Canadian wealth management firms are increasingly integrating artificial intelligence (AI) into their operations, a trend underscored by new global research from Montreal-headquartered CGI. However, the study reveals a significant disparity: AI adoption is accelerating at a faster pace than enterprise readiness, a gap that is effectively stalling meaningful technological advancements and impacting the potential for substantial return on investment. This disconnect poses a critical challenge for Canadian advisory firms aiming to harness the full power of AI for growth and client service.
The comprehensive findings, detailed in CGI’s 2026 Voice of Our Clients study released on June 18, 2026, are based on in-depth interviews with over 1,800 business and technology executives worldwide, the majority of whom hold C-level positions. While the research is global in scope, the identified patterns and challenges resonate profoundly with the current landscape Canadian advisory firms are navigating as they grapple with the practical implementation of AI.
Key Findings: The Growing AI Readiness Gap
CGI’s extensive research highlights several critical areas where the enthusiasm for AI adoption is not being matched by the necessary organizational preparedness. Three overarching findings from the study are particularly salient for the financial services sector:
Firstly, a significant portion of organizations are applying AI to their core business processes, indicating a proactive approach to leveraging the technology. However, this adoption is not consistently supported by robust measurement of the outcomes. This disconnect suggests that while firms are experimenting with and implementing AI solutions, they may not have a clear understanding of their actual impact or effectiveness.
Secondly, there is a discernible gap between the application of AI and the existence of a comprehensive enterprise-wide AI strategy. This implies that AI initiatives might be operating in silos or as standalone projects, rather than being integrated into a cohesive, long-term vision for the organization. Without a clear strategic roadmap, the potential for scaled and sustainable AI integration is diminished.
Thirdly, the study points to a pronounced challenge in the IT talent landscape, specifically the difficulty in recruiting essential IT professionals. This shortage has a direct and material impact on the execution of AI programs, creating a bottleneck in implementation and operationalization.
The readiness gap becomes even more stark when examining the quantification of results. Alarmingly, only 51 percent of the organizations surveyed reported that they actively quantify the outcomes of their AI adoption. For financial advisory firms, this statistic is particularly concerning. Implementing AI tools without a systematic approach to measuring their impact makes it exceedingly difficult to justify continued investment, identify areas of true value creation, or optimize future AI strategies. This mirrors previous reports by Wealth Professional, which have indicated that investors may not perceive the benefits of AI adoption if firms fail to demonstrate a clear return on investment (ROI). CGI’s data at the enterprise level substantiates this challenge.
The study visually represents this disparity through comparative metrics:
- AI Application vs. Measurement: Organizations are actively applying AI to core processes, but a smaller percentage are measuring the resulting outcomes.
- AI Activity vs. Strategic Readiness: While AI activities are underway, fewer firms have established a comprehensive enterprise AI strategy.
- IT Talent Shortage vs. Execution Impact: A significant number of firms struggle to recruit IT talent, and these shortages directly impede program execution.
This data, compiled from interviews with over 1,800 business and technology executives globally and published on June 18, 2026, paints a clear picture of an industry eager for AI but not fully equipped to realize its potential.
The Dual Challenge: Legacy Systems and Talent Shortages
CGI’s research zeroes in on two primary operational constraints that are particularly relevant to wealth management firms in Canada: the pervasive issue of legacy systems and the persistent shortage of skilled IT talent.
The first major hurdle identified is outdated infrastructure. A substantial 45 percent of executives surveyed indicated that legacy systems significantly challenge their data and AI strategies. These antiquated technological frameworks often lack the flexibility, scalability, and integration capabilities required to support modern AI applications. They can create data silos, hinder data accessibility, and complicate the deployment of sophisticated AI models, thereby impeding innovation and efficiency.
The second critical constraint is the difficulty in acquiring and retaining IT talent. Nearly 70 percent of executives reported facing challenges in recruiting IT professionals. Furthermore, a significant 52 percent stated that these talent shortages are materially affecting their ability to deliver and execute AI programs. This lack of skilled personnel – from data scientists and AI engineers to cybersecurity experts and IT project managers – creates a critical bottleneck. Canadian firms are already preparing for workplaces where AI agents and human employees collaborate. However, securing the human capital necessary to build, implement, maintain, and govern these advanced systems remains a persistent and formidable barrier.
Tim Hurlebaus, CGI President and CEO, commented on the evolving landscape, stating, "Executives are navigating an environment defined by rising complexity, from regulatory pressures to fragmented systems, while still being expected to deliver measurable outcomes. Our 2026 Voice of Our Clients insights show a clear evolution toward digital engineering and reengineering initiatives." This sentiment underscores the dual pressures of operational complexity and the imperative for tangible results in an increasingly digital world.
Strategic Responses and the Path Forward for Canadian Firms
In response to these challenges, the CGI report identifies three key strategic actions that organizations are pursuing:
- Accelerating Digital Engineering: Firms are prioritizing initiatives that modernize their core systems and processes, often through digital engineering approaches. This involves rebuilding or rearchitecting existing systems to be more agile, data-centric, and ready for advanced technologies like AI.
- Scaling AI Initiatives: The focus is shifting from isolated AI use cases to embedding AI more broadly across the enterprise. This requires a more strategic and integrated approach, moving beyond pilot projects to full-scale implementation that drives tangible business value.
- Prioritizing Data and AI Strategy: Organizations are recognizing the foundational importance of a well-defined data and AI strategy. This involves establishing clear objectives, governance frameworks, and roadmaps for how AI will be leveraged to achieve business goals.
Dave Henderson, Chief Technology Officer for CGI, elaborated on the core opportunity: "The opportunity lies in helping organizations move beyond isolated AI use cases toward embedding AI into complex enterprise environments." This highlights the critical need for a holistic approach to AI integration, rather than viewing it as a collection of discrete technologies.
The "uncomfortable truth" for many firms, as previously highlighted by Wealth Professional regarding AI in Canada’s wealth management industry, is that adoption statistics can often mask underlying readiness issues. CGI’s global data reinforces this finding at a significant scale. While technology and digital acceleration remain the most cited macro trends, identified by 70 percent of executives in the CGI study, only 25 percent of these executives rate their current operating models as highly agile. This stark contrast underscores the disconnect between recognizing the importance of digital transformation and possessing the organizational agility to execute it effectively.
Investing in AI tools without concurrently addressing fundamental issues such as robust data infrastructure, the modernization of legacy systems, and the cultivation of essential talent is unlikely to yield the desired returns. For Canadian wealth and advisory firms, this means a strategic imperative to invest not just in AI technology itself, but in the foundational elements that enable its successful and sustainable deployment. This includes a concerted effort to upgrade technological infrastructure, develop comprehensive talent acquisition and retention strategies, and embed AI within a clear, enterprise-wide strategic vision. The future success of AI adoption in the Canadian wealth management sector will hinge on closing this critical readiness gap.
For further insights into how Canadian wealth management firms are navigating the complexities of AI adoption and integration, readers are encouraged to explore Wealth Professional’s dedicated wealth technology coverage.
