This month, the federal government released AI for All, a national AI strategy that is underpinned by real ambition: $2.3 billion in funding, a target to lift business AI adoption from 12 per cent to 60 per cent by 2034 and a clear commitment to data sovereignty. For anyone working at the intersection of technology and physical industry in this country, there is a lot to welcome here.
Transportation is named as a priority sector, and that is the right call. The movement of goods and people is foundational to every other sector on the government’s list: health, energy, agriculture, manufacturing. AI is already changing how fleets operate, how drivers are protected and how businesses measure and reduce their environmental footprint. Getting the transportation sector right will have compounding benefits across the entire economy.
What we should not be doing is wasting money developing our own AI if that means building AI models or constructing data centers from scratch. The government’s priority should be to keep our options open: don’t commit to any one vendor or technology, and instead spend the effort and money on incentivizing Canadian companies to improve our productivity gap by leveraging the AI that is already available.
The big tech players, the hyperscalers, are investing in a way that Canada cannot match and trying to keep up technically would risk burning money without delivering a meaningful advantage. The four largest hyperscalers, Google LLC, Microsoft Corp. , Amazon.com Inc. and Meta Platforms Inc. , are expected to spend more than US$700 billion on AI infrastructure in 2026, while Canada’s national AI strategy has a budget of $2.3 billion over five years. Trying to compete on these terms is not realistic. Rather than owning every server, we should be more concerned about controlling the data that runs on them, where it lives, who can access it and the legal framework.
The strategy can also be strengthened in its implementation. Voluntary certification for AI is a reasonable starting point for many applications, but transportation involves AI operating in environments where safety is essential: braking decisions, driver monitoring and hazard detection on highways in difficult conditions. Far from being a burden on innovation, a minimum standard for safety, data quality and accountability are what responsible deployment requires.
The provinces are already moving in this direction. British Columbia passed legislation last month mandating cameras in commercial trucks. The United States will by next year require new heavy trucks to be fitted with automatic emergency braking technology that depends on forward-facing AI video camera technology . Federal leadership on what responsible AI looks like in these environments would give industry clarity and it would give Canadians confidence.
We also need a clearer position on connected vehicle data. As vehicles become more AI-enabled, there is a real risk that data will become fragmented across proprietary systems. That in turn could render the data inaccessible to the businesses that generate it and incompatible across platforms. Establishing interoperability standards early, before the ecosystem hardens, is the kind of infrastructure decision that shapes an industry for decades to come.
Finally, the strategy is understandably focused on opportunity. But workers in transportation — the drivers, the dispatchers and the fleet managers — are asking valid questions about what AI means for their roles. A national strategy that speaks directly to how AI augments rather than displaces the people currently doing this work would go a long way toward building the public trust that the strategy itself identifies as a gap. Only 26 per cent of Canadians currently feel excited about AI. Addressing that shortfall in confidence is as important as closing the adoption gap.
These are the natural next questions that follow a strong opening commitment. Canada has the talent, the data, and the industrial base to deliver on this strategy. What it needs now is a government willing to move from vision to decision: sector-specific implementation plans, a regulatory framework for AI in areas where safety is critical and timelines that can be both measured and met. The private sector is ready to move. The question is whether policy will keep pace.
Neil Cawse is the founder and CEO of Geotab