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Montreal is now recognized as one of the world’s leading hubs for artificial intelligence. In just a few years, the city—and, more broadly, Quebec—has built a robust ecosystem, with more than 1,500 researchers; Mila (the Quebec Institute for Artificial Intelligence) represents the world’s largest concentration of academic researchers in deep learning. Revolving around this core is a rare concentration of talent, substantial government support, and a growing network of innovative companies.
But beyond the rankings and reputation, one question is of greater interest to local leaders: what does this leadership actually mean for their organizations? Because Quebec’s true strength in artificial intelligence lies not only in the excellence of its research. It lies in the synergy between this cutting-edge ecosystem and companies—often SMEs—that are agile enough to adopt AI gradually and in a way that aligns with their business needs.
It is this combination that puts Quebec companies in an enviable position: they have access, right on their doorstep, to the expertise, talent, and funding needed to realize AI’s full potential. This article provides an overview of this ecosystem, sector by sector, and shows how a local organization can find its place within it.
Québec’s status in artificial intelligence is neither a matter of chance nor a recent trend. It is based on four strengths that have come together over more than three decades: a critical mass of researchers, groundbreaking scientific breakthroughs, a flagship institution, and consistent public support.
Quebec’s first strength is its concentration of intellectual talent. Greater Montreal is now home to 27,000 workers with AI skills—a pool that has grown by 15% over the past twelve months. This workforce is supported by an exceptional academic foundation: the Université de Montréal, McGill, Polytechnique, HEC Montréal, and Université Laval produce a new generation of highly qualified professionals every year. This concentration attracts the research labs of global digital giants and fuels an ecosystem where talent attracts talent.
At the heart of this story is Yoshua Bengio. A pioneer in deep learning (the branch of AI that has made recent advances in computer vision, natural language processing, and generative AI possible), he founded Mila in 1993 at the University of Montreal. His work, among the most cited in the world, has made Quebec one of the scientific cradles of modern AI, long before the technology became a topic of conversation among the general public.
This legacy is embodied today in Mila, the Quebec Institute for Artificial Intelligence. Born out of a collaboration between the University of Montreal and McGill University, the institute brings together more than 1,300 researchers and represents the world’s largest concentration of academic researchers in deep learning. Beyond basic research, Mila serves as a hub: it supports Quebec companies in the development and adoption of AI technologies and cements Montreal’s position as one of the world’s leading centers in the field.
This scientific excellence has been supported by consistent public commitment. The Quebec Strategy for Research and Investment in Innovation 2022–2027 allocates $125 million for AI-related initiatives, and the government has renewed its support for Mila through 2026. At the Canadian level, the Scale AI supercluster, based in Montreal and dedicated to applying AI to supply chains, brings together dozens of companies of all sizes and funds concrete industry-led projects.
But this global reputation means nothing to a local organization unless it translates into tangible access. Yet this is precisely what sets Quebec apart: locally trained talent, specialized partners nearby, and structured funding programs. The ecosystem is not just a source of collective pride—it is an asset that Quebec companies, regardless of their size, can directly leverage.
Understanding the ecosystem is good; knowing who to turn to is better. For an organization looking to take action, Quebec’s AI players can be grouped into three categories, depending on the need: exploring a research question, having a solution developed, or funding the initiative.
When a project runs into a scientific problem—such as an algorithmic challenge or a complex data issue—Quebec offers rare access to world-class research.
This is where most projects really come to life. Because there’s a gap between a scientific breakthrough and a tool that’s up and running in a company: the challenge of integrating it with existing systems, data, and business rules.
Several types of players operate in this space.
It is precisely at this stage that the true value of AI is realized: in its integration with a company’s systems, data, and processes.
Cost is often a barrier for organizations even before they get started, and this is precisely where Quebec’s ecosystem makes a difference.
For an SME, this safety net makes all the difference: it makes a type of project accessible that was once reserved for large organizations.
The adoption of AI varies from sector to sector. According to the Quebec Institute of Statistics, the industries that use it the most are finance and insurance, the information and culture sector, and professional and scientific services, with adoption rates ranging from 37% to 55% in the second quarter of 2025. Here’s an overview of the areas where the transformation is most visible.
This is the most advanced sector in Quebec in terms of AI. Financial institutions and insurers rely on machine learning to detect fraud in real time, assess risk, automate claims processing, and personalize their offerings. The wealth of their data and the repetitive nature of many processes make this a particularly fertile ground, where productivity gains can be measured quickly.
A historic pillar of Quebec’s economy, the manufacturing sector perhaps best illustrates the concrete changes AI is bringing to local businesses. Predictive maintenance, production optimization, automated quality control—the applications are numerous. But AI also plays a more strategic role in this sector.
