Global trends report shows AI adoption still lags in Canada

A new report, shared at the ALL IN conference in Montréal on Wednesday by data platform company WEKA, reveals key findings on the lagging adoption of artificial intelligence (AI) in Canada. 

“Global AI demand is outpacing access to AI accelerators and GPUs needed to power AI projects.”

The study, conducted by S&P Global Market Intelligence, gathered responses from 1500 AI professionals and decision-makers. The data, which offers an overall look at the current trends shaping AI adoption worldwide, noted an “astonishing rate of change” since the onset of ChatGPT 3 and the first wave of generative AI models reached the market in early 2023. 

“In less than two years, generative AI adoption has eclipsed all other AI applications in the enterprise, defining a new cohort of AI leaders and shaping an emergent market of specialty AI and GPU cloud providers,” John Abbott, principal research analyst at 451 Research, part of S&P Global Market Intelligence, said in a statement. 

Abbott’s research team also reported a direct correlation between the degree of AI maturity within a company and its revenue, operating efficiencies, and time to market for product innovation. 

The proportion of all respondents who said AI is “widely implemented” in their organizations grew from 28 percent in 2023 to 33 percent in 2024. Among those in North America, the rate is even higher with 48 percent saying AI drives critical value in their companies. 

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However, the penetration of these AI tools within Canadian businesses remains low. In Canada, only 35 percent of organizations say AI is “widely implemented, [and is] driving critical value,” according to the report. The average organization in Canada has eight AI or machine learning (ML) projects in the pilot phase and 16 in limited deployment. However, on average, only seven are deployed at scale. 

Although AI is now more widely implemented in global organizations, obstacles remain in deploying AI successfully at scale, the report reveals, with GPU availability among the biggest challenges cited in the report. Thirty percent of organizations surveyed in the report noted GPU access among the top three most serious challenges in moving AI models into production.

“Global AI demand is outpacing access to AI accelerators and GPUs needed to power AI projects,” the report says. 

According to the report, most organizations are also still concerned about the impacts of their AI/ML projects on their carbon footprint. Nearly two-thirds of the organizations globally (59 percent in Canada) say they are concerned about the impact of AI/ML on their energy use, and up to 25 percent of organizations (14 percent in Canada) indicate they are very concerned about AI’s carbon footprint. 

More details about these insights can be found in the full report. 

Feature image courtesy of WEKA.