Punchcard Systems, an Edmonton consultancy that builds software and AI tools, released The State of AI at Work in Canada on October 6, 2026. Angus Reid Group ran the survey for Punchcard from September 2 to 11, polling 1,100 working Canadians and recruiting extra respondents in heavy industries, construction among them. Punchcard reports that 64% of construction workers trust AI to read technical drawings and 63% trust it to interpret Canadian codes and standards, provided they can review what it produces, while 87% have received no formal AI support from their employer. The tasks in the survey run from reports and job paperwork up to drawing review and decisions that affect worker safety.
What it does
The survey asks workers how they use AI and which tasks they would hand it. It tests no tool. For each task, respondents could say they trust AI completely or trust it with a person checking the output, and the report counts the two answers separately. The public landing page shows five of the eight heavy-industry tasks in the full report.
| Task | Trust completely (%) | Trust with review (%) | Total (%) |
|---|---|---|---|
| Routine procedures, product specs or how-to information | 9% | 68% | 77% |
| Reports, logs or job paperwork | 5% | 66% | 71% |
| Technical drawings, manuals or spec sheets | 4% | 49% | 53% |
| Safety, compliance or code requirements | 3% | 49% | 52% |
| Decisions affecting worker safety or physical risk | 2% | 27% | 29% |
Construction comes out ahead of the heavy-industry average on the technical work. Across heavy industry, 53% of AI users trust AI with technical drawings, manuals or spec sheets when both answers are counted, against Punchcard’s 64% for construction on drawings. Only 4% of heavy-industry users would take a drawing answer from AI without checking it. The release says 36% of construction workers would trust AI on decisions that affect worker safety with review, and none would trust it completely there.
The figures are most useful to an operations lead or CFO writing an AI policy for field and office staff. Punchcard counts AI training, approved tools, written rules and a named person to ask for help as formal support. Construction had the highest share of workers with none of it. (Only 6% of AI users say their organization has given them formal responsibility for AI governance or safe use.)
| Group | No formal AI support (%) |
|---|---|
| Construction | 87% |
| Agriculture | 77% |
| Heavy industry overall | 68% |
| Manufacturing | 67% |
| Transportation and logistics | 65% |
| Other industries | 54% |
Punchcard says 52% of all Canadian workers in the sample use AI for work, 49% in heavy industry and 57% in the service sector. In construction, 31% of AI users say it has affected their role, the lowest of the five heavy industries on the landing page (agriculture is next at 32%).
Evidence so far
The evidence is one survey of self-reported answers, commissioned by a firm that sells AI training and custom AI tools. Respondents were members of the Angus Reid Forum panel. Punchcard gives a margin of error of plus or minus 3.0 percentage points, and labels it as what a probability sample of 1,100 would carry, for comparison only.
The construction figures rest on a smaller group. The number of construction respondents is not on the public pages, so a reader cannot compute the margin on the 87% or the 64%, though it is wider than the full-sample figure. The bases also differ between the two documents. The release says “construction workers,” while the landing page labels its trust chart as answers from AI users. The likeliest reading is that the 64% and 63% describe construction respondents who use AI, and the full report would settle it.
So, the time and error figures cover all industries together:
- Of AI users who answered the question, 65% say AI saves them time, at an average of 6.1 hours a week, and 35% report no time saved.
- In the release, 94% say they rework AI output before they can use it, and 19% say reviewing AI work is a regular part of the job.
- Among AI users, 24% say they caught an AI error before it caused trouble, and 18% say AI output did cause a problem at work, including 3% who report a serious one such as a safety incident or a financial loss.
How to measure it on your projects
Reports, logs and job paperwork rank second on the trust list at 71%, which makes the daily report a reasonable first pilot. Track the correction rate, the share of AI-drafted daily reports that the superintendent or project manager changes for a factual error, such as a wrong crew count, quantity or location, before the report goes out. Pair it with minutes per report, since 94% of AI users in the survey rework output before they use it.
Capture the baseline before the tool goes live:
- For two weeks on one job, have the superintendent log the minutes spent writing each daily report.
- Have the reviewer note every factual correction made to those reports.
- Divide reports with at least one correction by all reports filed.
Run the AI drafts on the same job for the next two weeks and compare both numbers. Write down who checks each draft before the pilot starts, which also gives the job one of the written rules Punchcard counts as formal support.
Availability and cost
The full report is a free download from Punchcard’s site after a registration form. It adds trust figures for all eight heavy-industry tasks and compares AI support across seven heavy industries.