CEO Global Network Podcast
🎙 Hosted by John Wilson, founder of CEO Global Network and author of GREAT CEOs and How They Are Made, this podcast delivers powerful insights for CEOs and executives looking to grow as leaders and drive lasting success.
Each episode features candid conversations with high-performing business leaders, expert speakers, and industry trailblazers—all focused on sharpening your leadership edge, building resilient companies, and improving your life, your team, and your impact.
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CEO Global Network Podcast
Daniel Wigdor, CEO of AXL - Unlocking Human Potential with AI
In this episode of the CEO Global Network Podcast, host John Wilson sits down with Daniel Wigdor - Professor, inventor, tech entrepreneur, and CEO of AXL: Human Potential, AI Super Powered.
Daniel shares insights on why Canada leads in AI research but struggles to commercialize it, the missing “middle layer” of applied research, and how AXL is bridging that gap. He discusses misconceptions about AI, what it truly means to unlock human potential, and how AI can empower - not replace - people.
They also dive into Daniel’s journey as a professor, researcher at Meta, and entrepreneur, as well as his views on policy changes that could accelerate Canadian AI innovation. Finally, Daniel offers a fascinating glimpse into how human-computer interaction will evolve over the next decade.
This is a must-listen for leaders navigating the intersection of innovation, AI, and business transformation.
00:00 – 00:13
John Wilson welcomes Daniel Wigdor to the CEO Global Network Podcast.
00:13 – 02:14
What’s the missing link in Canada’s ability to commercialize AI research, and how is AXL closing that gap?
Daniel Wigdor explains that while Canada produces world-class research (thanks in part to figures like Geoffrey Hinton), the country lacks the “applied research” layer that bridges academia and industry. He shares a formative moment from his PhD at U of T, when Apple presented multi-touch as an innovation without recognizing its Canadian origins. Unlike the U.S., which has DARPA and other applied research organizations, Canada’s missing “middle layer” often results in Canadian talent and ideas being pulled south. AXL is working to fill that gap.
02:24 – 03:27
What misconception holds back mid-sized businesses from adopting AI?
Daniel notes that many businesses equate AI with chatbots like ChatGPT or Claude. When these tools give wrong answers, companies dismiss AI altogether. In reality, chatbots are just thin demos. Real value comes when businesses bring AI in-house, integrate their own data, and eventually rethink their business models around it.
03:27 – 06:18
What does “unlocking human potential with AI” actually look like in practice?
Daniel stresses that AI shouldn’t replace people, but empower them. Drawing from Marshall McLuhan’s theory, he highlights how new media often imitates old ones before truly innovating. At AXL, they study industries deeply to create tools that enable people to do things they couldn’t before.
– Example: In education, instead of replacing teachers with AI tutors, they’ve designed systems where students teach AI “novices.” This approach leverages proven pedagogy—that teaching others is the best way to learn—while empowering both teachers and students.
06:18 – 08:26
How do academia, research at Meta, and entrepreneurship complement—or clash—when tackling big tech problems?
Daniel says the common thread across science, startups, and big tech is the lean methodology: experiment, measure, iterate. But academia, especially in Canada, often resists commercialization due to fears that money will corrupt research. While valid, this tension means global giants (Google, Meta) often capture the value from Canadian taxpayer-funded innovation. Daniel argues Canada needs to better support local commercialization opportunities.
08:26 – 10:17
If you had the ear of policymakers, what’s the one change that could accelerate Canadian AI innovation?
Daniel offers two:
- Reform the SR&ED tax credit program. Right now, startups get addicted to government funding and avoid raising capital, capping growth. Instead, Canada should subsidize big companies to adopt products from startups—letting the market pick winners.
- Stop funding data centers with taxpayer money. Instead, invest in AI applications and ventures that directly benefit Canadians.
10:17 – 12:30
Looking 10 years ahead, what human-computer interaction will feel as natural as touch screens do today?
Daniel explains that touchscreens only felt “natural” because Apple paired them with simplified mobile apps and pre-released tutorials disguised as commercials. In the future, we’ll be surrounded by sensors, and computers will use context (what you’re doing, where you are, what your team is working on) to tailor interactions seamlessly.
– Example: in a car, only voice interfaces make sense; on a plane, voice is disruptive. The future lies in context-aware systems that switch modes fluidly.
12:30 – 13:02
Closing thanks. John Wilson thanks Daniel for the discussion; Daniel expresses gratitude to John and the listeners.
