Canadian insurers and other financial firms were among the country’s fastest adopters of artificial intelligence (AI) over the past year, but overall business uptake remained low, raising questions about competitiveness and productivity.
According to the Canadian Chamber of Commerce’s Business Data Lab (BDL), four sectors led AI adoption between Q2 2024 and Q2 2025: professional services; finance and insurance; information and culture; and health and social assistance. Each increased AI use by more than 10 percentage points, with some rising 15 to 20%.
In finance and insurance, reported AI use centered on data analytics (41% of firms), speech or voice recognition (35%) and machine learning (31%). For insurers, that translated into applications such as pricing and risk modeling, fraud detection, claims triage, chatbots and distribution support.
Across all sectors that adopted AI in the past year, the most common changes were redesigning workflows (40%), training existing staff to use AI (39%) and purchasing cloud services or storage (26%).
Despite public anxiety about automation, BDL data indicated that AI adoption had not yet led to widespread job losses. A 2025 Abacus Data survey found 47% of Canadians were somewhat or very concerned AI would take over their job or force a career change within five years, and 70% believed some roles in their industry would become obsolete.
BDL’s Q4 2025 Business Insights Quarterly, however, reported that only 6% of Canadian businesses using AI had reduced total employment, while 89% reported no change. In finance and insurance, AI adoption increased by more than 20% over the period while employment grew by about 8%, suggesting roles were being reshaped rather than eliminated. Youth employment also held up in high‑AI‑adoption industries, despite a national youth unemployment rate of 12.8% in November 2025.
Nationwide, AI use remained limited. In 2025, only about 12–14% of Canadian businesses reported using or planning to use AI. BDL projected adoption would reach 17 to 18% in 2026, still below levels reported in several advanced economies.
In its 2024 report Prompting Productivity: Generative AI Adoption by Canadian Businesses, BDL modeled two scenarios in which Canada would reach a 50% AI adoption “tipping point” between 2027 (fast scenario) and 2030 (slow scenario). Updated projections for 2026 were tracking closer to the slow‑adoption path.
BDL has argued that faster, responsible AI adoption will be important to improving Canada’s weak productivity performance and raising GDP per capita. It pointed to four main policy levers.
On regulation, the Chamber’s 2025 B7 communiqué called for “pro‑innovation” frameworks that protect privacy and security without adding so much red tape that firms in sectors such as financial services and insurance are discouraged from investing.
On investment, one‑third of Canadian businesses cited access to finance as a barrier to adopting new technology. Suggested responses included targeted financial incentives, sector‑specific AI centers of excellence to support small and mid‑sized firms, and better access to cloud infrastructure.
On workforce, businesses flagged hiring skilled staff (35%) and retraining employees (28%) as significant hurdles. The B7 communiqué urged governments to expand AI and digital education and to support employer upskilling efforts – issues that are increasingly relevant for insurers seeking data science, model governance and AI‑literate frontline talent.
On infrastructure, BDL noted that Canada is relatively well positioned in terms of compute, talent and innovators, but warned that large‑scale data centers are expensive and should be reserved for critical, sovereign data. Policymakers were encouraged to focus on ensuring access to compute for researchers and businesses and on supporting local providers that can expand capacity in Canada.
BDL also highlighted public trust as a constraint. IPSOS surveys showed Canadians were less knowledgeable and more nervous about AI than citizens of many other countries. Because public acceptance and business adoption tend to move together, how AI is used and explained, including in underwriting, pricing and claims, is likely to influence both consumer confidence and the pace of adoption in insurance and other sectors.
