More than eight in 10 Canadian companies are making progress in executing last year’s AI strategies, according to an IBM Canada survey.

The survey questioned 2,400 IT decision makers (ITDMs) and conducted by Morning Consult and developed in collaboration with Lopez Research. The study revealed that 83% of Canadian ITDM respondents report making progress in executing their 2024 artificial intelligence strategy, with 42% already seeing positive ROI from AI investments.

The data also reveals that Canadian businesses are using a combination of buying or leasing AI tools from vendors (65%), using an open-source ecosystem (57%) versus in-house development (42%).

More than half (56%) of Canadian respondents indicate they will hike their AI investments in 2025, while planning to leverage open-source ecosystems (41%), hire specialized talent (41%), evaluate models (43%) and use cloud managed services (49%) to optimize AI implementation.

“This is a crucial year to pivot on AI adoption in Canadian organizations and our success hinges on strategic investments across models, platforms and supporting our people,” says Deb Pimentel, president of IBM Canada and general manager of IBM Technology Canada. “This study underscores the importance of open-source platforms, high-quality data and a well-defined AI strategy to enhance productivity.”

According to the survey, ROI is not necessarily the primary driver of AI investments at Canadian companies and the lack of short-term ROI is not discouraging them: 39% of Canada respondents reported that AI investment was equally innovation-driven and ROI-driven, with only 7% reporting their strategy was exclusively ROI-driven.

Also, 25% of Canadian respondents identified “more rapid innovation” as the most important metric, followed by “productivity time savings” (21%) and “faster software development” (21%). Monetary savings (16%) and short time to trouble shoot issues (17%) are considered less important ROI measurements.

When implementing AI, the biggest challenges faced by Canadian organizations are tech integration (27%), lack of AI expertise (27%) and lack of AI governance (25%).