Growth conversations often begin with capital, though investors are only part of the picture. Non-dilutive funding such as grants increasingly plays a role in how growing companies finance hiring, product development and expansion.

When Evan Solomon, Canada’s first Minister of AI and Digital Innovation, joined SAAS NORTH in late 2025, the conversation centered on a bigger question: could Canada move beyond AI research leadership and become a place where enduring AI companies are built?

The best ideas in SaaS often take shape through conversation, on stage, between sessions and in the moments where operators compare what they are seeing in real time. Across those discussions, a consistent pattern has started to emerge.

Inside many companies, AI hasn’t arrived all at once. It has been showing up in small ways, a tool here, a workflow there, gradually finding its place inside day-to-day work. What follows is rarely a clean transformation.

For years, SaaS growth followed a simple equation: more people meant more seats, more licences, more revenue. Now, as AI begins to absorb work that once required teams, that relationship is starting to break.

Product teams today can build faster than ever. Tools like Claude Code and AI copilots have compressed development cycles and lowered the cost of execution. What hasn't changed is the harder part of product work.

When a company crosses the billion-dollar revenue mark, it is tempting to focus on the milestone itself. What often goes unexamined is the operating discipline, the cultural decisions and the structural rigor that made that milestone possible.

Across startups, a simple question keeps coming up: how much of this work still needs a human? Recent shifts, including tools like Claude Code, have accelerated what small teams can realistically build and automate, changing expectations across roles and workflows.