---
id: "lib-2026-07-30-genai-tools-among-canadian-workers"
type: "library"
title: "GenAI tools among Canadian workers"
lang: "EN"
org: "Statistics Canada"
source_type: "Report"
date: "2026-07-30"
week: "2026-W31"
url: "https://nosov.ai/library/lib-2026-07-30-genai-tools-among-canadian-workers/"
original_url: "https://www150.statcan.gc.ca/n1/daily-quotidien/260730/dq260730b-eng.pdf"
tier: "A"
tier_name: "Strong evidence"
tier_reason: "Official national statistics from Statistics Canada, based on a supplement to the Labour Force Survey with significance testing at the 95% level, the first release in a regular series."
summary_basis: "full-text"
original_minutes: "12"
tags: ["adoption"]
---

# GenAI tools among Canadian workers

Tier A (Strong evidence): Official national statistics from Statistics Canada, based on a supplement to the Labour Force Survey with significance testing at the 95% level, the first release in a regular series.

Summary based on the full text.

## In short

Statistics Canada released on 30 July 2026 the first results of a new series on AI use by workers, based on supplementary questions to the March 2026 Labour Force Survey. Just over one in three workers (35.9%) used generative AI at work in the past year, but most use it for some tasks only, and only 11.6% of users apply it to most or nearly all tasks. Use is concentrated in management, science, finance and professional services, and the most common reason for not using it is that it does not fit the work.

## Key numbers

- 35.9%: Canadian workers aged 15-69 who used generative AI at work in the 12 months to March 2026
- 11.6%: users applying generative AI to most or almost all of their tasks
- 56.0%: non-users who say generative AI has no applicability to their work
- 75.1%: generative AI use among workers in management occupations

## What it reports

- 93.4% of workers are aware of generative AI tools; 51.5% are familiar with how they apply to their current work, 15.0% very familiar.
- 41.6% used at least one AI or automation technology in their main job in the past 12 months; generative AI was the most common at 35.9%.
- By industry: professional, scientific and technical services 65.6%, finance and real estate 59.2%, education 53.0%, public administration 44.9%; lowest in accommodation and food 16.3% and agriculture 17.5%.
- By occupation group: high exposure and high complementarity 53.8%, high exposure and low complementarity 45.9%, low exposure 14.2%.
- Men use generative AI more than women in exposed occupations: 52.9% vs 41.2% in high-exposure, low-complementarity jobs, an 11.7-point gap.
- Intensity among users: 63.5% moderate (some tasks), 24.9% minimal, 8.0% most tasks and 3.6% almost all tasks. 31.4% use it daily and 38.3% a few times a week.
- Non-users (64.1% of workers) cite no applicability (56.0%), no interest (21.6%), security, privacy, environmental or ethical concerns (9.8%), lack of skills (5.8%) and company policy (5.0%). Only 3.8% cite lack of structured training from the employer.
- Private sector employees use it less (33.4%) than public sector employees (41.2%), but within exposed occupation groups the gap disappears.

## How they got it

Supplementary questions to the March 2026 Labour Force Survey for workers aged 15 to 69 in the provinces. Occupations are grouped with the complementarity-adjusted AI occupational exposure index (Felten, Raj and Seamans; Pizzinelli et al.). Differences reported are significant at the 95% confidence level.

## Limits

- Use is self-reported and measured as any use in 12 months, which says nothing about productivity effects.
- The release does not give the supplement's sample size.
- A single wave; trend data start with the September 2026 collection.

## Why it matters for companies

This is one of the few population-level baselines from a national statistics office, useful for checking vendor surveys that report near-universal adoption. The gap between 35.9% use and 11.6% broad use shows that most workers have added AI to a few tasks rather than reorganised their work. That more than half of non-users say the tools do not apply to their job, while few cite training, suggests that adoption programmes built around training alone address a minor barrier.

Original: https://www150.statcan.gc.ca/n1/daily-quotidien/260730/dq260730b-eng.pdf