, mostly to replace retirements, and could still be short as many as 34,300 (BuildForce Canada). AI will not frame a wall or pull cable. It can give your estimators, PMs and coordinators back the hours they lose to paperwork, so the senior people you have can carry more work.
That is also where the analysts say the near-term value sits. McKinsey estimates AI could automate 39% of non-physical work in construction, and puts bid/no-bid analysis, estimating and proposal drafting in the first wave, ahead of anything on the jobsite (Construction Dive, reporting McKinsey). The office side of your business is where to start.
of Canadian construction businesses used AI in the past year, versus 19.2% of all businesses
Statistics Canada, 2026 ↗of construction businesses plan to use AI in the next 12 months, up from 3.2% in 2024
Statistics Canada, 2026 ↗construction workers the industry needs to hire by 2034, mostly to replace retirements
BuildForce Canada, 2026 ↗of Canadian construction leaders say the labour crunch limits their ability to bid or meet deadlines
KPMG in Canada and CCA, 2025 ↗Most AI advice is written for office businesses with clean data and one system of record. Contractors don't work that way, and the advice breaks in predictable places.
Each job has a different owner, spec, site and team, so "automate the repetitive work" sounds like it doesn't apply to you. It does: the repetition hides inside the documents: prequalification forms, résumés, project sheets, submittal packages, RFIs, change orders and progress claims. That is where AI earns its keep.
The best answer to a bid question is usually in a submission from four years ago, a closeout binder, or the head of a superintendent who retires next spring. It sits across your project management system, your accounting system and a decade of shared drives. A chatbot without that history gives generic answers.
Under a stipulated price contract, a missed spec requirement or a wrong quantity is your problem, not the software's. That doesn't mean keeping AI away from estimating and submittals. It means designing the human check into the workflow, at the step where an error would cost you, before anything leaves the building.
Estimators live in spreadsheets, PMs live in email, and superintendents and foremen work from a phone on site. A Copilot rollout planned for head office tends to miss the field entirely. Field use needs short, specific tools, like an incident classifier or a procedure lookup, that answer one question well.
Owners, consultants, subtrades and suppliers all send you documents in their own formats, on their own deadlines. In Ontario, prompt payment rules require payment within 28 days of a proper invoice unless a notice of non-payment goes out within 14 days (OAA). AI that helps a contractor has to handle what comes in from outside, on the clock, not just what your own team writes.
Start where your people read, search and retype the most. In most general contractors and trade contractors that means business development and preconstruction first, then project administration, then safety. These are builds we have delivered, written up in full in our Use Case Explorer. Quantity takeoff belongs on this list too: see the Laframboise story below.
Upload the RFP and the tool pulls out the requirements and scoring criteria, scores whether it's worth pursuing, and drafts a response from your past winning submissions. A checklist confirms every requirement is answered. That matters most in the weeks when three bids close at once.
Bid teams know the right paragraph exists; finding it under a deadline is the problem. This build turns your proposal archive, staff résumés and project references into one searchable home that drafts new submissions. It is the kind of build behind the Buttcon story below.
Owners want proof you've built this before, with this team. The tool ranks your completed projects against the selection criteria and produces project sheets ready to send. You can ask, in plain language, for a project manager and superintendent who have delivered a hospital or a school together.
ICI and civil work is spread across public portals, owner sites and private invitations, checked whenever someone has time. This build watches every source on a schedule, scores each opportunity against the work you actually do, and puts one ranked list in front of your team each morning, in English and French.
Senior estimators shouldn't spend their week typing standard hours into an old spreadsheet. A build we've delivered fills standard hours automatically, predicts variable hours from past jobs and puts a confidence rating on every estimate. The same approach fits mechanical, electrical and specialty contractors pricing self-performed labour and service work.
Coordinators compare shop drawings and equipment submittals against the drawings and schedules sheet by sheet. An agent loaded with your review guide lists every mismatch for a person to confirm; in its first session it caught a real equipment discrepancy. Fewer rejected submittals means fewer weeks lost waiting on resubmission.
Deciding whether an incident meets your serious-incident criteria meant rereading about 20 pages of guidance, and different people reached different answers. A safety manager built an agent, with our coaching, that applies your own criteria and explains its reasoning in seconds. A person still makes the call, now with a consistent, auditable starting point.
Decisions from owner, consultant and subtrade meetings get explained out loud and then lost. Copilot can search your recorded Teams meetings and return the decision with its context, instead of someone rereading weeks of notes before a change order discussion.
The tools are rarely the problem. A DEWALT survey of construction professionals, reported by the Daily Commercial News in 2026, found only 9% use AI as part of their day-to-day work, while 39% are piloting (DCN). That gap is about people and process. Four patterns come up most.
Everyone got Copilot or ChatGPT, a lunch-and-learn showed them how to summarize an email, and usage faded. Nobody showed the estimator how it changes a bid, or the coordinator the RFI log. Our AI-First Moments workshops fix this by having people bring their own workflow, a live bid or a real submittal, and rebuild it in the room.
A sharp estimator or a tech-minded PM builds something useful. Nobody else uses it, and it leaves when they do. Spread happens through people: an AI Ambassador network with a named person in each department and region, and builder cohorts that teach more of your staff to build, so good ideas become shared tools.
Training happens in the boardroom, on office examples, and superintendents and foremen tune out. The field needs short, specific uses, practised until they become habit. That is what the six-week AI Habit Builder is designed to do: small behaviours, repeated, measured on the work itself.