Take the case of a custom equipment manufacturer in Plessisville, in the Centre-du-Québec region. Its estimating process, which required dozens of hours of expert work per quote, was holding back its growth and relied on the informal know-how of a few senior estimators. By centralizing these business rules in a secure AI agent, the company reduced the estimation time from six hours to thirty minutes for its most complex equipment, increased its capacity by 50%, and, most importantly, secured key expertise before its experts left the company.
The aerospace and transportation sectors, which have a strong presence in the Montreal region, are leveraging AI for simulation, design, and logistics optimization.
This is Scale AI’s area of expertise, as its mission focuses specifically on applying AI to supply chains. Demand forecasting, inventory optimization, route planning, and end-to-end traceability: Quebec companies such as OPTEL, in the Quebec City region, have been developing smart solutions for years that make supply chains more efficient and predictable.
Healthcare offers strong potential, driven by Quebec’s expertise in the life sciences and by Mila’s research in this field. Diagnostic assistance, medical imaging, screening, and personalized medicine: applications are multiplying. However, the sector is advancing more cautiously than others, as the requirements for clinical validation, data protection, and ethical oversight are—rightly so—particularly high.
For a company, the breadth of training options is no small matter: it ensures not only the ability to recruit talent but also to develop the skills of its own teams.
Quebec universities offer specialized programs in AI, data science, and machine learning, ranging from bachelor’s degrees to doctorates. This depth of academic expertise, supported by research institutions such as Mila and IVADO, produces a pool of highly qualified graduates every year. At the college level, technical programs and certificates of studies train an operational workforce better suited to the practical needs of SMEs. For an organization, this means one simple thing: talent is right nearby, and it’s constantly being replenished.
Beyond formal academic programs, continuing education opportunities allow companies to develop their existing teams without relying solely on recruitment. Specialized certifications, short courses, and professional development programs offered by universities, industry organizations, or ecosystem stakeholders: these pathways help professionals already in the workforce acquire skills in applied AI. This is often the fastest way for an organization to develop a data-driven culture and prepare its managers to lead AI projects.
In practical terms, AI has an impact in several key areas:
Successful organizations generally follow the same approach: taking small steps, but in the right direction. Here’s how to do it.
It all starts with a real business problem, not the technology. The first question isn’t “How can we use AI?” but “Where is my real bottleneck?” A time-consuming process, critical expertise concentrated in a few people, or a repetitive task that ties up skilled employees—these are the best candidates. The right use case is one where the benefit is concrete, measurable, and significant for the company. It’s better to aim for a specific, high-impact target than to spread AI efforts too thinly.
Once the target has been chosen, it would be a mistake to try to solve everything at once. The safest approach is to tackle a small initial scope—often the most complex or representative case—to quickly demonstrate value. This approach has proven effective: by delivering a first functional solution in a matter of weeks rather than several months, you validate business rules, reassure teams by quickly putting a tool in their hands, and lay the technical groundwork for the rest of the deployment. The pilot serves as proof of the project’s value and as a springboard: if it works for the most challenging case, it will work for the others.
Technology is only part of the equation. A good integration partner starts with the business problem before discussing tools, understands the realities of local businesses, and knows how to align a solution with existing systems, data, and processes. This is precisely where the true value of AI lies: not in a model’s performance, but in its careful integration into an organization’s context. In this regard, the proximity of an ecosystem rich in expertise—including locally trained talent, specialized firms, and support programs—gives Quebec businesses a tangible advantage: they don’t have to look far to find the right partners.
Ready to take action?
The process always starts with a simple conversation: what use case would make the biggest difference in your organization? That’s exactly the starting point we explore with local companies. Let’s talk about your first use case and see together how to turn your opportunities into concrete results.
Quebec’s story in artificial intelligence is far from over, and the coming years could be the ones where the advantage shifts fully to businesses.
The first trend is widespread adoption. Until now, AI has primarily benefited large organizations and sectors that are already digitized. But the democratization of these tools, combined with a supportive ecosystem, is now making these technologies accessible to small and medium-sized businesses. The gap between large and small organizations—which still exists today—is set to narrow.
The second trend is responsible AI and data sovereignty. In a context where the protection of personal information is becoming a major business issue, the ability to deploy solutions that keep data private will become a key differentiator. Companies that adopt AI without sacrificing trust—both from their customers and their employees—will gain a competitive edge.
Finally, Quebec’s historic strength lies in its collaboration between research, industry, and government. It is this synergy—between world-class researchers, companies willing to experiment, and public programs that mitigate risk—that has made Quebec a recognized hub. And it is this synergy that will continue to transform scientific leadership into tangible economic advantages, provided that companies seize this opportunity.
To learn more, explore our articles on artificial intelligence and discover how local companies are transforming the way they do business.
