Opinion: AI is more than data centres

Walking into the Bay Area Economic Summit as president of MBAi, I expected the familiar headline: that the AI economy is a race to build data centres. Walking out, I was convinced that data centres are only scaffolding. The real story, and the one we keep underselling, is innovation: what we build on that infrastructure and who it serves.

That tension was visible everywhere. MP Stephen Crawford called data centres “the new engine of the economy,” and he is right that Ontario needs compute, energy and sovereign storage to compete. But an AI leaders panel featuring Garry Wood, founder and managing partner of Stone Management Partners, Prabh Kaur, KPMG Canada executive director and Sam Dutta, senior director for RBC Borealis, kept pulling the conversation back to a sharper point: “AI is not the goal — solving problems is the goal.”

Only about three per cent of organizations are seeing measurable impact, because leadership and culture are missing. As Dutta argued, the differentiator is not the model everyone can buy, it is the application of proprietary data and domain expertise to real problems. That is innovation, which is exactly what gets lost when the narrative collapses into megawatts and square footage.

Nowhere was the cost of that narrow framing clearer than in Hamilton. This month, the city’s Committee of Adjustment weighed more than 1,200 letters of opposition to a proposed AI data centre planned for downtown Hamilton, and the land severance was denied.

Innovation leaders must rebuild public trust through science communication. Transparency about water use, energy and how we plan to mitigate risks is not a courtesy; it is the precondition for building anything at all.

My second takeaway concerns the mental models we are asking people to change. Everyone wants agentic AI, but few discuss what it demands of a business. The next generation of software will not be a tool we operate; it will work in the background, reading context and making decisions from the data. For companies, this represents a shift from interacting with software to trusting something autonomous. This is a hard thing to ask of any organization, but it will be necessary if we want to transform how our infrastructure functions.

Third: rather than chasing AI for its own sake, we should pinpoint the public systems where it can do the most good. Carney’s AI for All strategy identifies a flagship health mission and better government services. Councillor Tammy Hwang pointed to Hamilton’s brownfield lands and water-cleaning technology as a way to build responsibly. Improving public infrastructure with AI lowers government costs, frees funding for other priorities and raises service quality, which, in turn, rebuilds the trust every other ambition depends on.

The summit’s closing line captured the stakes: the question is not whether AI will shape our future, but whether we will lead that future or follow it. For the Hamilton-Burlington region, leading could mean treating data centres as the floor, not the ceiling, and making innovation, trust and the public good the story we choose to tell.