A Look Inside the Boardrooms of Innovative Canadian Companies

September 3, 2026

Artificial intelligence (AI) has upended the playbook for software companies, reshaped venture capital, and created a new set of questions that boards have never had to answer before. Through it all, Brice Scheschuk, CPA, CA has had a front row seat.

As Managing Partner of Globalive Capital, Chief Strategy Officer at AI advisory firm ZeroStone and a director on numerous boards, Scheschuk operates at the intersection of innovation, capital and governance. He co-founded and served as CFO of WIND Mobile, guiding it from startup to a multi-billion-dollar exit to Shaw Communications, and is a co-founder of MindFrame Connect, a not-for-profit focused on mentorship for founders and investors.

We sat down with Scheschuk to discuss what’s dominating the conversation inside the boardrooms of some of Canada’s most innovative companies. What he described matters for CPAs, whether they’re advising innovative companies, sitting on boards, or helping clients navigate a rapidly changing environment.

The “SaaSpocalypse”

From roughly 2010 through the end of the pandemic, the software industry followed a well-understood playbook. Find a niche, build a product, go to market, scale. Rinse and repeat.

AI broke that playbook. “The software world has been completely rocked by AI,” says Scheschuk, “and where it’s really been adopted most aggressively is in coding, which is a direct drive at software.” The result is what has been called the “SaaSpocalypse”: a dramatic selloff of software stocks driven by fears that AI coding tools could enable companies to build their own custom software instead of buying it off the shelf. Software stocks lost more than $1 trillion in market capitalization in early 2026. They have since then recovered some of that ground but the recovery has been volatile. In late August, a single Salesforce earnings report sent the stock up 23 per cent, pulling the broader software sector up with it. Weeks earlier, Salesforce had been down 43 per cent on the year.

Scheschuk sees the correction as a shakeup, not an extinction event. Enterprise software with deep systems of record and sticky customer relationship are not disappearing overnight. “There’s a perception that you could just drum up an instance of a coding tool and rebuild an established software solution,” he says. “People are starting to get disabused of that notion.”

A New Growth Narrative

The expectations for how quickly a venture-backed company should grow have also fundamentally changed. In the SaaS era, the gold standard was what insiders called the “triple, triple, double, double.” A company would triple its annual recurring revenue (ARR) for the first two years, then double it each year after that. Hit that trajectory and “you were gold standard, you were on your way to being a unicorn,” according to Scheschuk.

Not anymore. “What was a triple, triple, double, double went to a 10x and 10x over two years,” says Scheschuk. “So $1 million to $10 million to $100 million. And there are about 20 examples of this.” Anthropic, Scheschuk notes, entered the year at roughly $9 billion in ARR and has recently reached $50 billion ARR, growth at a scale and speed that has never been seen before.

The result is an extreme concentration of returns. Scheschuk points to analysis from technology fund Altimeter that noted that investor returns from SpaceX, Anthropic, and OpenAI at current valuations would alone outstrip the net gains from the entire previous decade of startup investing. Whether those projections hold (SpaceX’s valuation has recently come back down to earth after hitting over $2 trillion in June) what is more important is what they illustrate: venture returns have increasingly become more concentrated in fewer companies. “We have never seen a more concentrated environment,” Scheschuk says.

This concentration has cascading effects across the ecosystem. Capital is flowing toward fewer deals that grow faster at much higher valuations, leaving behind a broad set of companies that would have been financeable just a few years ago. According to RBCx data, capital has concentrated sharply: the top five Canadian VC funds now capture 80% of all capital raised, up from 46% in 2023. Fewer early-stage companies are seeking funding as a result, with the number dropping from 162 in January 2025 to just 61 by March 2026. Recent data from the Canadian Venture Capital and Private Equity Association (CVCA), released in August 2026, showed that deal count continues to fall while total dollars increase: more money is going to fewer companies. For founders without existing relationships at the right firms, raising has become significantly harder. As Scheschuk puts it, "a key role of the board is thinking through runway and burn and growth." That thinking now must account for a very different capital environment.

A Tougher Exit Environment

The exit environment has gotten tougher too. The same forces compressing multiples and concentrating capital are making it harder for PE and venture-backed companies to find a path to liquidity. PitchBook data shows that private equity firms are currently holding on to 33,575 unsold companies in their portfolios and would need approximately nine years to clear their current backlog at the current pace of exits.

