CBJ JUNE 2026

19 CANADA’S AI ECONOMY: GOVERNANCE, TRUST, AND THE FUTURE OF WORK JUNE 2026 « The Canadian Business Journal 18 While this can increase flexibility and entrepreneurship, it also raises questions about income stability, benefits, and long term financial security. The structure of employment may therefore shift toward a mix of traditional firms, independent workers, and platform mediated work arrangements. The productivity and distribution question At the macroeconomic level, AI presents a familiar but unresolved challenge. Productivity gains do not automatically translate into broadly shared income gains. If AI increases output per worker while reducing the demand for certain types of labour, the distribution of income between capital and labour may shift. This could lead to higher returns for firms and investors while wage growth for certain categories of workers slows. The overall size of the economy may expand, but the distribution of benefits becomes more uneven. The key policy question for Canada is therefore not only how to encourage AI adoption, but how to ensure that the gains from productivity are widely shared across the labour market. The data centre and infrastructure dimension Although AI is often described as a digital transformation, it is heavily dependent on physical infrastructure. Data centres, semiconductor supply chains, and electricity systems form the backbone of AI deployment. In Canada and globally, investment in data centres is expanding rapidly. However, there is a distinction between announced projects and fully operational capacity. Many facilities move slowly through stages of permitting, construction, and grid connection. This means that the pace of physical buildout can lag behind expectations generated by investment announcements. This infrastructure expansion has important economic consequences. During construction phases, it creates demand for skilled trades, engineering, and related labour. However, once operational, data centres require relatively small permanent workforces compared to the scale of capital investment. This creates a pattern where employment effects are significant in the short term but limited in the long term. At the same time, the growth of data centres places pressure on energy systems. Electricity demand becomes a central constraint on AI expansion. In some regions, the speed of grid expansion and energy availability determines how quickly AI infrastructure can scale. This links the future of AI directly to Canada’s energy policy and infrastructure planning. A transition still taking shape Canada is not experiencing a sudden disruption in employment, but a gradual restructuring of work. AI is reshaping tasks, compressing some job categories, expanding others, and creating new hybrid roles that did not previously exist. At the same time, physical infrastructure constraints, regulatory uncertainty, and labour market frictions are slowing the pace at which these changes are fully realized. This creates a period of adjustment in which productivity, employment, and wages may not move in alignment. The future of work in Canada will not be defined by a single outcome. It will be defined by how effectively institutions, firms, and workers adapt to a system where intelligence is increasingly abundant, but the ability to integrate, govern, and distribute its benefits remains the central challenge.