Generative AI adoption in Canadian financial services

Over 90% of Canadian financial services leaders now view generative AI as critical to competitive advantage, with 86% investing despite ongoing economic uncertainty. The urgency is clear: organizations recognize that GenAI is no longer optional, but a non-negotiable lever for increased efficiency and productivity. Several factors are converging to accelerate adoption:

• Technology maturity: Generative AI models have advanced rapidly, enabling more reliable, scalable, and secure applications.
• Competitive pressure: Early adopters are already realizing productivity gains, prompting others to follow suit or risk falling behind.
• Efficiency and productivity: Automation of routine tasks, improved data analysis, and enhanced decision-making are delivering measurable value.
• Customer expectations: Clients increasingly demand seamless, personalized, and digital-first experiences – GenAI is central to meeting these needs.

Canadian banks and insurers are moving beyond experimentation, investing in generative AI to drive real business value across core functions. In Canada’s competitive financial landscape, GenAI is transforming how organizations analyze markets, personalize services, engage customers, manage risk, and streamline operations. Here are some GenAI use cases for financial services:

The Canadian financial services sector is well positioned to lead in generative AI adoption, thanks to its access to rich, increasingly structured datasets and a growing culture of innovation. This combination offers a significant advantage, but also raises the bar for data quality, integration, and governance. For banks and insurers alike, success with GenAI depends on having clean, accessible data and the ability to connect AI with other emerging technologies.

Customer readiness is another defining factor. Canadian consumers have shown strong willingness to adopt digital and mobile financial services, creating a receptive environment for GenAI‑enabled offerings. As a result, financial institutions are investing not only in technology, but also in change management and customer education to drive adoption.

While these strengths are shared across the sector, there are notable differences in approach. Respondents to the survey indicated that insurance organizations are leading in advanced GenAI adoption, with 30% reporting full integration across core operations and workflows. Banks, meanwhile, are mostly in partial adoption, focusing on productivity and sales, and expect a faster return on investment.

Ultimately, what sets Canadian financial services organizations apart is not just their data or regulatory expertise, but their willingness to adapt and innovate at scale. Leaders in this sector recognize that GenAI strategies must be tailored to each organization’s maturity, risk appetite, and the evolving expectations of Canadian customers.

Generative AI is unlocking new sources of value across Canada’s financial services sector. For banks and insurers, the most immediate benefit is efficiency: 37% of banks and 28% of insurers report that GenAI is driving measurable productivity gains, allowing teams to automate routine tasks and focus on higher-value work. In insurance, faster data analysis is particularly impactful, streamlining underwriting and accelerating claims processing – critical for improving customer experience and operational agility.

Beyond efficiency, GenAI is fueling innovation and deeper personalization. Both sectors are using AI to develop new products and deliver tailored customer experiences, helping to build loyalty in a competitive market. Insurers are also leveraging GenAI to transform their workforce, upskilling employees and redeploying talent into AI-enabled roles, which supports long-term adaptability.

Looking ahead, Canadian financial institutions recognize that scaling GenAI requires more than technology. A strong culture of experimentation, embraced by 91% of leaders, is seen as essential for unlocking GenAI’s full potential. Leadership clarity refers to the confidence and understanding among senior executives about the value GenAI will deliver and the roadmap to achieve that value. According to the survey data, 89% of organizations report having this clarity, with insurance leaders showing even greater confidence at 96%. However, moving from pilot projects to enterprise-wide adoption remains a challenge. Success will depend on robust data foundations, integrated platforms, and a commitment to continuous innovation.

Despite the promise of generative AI, Canadian financial institutions face significant hurdles on the path to scaled adoption. Data quality remains a foundational challenge – 30% of banks and insurers cite it as a major barrier, underscoring that even the most advanced AI is only as good as the data it learns from. Without clean, integrated data, GenAI initiatives risk stalling or delivering inconsistent results.

Privacy and cybersecurity concerns are top of mind. With 95% of leaders worried about potential breaches and misuse of sensitive information, and 60% of whom have already experienced a cyber incident, the demand for stronger governance is growing. Yet few organizations have mature frameworks in place, leaving many to navigate evolving risks without clear policies or guardrails. Adding to these challenges, many financial institutions face self‑created hurdles: intricate AI operating models, layered governance processes, and unclear ownership across business and technology teams. These internal challenges can slow decision‑making, dilute accountability, and impede scaling.

Regulation is widely viewed as an enabler rather than a constraint. Ninety-six percent of respondents support clear, enforceable rules and regulatory sandboxes to foster safe innovation. At the same time, talent and change management are persistent constraints. While half of firms are redeploying staff into AI-enabled roles, reskilling and employee buy-in remain critical gaps. At the same time, organizations must navigate critical build‑versus‑buy‑versus‑borrow decisions across a rapidly expanding vendor landscape. Building AI literacy and a culture of adaptability will be essential as financial institutions move from pilots to enterprise‑wide GenAI deployment.

Canadian banks and insurers are scaling generative AI with a disciplined, strategic approach. Nearly half are investing in both talent acquisition (47%) and advanced technology platforms (44%), recognizing that success depends on the right mix of skills and tools. IT modernization leads the agenda, with 60% of organizations upgrading core systems to embed GenAI into daily operations. Generative AI investments in sales and accounting are also rising as firms seek to drive value across the business.

When it comes to measuring success, most Canadian financial institutions expect to see returns on their GenAI investments within one to three years. Rather than focusing on immediate revenue, leaders are tracking productivity gains and adoption rates as key indicators of progress.

However, measuring ROI remains a critical challenge. Many organizations are improving productivity but can lack clear frameworks to translate those gains into growth. To realize full value, firms need holistic ROI models that combine hard financial metrics, such as cost savings, revenue growth, and operational efficiency, with strategic indicators like improved decision-making, employee experience, customer loyalty, and sustained adoption. Establishing KPIs at the outset, supported by strong governance and accountability, is essential for turning AI ambition into measurable results.

Policy and regulation are viewed as critical enablers of GenAI at scale. There is strong support for harmonized rules, tax credits, and regulatory sandboxes, with 96% of organizations advocating for clear frameworks to accelerate responsible and effective adoption.