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Race Alongside the Machines:

Occupational digitalization trends in Canada, 2006-2021

November 2022

Race Alongside the Machines: Occupational digitalization trends in Canada, 2006-2021


Ibrahim Abuallail

Ibrahim Abuallail

Viet Vu

Viet Vu


  • Sean Mullin
  • Mark Hazelden
  • Anusha Arif
  • Nina Rafeek Dow
  • Mariana Rodrigues


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Executive Summary

Machines are here to stay, and there’s no turning back. But technology doesn’t have to be a force that “happens” to us. When implemented in a way that centres workers and their efforts, coupled with skills training investment, technology and automation can augment and complement workers, not replace them.

Jobs that once required little to no digital skills are increasingly requiring workers to adopt them into their day-to-day work tasks. Production outputs, resource needs and labour patterns are perpetually changing, and these changes require new thinking on how we prepare Canadians for the future of work.

This report offers a comprehensive look into how technology has impacted jobs and workers in the last 15 years. This information is designed to serve as a tool to understand the projected impact of technology on worker outcomes in Canada to ensure that we get the best and avoid the worst of technology-driven innovation.

In our 2019 report, Who Are Canada’s Tech Workers, we developed an analytical framework to define technology workers. Now, we combine that framework with the National Occupational Classification (NOC). We use these to measure digital intensity and the rate of change in digital intensity across all occupations in Canada in the past 15 years, from 2006 to 2021. As the NOC lacks detailed data on the skills needed to perform each job, we use a crosswalk with the American equivalent, O*NETOnLine.

The results show that technology adoption has touched every single occupation in Canada—but differently. Our data supports global evidence that over the past 15 years, jobs requiring more routine tasks have overwhelmingly advanced in digital adoption as routine tasks were replaced with technology. But cloud computing, artificial intelligence, the Internet of Things (IoT), and big data are among the growing innovations in digital technology that are shifting the influence of digitalization to occupations that had previously been overwhelmingly non-routine.

Top six takeaways

  1. In the last 15 years, occupations associated with routine work saw the highest rates of digitalization. Jobs with the highest rates of digitalization were those that managed data, i.e., property managers, health information management, railway conductors, and scheduling coordinators.
  2. In the last five years, however, jobs most associated with non-routine work are the top movers in digitalization. The top occupations identified were photographic and film processors, physicians, and engineering inspectors.
  3. Digital technologies assist workers with carrying out work requiring a high level of reasoning and analytical skills. Workers who used technology to perform routine tasks saw more independence and autonomy in how they carried out their work, leaving them to focus on tasks that required more analytical thinking and higher reasoning.
  4. The fishing and agriculture sectors stand out as laggards in digital adoption. Fishing and agricultural sector occupations had the lowest rates of digitalization, likely due to a wave of technological advancement that already happened in the 1990s, followed by stagnated progress since then. These sectors will need to adopt IoT and Cyber-Physical Systems (CPS) to prevent illegal, unreported, and unregulated fishing and become more sustainable. 
  5. Pilots and translators were leading occupations for digital adoption between 2006 to 2016. During the 2016 to 2021 period, however, their pace of digitalization fell so significantly that compared to other occupations across the total (15 year) period examined, they present as digital adoption laggards.
  6. Digital skills in highest demand are constantly changing over the years, which has implications for worker training and risks of hyper-specialization. Malleability, critical thinking, and general knowledge across skills are vital to ensuring workers can adapt to the jobs of tomorrow.