What Makes Some Regions Better at AI?

Throughout history, some regions have excelled at innovation — like Renaissance Italy (14th–17th centuries) with art and engineering, Britain’s Industrial Revolution (1760–1840) with steam engines and railways, and Silicon Valley (1970s–present) with the digital and AI revolutions.

But here’s the thing: it’s not about geography or policy alone. Sure, those factors play a role, but what really sets regions apart is the community of innovators and the narrative they create around opportunity. As Acemoglu and Johnson explain in Power and Progress, “useful knowledge expanded dramatically during the nineteenth century,” driving transformative progress in everything from transportation to communication. When the right people believe they’re on the edge of something great, that’s where the magic happens.

Being In An Innovation Hub

Living and working in Toronto, you can feel it — there’s an energy around AI that’s hard to ignore. Walk through the city, and you’ll find students fresh out of the University of Toronto diving headfirst into AI projects. Then there are startups like Cohere, taking the world by storm with cutting-edge models, proving you don’t need to be in Silicon Valley to be at the forefront of tech.

I grew up in a smaller town where software development was hardly ever spoken of, let alone practiced. But when I came to Toronto, everything changed. Walking through libraries and coffee shops, I’d see colorful code whizzing by on people’s laptops and monitors. It was everywhere — AI models, software, algorithms in progress. You could tell instantly: this is an AI and software hub. And honestly, it’s inspiring.

In fact, Toronto has become Canada’s AI capital, with more than 11,700 AI specialists working across industries (Toronto Global). Over the past five years, the city’s AI ecosystem has grown by 44%, adding almost 96,000 jobs. It’s proof that when talent, ambition, and resources align, innovation follows.

The Evolving of Traditional Jobs

AI is shaking things up. 40% of jobs worldwide will be impacted — some roles will change, others will disappear, and new ones will emerge (IMF). From finance and healthcare to logistics and retail, no industry will be untouched. The smart move? Get ahead of the curve. AI isn’t a passing trend — it’s the future, and those who start today will shape it.

Many companies are adapting by building innovation teams — groups of strategists, coders, and problem-solvers focused on turning ideas into solutions. That’s where innovation consultants like me fit in.

I didn’t always know this was the path I’d take. I joined the Digital Management program at Ivey Business School because I wanted to get into Ivey, and the program seemed to suit me. Launched in 2021, it’s all about designing and integrating new tech solutions — skills I never knew existed but now find incredibly valuable.

Today, as part of an enterprise innovation team, I work with developers, strategists, financiers, and researchers to generate ideas that drive real value. The job evolves every month — one day it’s AI use cases, the next it’s building digital tools. It’s fast-paced, fulfilling, and proof that traditional jobs are evolving — and so must we.

Money Moves

In AI, resources are everything, and OpenAI’s latest funding round proves it. With billions flowing in, these investments will push the boundaries of what AI can achieve (Stanford AI Index Report).

In 2023, investment in generative AI surged to $25.2 billion, showing that we’re just getting started. But here’s the thing: if you want to spot the next big innovations, follow the money. Funding shows where breakthroughs are likely to happen, and keeping an eye on these trends helps innovators align with the future.

The areas attracting capital — like generative AI — aren’t just hype; they’re shaping tomorrow’s economy. For entrepreneurs, tracking where the money moves means knowing where to focus next.

Building an AI Ecosystem: It Takes a City

Creating an AI ecosystem — or any complex system — can’t be done in isolation. It takes more than just money, policies, or a handful of innovators. It takes a whole city. Geoffrey West, in his book Scale, explains that some cities — like San Francisco — rise and fall from the technology spotlight, but the ones that have thrived before tend to do it again (West, Scale). It’s not some magic ingredient in the water. Instead, there’s a complex mix of factors — resources, collaboration, and culture — that come together to ignite megabooms of innovation.

Toronto’s success is proof of this. When you give people tools, opportunities, and a community, they thrive. And in today’s AI landscape, the playing field is more level than ever. With 65% of foundation models now open-source (Stanford AI Index Report), you don’t need millions of dollars or a PhD to make an impact — you just need drive and the right environment.

Innovators build the foundation of great ecosystems, but they can’t do it alone. They need a network that encourages experimentation, risk-taking, and continuous learning. When these elements align, cities become hubs of innovation — and capital follows closely behind.

The Future Is Yours — Get in Early

Here’s the bottom line: AI is for anyone willing to dive in and learn. Whether you’re a student, a startup founder, or just someone curious about where the future is headed, the opportunity is now. The tools are accessible, the community is growing, and the boundaries are still being defined. The future of AI is open, and it’s waiting for people like you to shape it.

So, how have I been learning? Well, it starts with books — yes, the age-old idea that knowledge is power. But it’s true. Reading up on concepts and breakthroughs lays a solid foundation. There’s no shortcut around it — books are still one of the most effective ways to understand complex ideas.

Next, taking courses has been game-changing for me, even though it’s hard to stick with them sometimes. Let’s be real — at some point, you just have to sit down and power through, even if it feels uncomfortable. A great place to start is Andrew Ng’s AI and Machine Learning courses on Coursera (Andrew Ng on Coursera). His courses are clear, structured, and incredibly valuable.

Finally, just start building. It might seem intimidating, but trust me — ask ChatGPT to build you a web application, and you’ll be amazed by how good it can be. Start with small projects, experiment, and see where it takes you. AI is about hands-on learning, and the sooner you start, the faster you’ll grow.

Good luck, and don’t hesitate to reach out if you want to chat about AI or need advice. Follow me on LinkedIn: linkedin.com/in/bertomill.