Artificial intelligence

If You Weren’t There, You Missed a Turning Point for AI in Canada

Toronto became the center of Canada’s AI conversation on November 19 at Impact AI. What made this year different was the shift from ideas to action. Companies weren’t asking “What is AI?” anymore. They were asking:

How do we operationalize it?
How do we make it profitable?
How do we get our teams ready?

Right from the first keynote, the tone was unmistakable “If you don’t start now, you’ll be left behind.” That urgency set the stage for a day filled with honest insights and bold, practical guidance from leaders already deploying AI at scale.

AI has transitioned from an exploratory phase into a core operational capability. Leaders across industries acknowledged the same shift. As one speaker put it “Customers are asking different questions than 5 years ago.” - Ron Mcintyre, Fuel Transport 

Expectations have changed. AI is becoming embedded in operations, forecasts, customer experience, maintenance strategies and financial planning.

Examples shared:
- Manufacturers applying predictive maintenance to reduce downtime
- Retailers using demand forecasting to sharpen inventory planning
- Airlines training executives on AI’s impact on their PNL
- Energy providers exploring computer vision for inspection automation

The message was clear: AI isn’t on the horizon; it’s already reshaping profitability. McKinsey finds that companies with high-performing, tech- and AI-enabled IT organizations enjoy up to 10% higher profit margins and 35% higher revenue growth than their peers. At the macro level, generative AI could unlock $2.6–$4.4 trillion in additional corporate profits each year. 

The businesses moving fastest aren’t treating AI as a side experiment; they’re building it into the very engine of how they make money. The businesses moving fastest are not treating AI as a curiosity or a simple productivity tool. They understand that meaningful implementation goes far beyond asking basic questions to ChatGPT. Real competitive advantage comes from building tailored, embedded AI systems that automate workflows, improve forecasting, optimize operations and unlock insights that are unique to your organization. And the truth is simple: every month you delay, you are leaving money on the table through inefficiency, slower decision cycles, higher costs and missed opportunities. AI is no longer about experimentation. It is about survival and acceleration.

A powerful discussion came from the recurring theme of idea overload. Attendees heard one blunt reminder “Overabundance of ideas, you need to synthesize to real projects.”

Teams are overflowing with suggestions, pilots and wish lists. But without a strategic filter, most of these ideas remain stuck in the sandbox phase. Organizations want to use AI, yet many do not know where to start or how to connect initiatives to a real business priority. This lack of direction leads to scattered experimentation and almost no measurable impact. The result is stalled projects, unclear ROI and initiatives that never move beyond early experimentation.

One panelist captured it perfectly when they said, “Don’t fall in the FOMO trap. We look at scalability.” - Ron Mcintyre, Fuel Transport. Companies need a clear strategy, defined outcomes, and a realistic roadmap; otherwise, they will continue to build pilots that never turn into operational value. This is a pattern we often see in organizations stuck in POC hell (our take on why this happens and how to escape it).

And this leads directly to the most important question leaders should be asking: “Do you have the infrastructure to support your project?”

This isn’t just a technical question. It is a maturity question. Infrastructure means good data, clear ownership, integrated systems, cross-functional alignment, governance and leadership clarity. Without these elements, even the best ideas cannot take flight. They stall, they lose momentum and they never evolve into the operational value the business expects.

One of the standout moments came from an Alectra energy-sector speaker who reminded everyone, “Your data is your IP. So clean it out.”- Alectra. It was a simple line, but it hit the room hard because it captured the core truth behind every successful AI initiative. AI depends on data that is clean, consistent and well structured. If the data feeding your systems is chaotic, your AI will be chaotic as well.

Across industries, a familiar set of challenges continues to undermine AI initiatives: missing values that break models, forgotten legacy databases with no clear ownership, conflicting definitions across teams that lead to incompatible outputs, shadow data controlled by a single department and invisible to others, and a lack of documentation or governance that leaves no one accountable for quality. These issues may appear small in isolation, but together they form one of the biggest barriers to scalable AI.

The equation is simple: AI maturity equals data maturity. And the companies that are pulling ahead today are the ones that invested early in cleaning, organizing and governing their data. By treating data as strategic infrastructure rather than an afterthought, they have unlocked an advantage that competitors will spend years trying to match.

Real efficiency gains are already happening across the industry, not in theory but in measurable, operational terms. One standout example is Smart Persona, Cossette’s AI-driven virtual focus-group platform. Instead of relying on traditional research cycles that can take weeks and require significant human and financial resources, Smart Persona uses generative AI to simulate consumer behaviors, attitudes, and responses.

The results are evident: insights are delivered 65 percent faster and at a fraction of the cost. This speed doesn’t just compress timelines; it allows teams to iterate more often, test more ideas, and respond to market signals in near real time. What used to be a slow, linear process becomes a dynamic, data-driven feedback loop.

Despite the rapid progress, multiple speakers emphasized a reassuring truth: humans will always be in the loop - Nadia Malik, Bombardier. AI is not here to replace people. It is here to elevate them. It is here to support teams, enhance accuracy and free employees from the repetitive work that drains time and energy. When used properly, AI becomes a partner, not a threat.

The organizations moving the fastest are the ones investing in their people. They are training their workforce, not replacing them. They understand that the real power of AI comes from the combination of human judgment and machine intelligence. The future belongs to companies that help their teams work smarter, make better decisions and focus their expertise where it matters most.

Here are five things you can act on immediately.

1. Clean your data
Your first AI win begins with better data hygiene.

2. Start with one problem
Pick the clearest, most measurable pain point and show quick ROI. If you’re unsure where to begin, our AI Diagnostic helps identify high-impact use cases fast.

3. Create a cross-functional AI working group
AI thrives when IT, ops, finance and leadership align early.

4. Define ROI upfront
Know what success looks like before you start.

5. Launch a pilot within 90 days
Speed creates clarity. Clarity drives buy-in. We call it the Vooban method, where we help teams move from idea to pilot quickly using an innovation sprint and a clear blueprint framework that keeps risk low and alignment high.

Impact AI Toronto 2025 made one thing very clear: AI is no longer a technology conversation. It’s a business conversation.

The companies that understand this, and act now, will be the ones setting the pace for the next decade of Canadian innovation.