As Canadian businesses accelerate AI adoption, the challenge is no longer if but how to scale effectively, responsibly, and productively.
In this exclusive Techcouver interview, Manav Gupta, CTO and VP of IBM Canada, shares key insights from IBM’s latest global CEO and ROI of AI studies—and explains how AI agents, trust-first governance, and strategic upskilling are helping Canadian organizations move from experimentation to enterprise-wide transformation.
With examples ranging from IBM’s own internal adoption to Vancouver International Airport’s AI-powered operations, Gupta outlines what it takes to lead in the next wave of AI innovation.
How are AI agents addressing productivity challenges in Canadian businesses?
MG: AI agents are boosting productivity in Canadian businesses by automating repetitive tasks, optimizing workflows, and delivering actionable insights. The 2025 IBM CEO Study, 72% of Canadian CEOs are actively adopting AI agents, prioritizing productivity gains such as time savings and operational efficiency.
Vancouver International Airport (YVR) is an example of leadership in AI adoption, leveraging it and digital twin technology to drive operational efficiency and situational awareness in real time. By integrating predictive AI capabilities, they are enabling proactive issue resolution and data-driven decision-making. Every employee will be equipped with a trainable AI assistant, an AI Buddy, fostering cross-functional collaboration and creating a connected support ecosystem
As “client zero,” IBM has leveraged its own AI solutions, including tools from its watsonx platform, to streamline workflows, enhance decision-making, and improve operational efficiency. This first-hand experience has provided IBM with critical insights into the challenges of scaling AI, such as data integration and governance, and the solutions needed to overcome them. IBM’s key lesson? AI must be embedded into the core of the business, supported by a strong data foundation, to deliver measurable productivity gains and long-term value.
What skills and training do Canadian businesses need to focus on to successfully adopt and scale AI? Are there specific strategies IBM recommends for upskilling teams?
MG: To adopt and scale AI successfully, Canadian businesses need to invest in technical skills such as data science, machine learning, and AI model development, alongside business-critical skills like data literacy, critical thinking, and change management. Cross-functional collaboration is also essential to bridge the gap between technical and non-technical teams.
Businesses should adopt an AI-first approach to upskilling, combining targeted training programs, certification courses, and hands-on experience with AI tools. Empowering both technical and non-technical teams ensures organizations are equipped to leverage AI effectively and drive transformation.
Trust and ethics are critical for AI adoption. What steps should Canadian organizations take to establish effective AI governance frameworks while maintaining productivity?
MG: Trust is essential for AI adoption, but many organizations still face challenges in building it. To establish effective AI governance while maintaining productivity, organizations should:
- Enhance transparency and compliance: Implement tools and practices that enhance transparency, manage compliance, reduce bias, and provide clear insights into how AI models are trained and operate.
- Prioritize data integration: With 79% of Canadian CEOs emphasizing enterprise-wide data architecture, investing in data quality and governance is critical for scalability and trustworthiness.
- Embed ethical practices: Conduct regular audits, ensure model explainability, and focus on risk-based regulation to foster trust and accountability.
By embedding trust and ethical governance into AI systems, Canadian businesses can scale adoption responsibly while driving productivity.
What are the biggest challenges Canadian businesses face when scaling AI, particularly in terms of costs, energy/resource demands, and complexity? How can they overcome these obstacles?
MG: Scaling AI presents significant challenges, including high costs, integration complexities, and scalability issues. The 2025 IBM ROI of AI Study reports only 14% of AI initiatives in Canada have scaled enterprise-wide, and 43% of Canadian CEOs cite insufficient or poorly integrated data as a significant barrier. Additionally, scalability issues (47%) and integration with existing systems (44%) are common challenges for Canadian organizations.
To address these challenges, businesses should:
- Start small and scale incrementally: Pilot projects can test feasibility before broader implementation.
- Optimize costs and energy use: Lightweight, pre-trained AI models and energy-efficient architectures can reduce resource demands.
- Simplify integration: Hybrid cloud platforms enable scalable AI adoption without disrupting existing infrastructure.
By addressing these challenges with scalable, efficient AI solutions, Canadian businesses can unlock productivity gains and achieve enterprise-wide transformation.
Canada has a reputation for being a leader in AI innovation. What unique opportunities or challenges do you see for Canadian organizations to secure and maintain leadership on the global stage?
MG: Canada’s strong research community, government support, and diverse talent pool have positioned it as a global AI leader. The challenge now lies in scaling innovation—turning research into enterprise-ready solutions that drive productivity.
Opportunities for Canadian organizations include:
- Leveraging open-source ecosystems: With 41% of Canadian businesses planning to leverage open-source AI platforms in 2025, organizations can foster collaboration and innovation while reducing development costs.
- Investing in workforce transformation: As AI adoption accelerates, Canadian organizations can lead by reskilling their workforce and integrating AI assistants to enhance employee productivity.
Looking ahead, how do you see AI evolving in Canada, and what role will IBM play in driving both innovation and productivity across industries?
AI in Canada is rapidly evolving, with businesses increasingly adopting advanced technologies like agentic AI to transform operations and drive productivity. According to a KPMG Canada survey, 27% of organizations have already deployed agentic AI, and 57% plan to adopt or invest in it within the next six months. As adoption grows, Canadian businesses will increasingly leverage AI to address complex challenges, drive operational efficiencies, and deliver personalized customer experiences.
IBM will contribute by driving innovation through AI and hybrid cloud solutions, fostering partnerships with Canadian organizations, and advancing ethical AI practices. By supporting productivity and workforce transformation, IBM will help Canadian businesses lead in an increasingly AI-driven global economy.
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