Not for most day-to-day uses — real Canadian data shows businesses respond to AI mostly by training the staff they already have.
Short answer
Not for most day-to-day uses. Statistics Canada’s own survey of Canadian businesses shows they overwhelmingly respond to AI adoption by training the employees they already have, not by hiring specialists — though a smaller group does build up technical, in-house skill deliberately.
In the second quarter of 2026, Statistics Canada found that “Of businesses that reported AI usage in the last 12 months, over 2 in 5 (44.4%) businesses made changes in training or staffing practices due to AI use. Almost one-third reported AI-related training for existing employees (32.0%) and more than one-fifth reported AI-related training for existing executives (21.6%)”. The gap is wider at larger employers, where budget is not the constraint: among businesses with 100 or more employees, “68.1%” reported training existing employees and “51.7%” training existing executives, against “32.8% hired employees with AI-related skills and 30.2% used external consultants or vendors”. Training the people already on staff outnumbers hiring dedicated technical talent by roughly two to one, even where hiring is affordable.
This holds for using a tool someone else already built — a chat interface, an AI feature added to software you already run. It stops holding once you are the one deciding what an agent is allowed to do, or connecting it to your own systems: configuring scope, testing an integration and reviewing what an agent produces generally does call for a technical layer, at least to check the work, even if it does not require the person using the finished tool to have that background.
It also is not evenly true across industries. The same StatCan survey asked businesses that have not adopted AI what is holding them back, and found “lack of skilled workers was a barrier for businesses in information and cultural industries (20.9%) and manufacturing (12.0%)” — so while training an existing generalist is enough for most everyday uses, a real skills shortage is a genuine barrier in specific sectors, and it is worth checking which situation a given business is actually in before assuming either answer.
A plan-source note: the industry code sometimes cited for this question addresses developer and manager risk-management training, not end-user technical skill — StatCan’s own survey data is the better source, and it directly answers the question. See the plain-English guide to how AI works and where AI fits in everyday work.
See how a roadmap sequences training against hiring.
