POLICY BRIEF
June 2026
Vivian Li
Viet Vu
André Côté
This brief is part of the Dais’ portfolio of work with the Future Skills Centre, which is funded by the Government of Canada’s Future Skills Program.
The opinions and interpretations in this publication are those of the author(s) and do not necessarily reflect those of the Government of Canada.
For educators in Canada’s primary and secondary school systems, the emergence of generative artificial intelligence (AI) tools like ChatGPT has caused immediate disruption in the classroom and angst about longer-term implications. While some educators are embracing AI as a potentially transformative tool for teaching and learning, others feel unequipped for the pedagogical and job impacts. How should educators address AI’s threat to academic integrity, or students’ acquisition of essential skills like writing and critical thinking, when these tools complete assignments in seconds? How should educators take advantage of these powerful tools, and put them to productive use in day-to-day work? And will AI diminish their professional expertise, automate core tasks, and eliminate jobs, as in other sectors? The educational community is navigating uncharted territory, where the potential for both disruption and transformation feels equally profound.
To understand how AI could impact education workers, this policy brief uses the Dais’ unique methodology introduced in Right Brain, Left Brain, AI Brain to assess how exposed jobs are to AI, and whether these technologies are more likely to either assist or automate job tasks. The analysis covers six major occupations in education, including elementary and secondary school teachers, school principals and administrators, early childhood educators and educational counsellors.
In sum, this analysis suggests that education workers are more likely to encounter AI in their jobs, but the nature of their job tasks are more likely to be assisted than automated by AI technologies.
While highly generalized, the analysis offers a starting point for deeper exploration of specific types of AI applications, opportunities and impacts in the K-12 sector through further research and direct engagement with educators and administrators. Tasks in education occupations typically require planning, managing, interpersonal engagement with staff and students, and other tasks requiring judgement and “soft” or social-emotional skills, which are less likely to be automated.
Across the six education occupations analyzed, we identify tasks that are more likely to be assisted by AI than to be replaced or automated. For example, AI applications could assist primary and secondary school educators with preparing lesson plans (writing and structuring teaching material), synthesizing secondary information in teaching materials, writing quizzes and tests, or with more advanced applications like building an interface (agent) for students to offer personalized support with coursework. For principals, assistive AI applications could include drafting newsletters or communications, assessing teaching plans, or summarizing and analyzing curriculum materials.
This policy brief applies an analytical approach established by the Dais in previous research to assess core occupations in Canada’s K-12 education sector workforce for their exposure to AI (i.e. the probability of interacting with AI systems in day-to-day work), and complementarity to AI (whether usage of AI is more likely to assist the worker with common tasks, or to replace those tasks).
The research adapts leading techniques in economics for assessing AI occupational exposure and complementarity at the job task level, applying them to the more than 500 occupations in Canada’s National Occupational Code (NOC). Employment counts are based on Statistics Canada 2021 Census data. See the Dais’ Right Brain, Left Brain, AI Brain study for a detailed overview of methodology and data.
The first studies of job exposure to AI technologies were published a decade ago, in the context of a rapid rise in prominence of machine learning algorithms. They built on the economic literature describing how automation technologies replace human labour, emphasizing “task-based” automation where technologies impact specific tasks rather than entire jobs. This analysis has been updated to include the new generation of large language models (LLMs), powering chatbots like OpenAI’s ChatGPT, and other AI tools.
Canada’s K-12 workforce is sizeable but less diverse in job mix than other sectors of the economy, concentrated in a few larger occupational groups. The six occupations profiled in the brief capture a total workforce of 839,780, distributed across the 13 provinces and territories (see Table 1).
Table 1: Overview of six educational occupations (2021 Census)
| Occupation | Employment | Average Income |
|---|---|---|
| Elementary School and Kindergarten Teachers | 320,810 | $63,510 |
| Early childhood educators and assistants | 247,860 | $26,780 |
| Secondary school teachers | 165,015 | $70,110 |
| Other instructors | 43,700 | $16,110 |
| School principals and administrators of elementary and secondary education | 32,970 | $106,660 |
| Educational counsellors | 28,425 | $59,800 |
Figure 1 situates these education occupations (blue dots) across the exposure- complementarity index alongside other occupations (pink dots) in Canada’s labour force.
Please refer to the appendix for a more granular summary of key characteristics (i.e. typical roles, job titles, and duties / tasks) of four of the occupations profiled above from the federal government’s National Occupational Classification (NOC).