From efficiency to proficiency: Building a culture of AI literacy

If we can make sure that everybody within businesses, enterprises, governments and citizens alike can access and understand it, the narrative in Canada can shift from what AI will do to you, to what AI will do for you.

Louis Têtu,  Executive Chairman
Coveo 

Technology cycles often begin with strong expectations. We see early prototypes and imagine the transformative possibility, which fuels investment and hype. Eventually, the initial excitement settles into a more practical reality. Business leaders must turn those early experiments into sustainable capabilities.

Louis Têtu, Executive Chairman of Coveo, understands this transition deeply. Speaking at global technology forums like Web Summit Vancouver 2026, he consistently brings the focus back to tangible outcomes. The initial excitement must give way to operational discipline and measurable improvement. "Hype fuels booms," he notes, "but balance sheets decide busts.”  

For Têtu, organizations cannot afford to treat artificial intelligence as an isolated experiment. They must build genuine workforce proficiency. This requires a fundamental shift in how we view digital transformation. We have to move beyond IT running a succession of pilot projects for narrow, isolated use cases. Instead, Têtu's AI imperative is to embed digital literacy across the entire organization – replacing the mode of "waiting until something is ready for us," with a company-wide ability for workers to improve their own productivity.  

The quantum leap in productivity gains – gains in terms of improving what we can do – comes from proficiency not just efficiency. The ability to for people to do more on their own, as opposed simply doing more, faster. 

Moving past “efficiency” 

Many organizations mistakenly view artificial intelligence as primarily a tool for efficiency – “doing more, faster.” This concentrates focus on automating work flows to save bits of time here and there. For Têtu, this approach misses the larger opportunity. 

Têtu sees "proficiency" in terms of employees being able to solve higher-order problems with confidence. It allows professionals to more effectively manage growing business complexity. He emphasizes that technology should elevate human potential.  "Proficiency," says Têtu, "is about giving people the context they need to make the best possible decision in the moment."  

When teams have context-aware tools, they make smarter decisions. A supply chain manager can navigate global disruptions more effectively. A customer service representative can anticipate client needs with much greater accuracy. This creates a bottom-up swell of innovation. Employees who understand the core business find entirely new ways to apply technology. They move from being task executors to strategic thinkers. 

In any organization – any society – there are always people who understand technology more. But AI is a very horizontal technology that arguably transforms every area of business, every citizen, and our lives. And so, to make real gains you need to make sure that everybody in the organization becomes AI literate. 

Democratizing AI literacy: For proficiency, engagement and retention 

To get to proficiency, building company-wide AI literacy is vital. Instead of being a mandate for IT to source and deliver AI solutions, it must be a “horizontal” initiative. Têtu argues that, “getting everyone to participate in the transformation enabled by AI is the best way to lead this process.” And so, every department needs to be empowered to learn, understand and develop these new capabilities.  

AI opportunities must be accessible to the frontline worker and the financial analyst. When technology sits only in a specialized lab, pilot or sandbox, the impact is narrow (or theoretical). When it is ubiquitous across the workforce – because it comes from within that workforce – it becomes a driver of daily value. And that is before we even consider how adoption improves (and fear recedes) when solutions are developed by the people who will use them. 

This broad approach also creates an environment where skilled domestic talent can thrive. Professionals want to work for organizations that empower them. Providing advanced, intuitive platforms is a vital talent retention strategy. It signals that an organization is invested in the future of its workforce and the tools they need to compete on a global stage. 

As much as we are in love with science and research, we need to be in love with the adoption, the industrialization, the commercialization, the monetization of our intellectual property. 

Commercializing Canadian research 

Canada produces world-class science and research. Our academic institutions are globally recognized leaders in technological development. We see this firsthand in how Canadian AI research lays the foundations for tomorrow's breakthroughs. Retaining our top talent requires giving them the best tools to work with. 

Canada faces an innovation paradox. We excel at foundational science but often struggle with broad commercialization. To be “in love” with adoption, industrialization and commercialization, we have to bridge the gap from AI research to adoption. 

This means ensuring our abundance of expertise translates to benefits for our domestic industries. If we can’t make the most of (and capitalize upon) these capabilities within our own borders, we also risk losing our brightest minds to the international organizations who can – effectively exporting our talent and intellectual property to foreign technology giants. Building strong domestic technology ecosystems ensures local expertise directly supports national competitiveness. When Canadian businesses adopt Canadian innovations, the entire economy benefits. 

Infrastructure only changes the economy when every business can plug into it easily. How can you quickly get AI into 100,000 businesses in two to three years? Create infrastructure that is highly industrialized, that is available easily to all Canadians and all Canadian businesses. 

Building an ecosystem of AI on tap 

For Têtu, the third and final piece needed to lead in AI is accessibility. If we are to educate our workforces (and indeed our entire population) at the same time that we bridge the gap between research and industrialization, then AI must be safe, trustworthy, and readily accessible. He sees a vital need for standardized, accessible AI capabilities, where the tools are as easy to access as electricity or water. He calls it “delivering AI on tap."  

When organizations can easily “plug in” to a secure AI capabilities, adoption rapidly accelerates. This ecosystem enables both mid-market and enterprise organizations to integrate insights seamlessly, a key driver for economic impact in Canada. 

Make it easy to adopt. Make people literate about the technology, but make the infrastructure readily available for businesses, for institutions, for governments to tap into. It’s what I refer to as “AI on tap.”