What Canadian AI disruption research says

57.4% of Canadian jobs are classified as highly AI-exposed. (Source: Future Skills Centre, Canada’s Workforce in Transition, Sept 2025)

53% of tasks across all occupations are performable by current AI. (Source: Conference Board of Canada, Understanding the Influence of AI on Employment, Jan 2026, p.4)

Canadian AI adoption grew from 3.7% (2021) to 6.8% (2023) nationally. (Source: The Dais/FSC, Right Brain Left Brain AI Brain, Jan 2025)

In the CSBC table used for this project's sector-adoption gap, Manitoba sits at approximately 2%, while the national benchmark was 12.2% in Q2 2025. Statistics Canada's Q2 2026 Daily now reports 19.2% national AI use, so the Manitoba comparison should be treated as a source-vintage proxy until the sector table is refreshed. (Sources: Statistics Canada CSBC and Statistics Canada Daily, Q2 2026)

Industry exposure rankings by AI task concentration: Agriculture 76.3%, Utilities 66.4%, Professional Services 64.6%, Mining 64.2%, Manufacturing 58.6%, Finance & Insurance 57.7% — down to Accommodation & Food at 26.0%. (Source: Conference Board of Canada, 2026)

The FSC 4-quadrant framework, building on the IMF complementarity methodology by Pizzinelli et al., classifies workers by two axes: how much AI can do their tasks (exposure), and whether AI assists or replaces them (complementarity).

27% of Canadian workers are in high-exposure, high-complementarity roles where AI assists them. 29% are in high-exposure, low-complementarity roles where AI competes with them. (Source: The Dais/FSC, Right Brain Left Brain AI Brain, 2025)

High-exposure, high-complementarity examples: physicians, engineers, senior managers, nurses. Key skills: planning, leadership, coaching, critical thinking.

High-exposure, low-complementarity examples: administrative assistants, auditors, accountants. Key skills: accounting, data analysis, information filing, proofreading. (Source: The Dais/FSC, Right Brain Left Brain AI Brain, 2025)

The Conference Board of Canada projects a J-curve: approximately 535,000 jobs lost by 2030, followed by a net gain of 555,000 jobs by 2045 as productivity benefits materialize. (Source: Conference Board of Canada, 2026)

Policy Exchange identifies three preparation windows: 1–2 years to design reforms, 3–5 years to implement major changes, and 5+ years of continuous adaptation. (Source: Policy Exchange, Government in the Age of Superintelligence, 2025)

Goldman Sachs estimates that two-thirds of jobs have significant AI exposure, and that generative AI could substitute a quarter of current tasks. (Cited in: Policy Exchange, 2025)

The UK government estimates 30% of the workforce could be automated within 20 years. One in three people already believe AI could do their job within five years. (Cited in: Policy Exchange, 2025)

Steepest job posting declines between 2022 and 2024: web designers −97.9%, information services −55.6%, authors/writers −56.2%, desktop publishing −74%, customer service −54.2%. (Source: FSC, Canada’s Workforce in Transition, 2025)

Fastest-growing AI-augmented roles over the same period: conductors and composers +43.4%, early childhood educators +22.6%, dentists +25.6%, nursing supervisors +18.7%. (Source: FSC, 2025)

Policy Exchange argues for a “skills revaluation”: roles dismissed as low-skilled are more accurately described as low-paid. Physical touch, emotional intelligence, and interpersonal skills will command increasing premiums as cognitive work is automated. (Source: Policy Exchange, 2025)

OpenAI’s Industrial Policy paper projects that AI infrastructure buildout — data centres, power grids, cooling systems — will require approximately 20% more skilled trades workers than currently exist, including electricians, mechanics, ironworkers, carpenters, and plumbers. (Source: OpenAI, Industrial Policy for the Intelligence Age, 2026)

Policy Exchange recommends building UK national capacity to retrain 250,000 workers annually. This is a UK recommendation, not a Manitoba target; it is not directly transferable to Manitoba without local labour-force modelling. (Source: Policy Exchange, 2025)

Universal basic income discussions are entering the mainstream policy conversation, alongside working-hours reforms such as the 3.5-day work week. (Source: Policy Exchange, 2025)

Canada has funded 300+ active skills projects, with growing emphasis on employer-worker co-investment models. (Source: FSC Impact Report, 2025)

Services-based industries — accommodation, education, retail — gain proportionally less from AI productivity gains, and will require different transition strategies than knowledge-work sectors. (Source: Conference Board, 2026)

Policy Exchange identifies an “automation taboo”: governments tend to suppress open discussion of AI-driven job displacement due to political sensitivity, which delays preparation at exactly the moment it is most needed. (Source: Policy Exchange, 2025)