The owner or board asks "what's our AI plan?", but the executive team doesn't use the tools, and PMs read that as permission to keep doing it the old way. In a risk-aware industry, people copy what leaders do. Our six-week leadership sponsorship work puts AI into the executives' own decisions and meetings, and sets targets in cycle time and capacity created.
This assumes you have some licences and a few experiments. Prove value on live projects early, then scale what worked. It follows our Three-Layer AI Playbook.
You don't need a 40-page AI policy to start. You need clear answers on four things specific to construction in Canada.
Drawings, specs and tender documents arrive under contract terms, and public owners often add confidentiality and privacy clauses through their supplementary conditions to CCDC 2. The City of Waterloo's, for example, binds the contractor to MFIPPA (City of Waterloo). Keep client documents in tools that run inside your own tenant, and read the supplementary conditions before a new tool touches a project.
Microsoft 365 Copilot answers from anything a user already has access to. In most contractors that includes old project sites, shared bid folders and the odd HR spreadsheet left open to everyone. Microsoft's own deployment guidance starts with fixing oversharing before broad rollout (Microsoft Learn). Do that clean-up first; it is cheaper than explaining a leak.
A quantity, a schedule of values or a notice of non-payment carries your firm's liability, whichever tool drafted it. Every build should show its source, make a person confirm the output at the step where errors cost money, and keep a record of who approved it. Design work under a professional seal stays with the professional of record.
Résumés, incident reports, timesheets and certifications are personal information. Canada's privacy regulators have been clear that existing privacy law applies to generative AI (Office of the Privacy Commissioner of Canada). And if you build for hospitals, school boards or municipalities in Ontario, Bill 194 lets the province require those institutions to put accountability frameworks and oversight around their AI use (Legislative Assembly of Ontario). Expect those clients to start asking how you use AI on their work.
Two construction firms, and one engineering firm that bids and delivers much like you do.
“Our first build changed how we pursue work. Our proposal content, resumes, and project history now live in one place. Our team can research, draft and build submissions much faster than before, with better consistency. ForwardPath took the time to understand how our business actually bids, and we’re already looking at what’s next with them to find and qualify tenders earlier.”
A general contractor that put its proposal content, résumés and project history in one place and now builds submissions much faster, and is looking at finding and qualifying tenders earlier.
“We transformed a laborious, manual quantity takeoff and data entry process into something fast and accurate that takes just minutes.”
A construction firm that turned a manual quantity takeoff and data entry process into one that takes minutes, the clearest example of AI paying off in preconstruction.
“ForwardPath has delivered AI tools that our teams use every day. More departments keep adopting these tools, and ForwardPath has been a reliable, long-term partner every step of the way.”
An engineering and consulting firm that bids for work like a contractor does, where proposal generation and tender discovery spread from one team to more departments.
Ask these of your own team, and of any partner pitching you. Vague answers are a signal.
If nobody can say how long a proposal, takeoff or submittal review takes now, nobody will be able to prove AI made it faster.
AI projects owned by IT alone tend to produce tools nobody asked for. The chief estimator or the PM lead should own the outcome.
Bid pricing, subtrade quotes and HR files sitting on open sites become searchable the day licences go out.
Every build should name the review step. That protects you on price, contract and safety, and it builds trust with the people using it.
Your bid history and project data are an advantage your competitors can't copy. Keep the tools and the data under your control.
If the plan has nothing for superintendents and foremen, half your company is out of it from day one.
Capacity created only counts if it goes somewhere: more bids answered, more projects per PM, less overtime at month end.
Mostly in the office, not on the jobsite. The practical early uses are drafting proposals and prequalification responses, finding past projects and résumés for bids, watching tender portals, automating quantity takeoff and data entry, checking submittals against drawings, and answering safety and procedure questions. Statistics Canada found only 9.2% of construction businesses used AI in the past year, so most firms are still early. The ones getting value picked a few document-heavy workflows and changed how that work gets done.
Start with the workflow where your senior people lose the most hours to reading, searching and retyping, and where you can measure the before and after. For most general contractors that is proposals and prequalifications, followed by takeoff, submittal review and project administration. Pick three to five workflows, name an owner for each, record a baseline, then prove one on a live bid or project within 90 days before you scale.
It can take most of the manual effort out of them. Laframboise Group, a construction firm we worked with, turned a manual quantity takeoff and data entry process into one that takes minutes. The right design still has an estimator review the quantities before they go into a price, because under a stipulated price contract the number is yours. Treat AI as the fast first pass and your estimator as the final check.
Not into public consumer tools. Owner and consultant documents arrive under contract terms, and many public owners add confidentiality and privacy clauses. Use tools that run inside your own Microsoft tenant, with your existing permissions, and fix overshared SharePoint and Teams sites first. A one-page rule on what goes into which tool, plus approved builds in your own environment, covers most of the risk without slowing people down.
Not in an industry that BuildForce Canada says needs to hire 306,200 workers by 2034. The realistic effect is that each estimator, PM and coordinator spends less time on paperwork and more on judgement: pricing risk, managing subtrades, dealing with the owner. That lets the experienced people you have carry more work, and helps newer staff get up to speed faster, which matters as senior people retire.
Habits and quick wins can show up within weeks when people practise on their own work. Custom builds take longer: the builds on this page range from a few days for an agent built during coaching to about six weeks for a proposal archive and three to four months for tender discovery or estimating tools. Measure in cycle time and capacity created, such as hours per proposal or days per submittal, rather than how many people logged in.
Start with a conversation with our leadership team. We’ll look at where you are, where AI can move the needle first, and what your next 90 days could look like.
Figures are quoted from the sources above as published. Use cases describe builds ForwardPath has delivered; client names appear only with permission.