Tokens are the currency of AI. Learn how they influence pricing, costs, and the value different agentic models can deliver.
AI is rapidly becoming one of the largest and most unpredictable cost drivers in the enterprise, forcing organizations to rethink how technology investments get measured, governed, and scaled.
As adoption accelerates, traditional cost models break down. AI no longer scales through licenses or compute alone, but rather, scales through tokens, the currency of AI work that links usage directly to cost and business value. AI cost structures also depend on how solutions are built and deployed, each with distinct implications for scalability, cost efficiency, and control.
For Canadian organizations, governing AI means treating this investment as a dynamic economic system, forecasting, and optimizing token consumption with the same discipline applied to capital. This challenge is amplified in a constrained economy, where innovation has to move without losing cost discipline, data sovereignty has its own demands, and ROI has to be measurable.
Those who succeed will convert AI consumption into enterprise value, aligning infrastructure, operating models, and financial governance to optimize outcomes. But without the right discipline, efficiency gains will fuel more usage and higher costs, eroding the value they were meant to create.