Just over six months ago, World Trade Centre Toronto launched the AI Business Catalyst to create space for business leaders to work through AI decisions in a practical way.
Since April, 872 participants from 128 companies have come through 18 sessions. The room has included manufacturers and CFOs, HR leaders and founders, executives from financial services, healthcare operators, hospitality managers, retailers and professional services firms. Fifty advisors, mentors and subject matter experts have contributed to those discussions.
The participation numbers tell part of the story. The range of industries in the room tells another.
What has proven most consequential, though, is how those conversations have unfolded. As leaders from different sectors compared notes, challenged assumptions and pressure-tested ideas against their own operating realities, the tone shifted. The sessions became less about what AI could theoretically do and more about how it should be approached inside real organizations.
Those exchanges — across sectors, roles and levels of AI maturity — have shaped what participants describe as the most valuable outcomes of the program.
Structure Reduces Uncertainty
In the early stages of AI exploration, leaders often begin with possibility. What can we test? Where could automation fit? How fast should we move?
Inside these sessions, that line of thinking tends to give way to something more grounded.
Who owns this decision internally? Is the underlying data reliable enough? What are the downstream implications if this scales?
Manny Bonilla, VP Product Strategy at Shoplogix, reflected on his experience in the Manufacturing session this way: “I felt the structure of the program helped by giving some frameworks to make decisions on how I will move forward in driving AI adoption at my company.”
The emphasis on structure appears repeatedly. Not acceleration for its own sake, but sequencing. Not disruption as a slogan, but decision-making discipline.
Across sectors, what reduces friction is not more information. It is clarity around responsibility.
Application Is the Benchmark
Enthusiasm for AI is widespread. The real test is whether something changes the next day.
In a session focused on revenue growth, Amos Adler, CEO of MemoText, described it as a “great day with real valuable lessons I’m already using.” Tariq AlBarwani of Strom Futures noted that he had already implemented an AI-first approach in his marketing execution plan based on the discussion.
For Damaris Puga, Chief Implementation Officer at Trade Cafe, the value lay in clarity. The program helped clarify how to begin using AI tools in her company and offered practical ways to improve sales performance.
The language participants use is consistent. Frameworks. Practical starting points. Usable insights.
Interest alone does not move organizations forward. Confidence about where to begin does.
Context Shapes the Outcome
AI does not present the same questions in every industry.
In manufacturing sessions, leaders frequently press on feasibility and depth. Jeffrey Moss, President of MOSS Led, appreciated the overview but expressed interest in more hands-on implementation support. Andrew Szasz of Protectolite Composits suggested more project-based formats that would allow participants to leave with something closer to a trialed plan.
In hiring and retention discussions, the tone shifts. Integration and internal readiness take precedence. Priya Patel of Alleviate Physiotherapy said the session gave her “lots of ideas to use AI tools in our business,” reflecting a focus on operational application rather than theory.
The most productive discussions are the ones that acknowledge these differences rather than flatten them.
Peer Perspective Changes the Energy
One of the less visible outcomes of the first six months has been the effect of peer exchange.
When leaders hear how others are navigating similar implementation challenges, the conversation becomes more realistic.
In an Executive Roundtable, Carolina Giliberti of Ontario Global 100 described it as “a great opportunity to hear how companies are struggling with the implementation of AI in their businesses.” Mei Burgin of Regenerative Capital said the peer brainstorming left her feeling equipped to take next steps. Nick Bobrow of Unity Brands valued interacting with leaders from different sectors and left with new business connections.
Struggle, in this context, is not a weakness. It is a sign that the conversation has moved beyond surface-level optimism.
What Maturity Looks Like
Taken together, the first six months suggest a shift in posture.
Organizations are no longer asking whether AI matters. They are working through what responsible adoption looks like inside their own operations.
The sessions that resonate most are those that reduce ambiguity, connect directly to how a business runs and allow leaders to pressure-test ideas against real constraints. There is also a clear appetite for deeper implementation support, not just broad overviews.
The AI Business Catalyst has not simplified the complexity of AI adoption. It has created space for businesses to examine it more deliberately and with more candor.
That shift in tone — from urgency to responsibility — may be the most meaningful outcome so far.