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AI isn’t delivering for Canadian banks. Except where it is
What’s working in AI, cloud, and banking modernization
Canadian banks are respected worldwide for their resilience and are expected to weather new headwinds well. But to continue thriving, they must accelerate their modernization and adoption of new technologies—and they know it. According to our latest Global CEO Survey, 42% of Canadian financial services leaders say their top concern is whether their organization is transforming fast enough for AI.
Yet despite focused effort and technology spending, most banks aren’t seeing results. Our CEO Survey found that fewer than one in ten Canadian financial services respondents say their organization has deployed AI at scale in any business function, trailing their global peers by double digits in areas such as back-office support and customer-facing products. 73% of Canadian financial services CEOs report little to no revenue impact from AI in the past year, and 60% say the same for costs.
But some banks are proving that AI can deliver returns in weeks, not years. They’re not just adopting AI—they’re unleashing it on challenges that have traditionally held them back. And the breakthroughs are real.
Canadian banking in 2026: Sound fundamentals, growing pressures
Canadian banks are on solid ground. Their diversified earnings models are proven, credit is normalizing, and capital efficiency continues to improve. But resilience isn’t the challenge. Relevance is.
Younger customers want digital-first, automated experiences. Fintech startups are delivering them with cloud-native architectures and AI capabilities that legacy systems can’t match. And as Canada moves toward open banking, the competitive pressure will only intensify.
Technology has become the primary lever for banks to respond—underpinning strategy, differentiating performance, and determining which institutions convert ambition into scalable growth. Banks are signalling return-on-equity and margin uplift through 2029. But getting there will require a fundamentally different approach to technology implementation.
Legacy systems, data silos, and the modernization gap
When the internet reshaped banking, financial institutions had years to adapt. With AI, they won’t.
The barriers to moving faster are structural. Legacy systems, some decades old, still underpin core operations. The data these systems hold is siloed, analog, or stored in outdated formats. The result: more than half (53%) of Canadian financial services CEOs say even their organization’s most-used AI tool can’t access all their documents and data. Even where banks have moved to cloud, many have layered manual processes and approval layers on top, negating the speed and scalability cloud should deliver.
Barriers also stem from the decision-making patterns banks have built over time. The same discipline that makes Canadian banks resilient—rigorous governance, conservative risk management, and cautious capital allocation—can slow their ability to move. And a track record of stable returns can make it harder to justify the heavy upfront spending that modernization demands. Perhaps unsurprisingly, 42% of Canadian financial services CEOs say their organization has limited access to capital to fund new initiatives.
Inside the banks, competing priorities compound the problem. Lines of business often fund technology projects that benefit the entire organization, creating hesitation and inefficiency. Leaders cycle through roles, and when new leadership arrives, projects may be reassessed or restarted, costing months of momentum.
Where AI in banking is breaking through
So what’s different about the banks that are achieving results?
They’re not starting with technology. They're starting with a business problem—a regulatory deadline, a manual process that can’t scale, a risk framework that isn't keeping pace. Then they’re applying AI to solve it. The result isn’t just a successful technology project. It’s a measurable business outcome.
Through our work with Canadian banks, we’ve seen this pattern firsthand. Three examples illustrate what it looks like in practice.
At one major Canadian bank, maintaining operational procedures was an enormous lift. Every product update or process tweak required rewriting, and employees were spending hours drafting documentation manually.
The bank applied generative AI to draft and update procedures, reducing manual writing time by more than 85%. Documentation was produced with high accuracy, at a fraction of the time and cost. Instead of drafting, teams shifted to validating and improving procedures. What started as a documentation challenge drove broader business process improvements.
At another Canadian bank, the finance department was facing mounting pressure. Regulatory expectations were evolving, transaction volumes were increasing, and demand for faster, deeper financial insights was growing. But critical processes were resource-intensive and time-consuming, documentation preparation was inconsistent in style and approach, and data extraction for reporting was complex and highly manual.
The bank started with three targeted generative AI use cases: automating the creation of analyst reports and earnings transcript summaries, streamlining the development of management discussion and analysis commentaries, and extracting and processing data from financial documents for peer analytics. Each delivered measurable results—faster turnaround, improved accuracy, and teams freed to focus on higher-value work.
Since implementing these initial use cases, the bank has expanded its use of AI across its finance operations. It’s now developing an agentic AI roadmap to help it move from solving individual problems to building a platform for ongoing reinvention.
Elsewhere, AI isn’t just solving operational problems. It’s making the case for further AI adoption.
Canadian banks are required to maintain detailed process maps for risk management and regulatory compliance. In practice, this work is so labour-intensive that it can be difficult to complete thoroughly or on time. One bank applied AI to accelerate the mapping process, and the results went further than expected. The solution benchmarked existing processes against industry standards, identified high-value opportunities for automation and agentic AI, and projected the associated time and cost savings. In effect, it built the business case for its own expansion.
For banks that have struggled to evaluate and prioritize technology investments, this changes the equation. AI is no longer just a tool to deploy. It’s a tool that helps banks figure out where to deploy it next.
AI is already delivering for Canadian banks
We can show you where it could deliver for yours
Making AI work in Canadian banking
These aren’t isolated wins. They reflect a pattern emerging across Canadian financial services: when banks start with a business problem, build trust into the solution, and execute with discipline, technology delivers.
Trust, in particular, is a common thread. On the operational side, that means aligning systems, people, and processes so performance becomes consistent and decisions easier to act on. On the digital side, it means building integrity into AI and data with guardrails that make it safer to innovate and scale.
The lessons from these successes are clear:
Building for what comes next
The banks seeing results today are solving immediate problems. But the capabilities they’re building in the process—trust, discipline, and speed—will matter far beyond any single initiative. AI and other powerful forces are putting enormous value in motion across the global economy. The organizations best positioned to capture it are those building these foundational capabilities now.
How PwC Canada can help
Capturing the value of AI and cloud demands new ways of working. We’ve seen it work firsthand, building solutions alongside organizations through innovation labs, centres of excellence, and co-creation models.
That’s how we work with Canadian banks. We also treat ourselves as “client zero,” adopting AI and automation tools internally before bringing them to market. It keeps us close to the challenges you face and builds trust in the solutions we offer.
Ready to move faster?
Let’s build what’s next—together
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Partner, Cloud Data & AI / Data & AI Leader for Banking, PwC Canada
Tel: +1-514 553-6551
Partner, Financial Services Technology and Transformation, PwC Canada
Tel: +1 647 500 7033