Scheschuk sees this playing out across boards in Canada as well. “PE exits and PE multiples and the number of companies that haven’t been cycled is much higher,” he says. “Some of that might be AI, and some of that might be the fact that PE got a little too aggressive in the last 10 years and they now have a backlog to deal with.”

For software companies in particular, the path to exit has narrowed. A growth rate that would have supported a healthy exit a few years ago may no longer be enough. Boards that once focused on optimizing for the next funding round or a strategic acquisition are now asking more fundamental questions: is the company growing fast enough to attract a buyer at all?

What AI Native Companies Look Like

While many companies are still figuring out how to adopt AI, a new class of company is being built using AI from day one. These “AI-native” companies, firms that have either started in the AI era or pivoted entirely to build their products, operations and go-to-market strategies with AI, are operating in ways that Scheschuk finds remarkable.

“I can’t believe how small they are in terms of headcount and what they’re able to deliver in terms of quality of product and go-to-market,” he says. These companies are lean by design, aggressively optimizing costs, and moving at a pace that established businesses struggle to match.

Scheschuk brings what he sees in these AI-native boardrooms directly into his work with more established companies, pressing hard on the questions: how do you get from where you are now to something closer to AI-native? Adoption in established businesses, however, has been slower than he expected. Through his work Scheschuk sees many companies with large software development functions that haven’t yet adopted AI-assisted coding tools, and he views that as a red flag.

The issue starts at the top. Successful AI adoption requires CEO-level championship. Companies that get it right are building dedicated enablement functions, sharing ROI stories internally, and creating incentive structures around AI adoption.

Dual-Use and the Shift to Deep Tech

Scheschuk is also tracking a significant shift in where innovation capital is flowing. “I have never heard the words ‘dual-use” so often as over the last year.” Across the venture landscape, more and more investments are being evaluated for dual-use potential; technologies that serve both a commercial market and a defence application. The defence case opens up significant government revenue alongside the commercial opportunity, and with defence spending increasing globally, the appetite is enormous.

This is part of a broader tilt toward deep tech (companies built on complex science and engineering, spanning areas like hardware, energy, life sciences, and defence) as investors seek more durable revenue streams than software alone can offer. A Celesta Capital analysis puts the current figure at 36% percent. These are harder businesses to finance, but their competitive moats, grounded in physical infrastructure, proprietary science, and regulatory barriers, are far more defensible than a point-solution software company that could be disrupted by the next AI release.

Rethinking Board Composition

This all leads Scheschuk to a pointed view on who should be sitting around the boardroom table. In his eyes, boards are over indexed on traditional governance expertise and under indexed on people who understand the technology that is reshaping the economy. “Your Board should include people who understand something about paradigm-shifting technology, who can ask the right questions, who can take actually take answers that they understand and challenge the CTO,” he says.

If he were vetting prospective Directors, Scheschuk says he would push them on how they’re personally using AI, whether they can name the leading AI coding and productivity tools, and whether they’ve built an agent application themselves. “I know that sounds weird to think about for the typical profile of a Director,” he says, “but I think you need some of this around the table.”

In the startup world, Scheschuk sees the board composition problem as different but equally pressing. Boards tend to get stacked with VCs, founders, then one investor, then another. The missing piece is the experienced operator who brings both strategic judgement and the governance instinct to keep the company on track without slowing it down.

The Measurer Persona

Scheschuk talks often about three personas that every startup needs: the builder (product and engineer), the seller (commercial and go-to-market), and what he calls the “measurer,” the person who brings financial discipline. It’s the measurer, he argues, that too many startups bring in too late.

This is where the CPA skill set comes into play for early stage start-ups. The measurer sets the foundational systems of record, financial discipline, and measurement frameworks that prevent companies from accumulating the kind of operational debt that becomes exponentially harder to fix later. In the venture capital model, where 80% of pre-seed and seed investments are expected to fail, it can be hard to get attention for financial discipline. But Scheschuk has seen what happens when companies skip it, and the cost of fixing it later is always higher.

Even in an era where AI can generate code, build products, and automate workflows, the fundamentals of measurement, financial rigour, and sound governance still matter. Given how fast everything else is moving, they may matter more than ever.