How AI Is Changing the Business of Canadian Banking

Artificial intelligence is becoming increasingly embedded in Canada’s financial sector, with banks and other financial institutions exploring how the technology can improve efficiency, analyze information and support a growing range of business functions.

The shift is happening alongside a broader modernization of financial services. While Canadian institutions have used artificial intelligence and machine learning for years in areas such as fraud detection and analytics, the emergence of generative AI has expanded the range of tasks that can potentially be assisted or automated.

The Bank of Canada’s 2026 Financial System Survey provides a snapshot of that change. Nearly all respondents reported using AI, although most described their use as limited or moderate. The most common applications were information gathering and analysis and internal operations. Examples included extracting information from financial documents, summarizing research, automating document workflows and supporting internal analytics.

For Canadian banks, the attraction is partly straightforward: AI can help employees complete existing tasks more quickly. The Bank of Canada reported that respondents generally viewed AI as a tool for improving productivity rather than replacing human judgment, particularly when decisions carry significant financial, legal or reputational consequences.

That distinction is important in banking, where automated systems can operate in areas involving customers’ money, personal information and financial decisions.

The next stage of AI adoption is likely to involve moving beyond individual experiments and incorporating the technology into established business processes.

According to the Bank of Canada’s 2026 survey, financial institutions expect to expand AI use over the next two years in areas including operational workflows, back-office activities, financial-crime prevention, customer service, investment research and employee productivity. Banks, broker-dealers and credit unions reported plans to implement AI across a broad range of business functions.

That expansion could change how work is organized inside financial institutions. Tasks involving document processing, information retrieval, research and other repetitive activities may increasingly be assisted by AI, potentially allowing employees to devote more time to work requiring judgment and specialized expertise.

Fergonn Fernandez, a strategic advisor to Canadian banking, financial services and insurance organizations for NewRocket, works with clients on issues including modernization, AI, automation and cloud technologies. His work reflects the broader challenge facing financial institutions, determining how emerging technologies can be incorporated into existing operations while delivering measurable business value.

AI adoption does not happen in isolation. Financial institutions must integrate new technologies with existing systems, data and workflows, some of which have been built over many years.

The Bank of Canada found that 58% of survey respondents cited difficulty integrating AI into existing infrastructure and workflows as a constraint on greater adoption. Talent was another significant challenge, with 56% identifying gaps in AI skills or difficulties hiring and retaining people with specialized expertise.

Data is another consideration. AI systems depend on the quality and availability of the information they use, making data management and governance important components of implementation.

The Office of the Superintendent of Financial Institutions, which supervises federally regulated financial institutions in Canada, has also identified AI as an area presenting both opportunities and risks. OSFI has noted that AI can create efficiencies and support risk assessment, while also introducing governance and complexity challenges.

The potential benefits of AI come with concerns that are particularly significant for financial institutions.

In its 2026 survey, the Bank of Canada identified data quality and bias, cybersecurity and data privacy, and model risk as major concerns among respondents. Model risk can include errors arising from model design or implementation, as well as limited explainability. Institutions also raised concerns about the possibility that AI adoption could move faster than governance and regulation.

Cybersecurity is an especially important issue. AI can be used to improve fraud detection and other defensive capabilities, but regulators and financial institutions are also concerned that the technology could make cyberattacks and financial crime more sophisticated.

OSFI has similarly identified AI-related risks alongside broader technology, cyber, third-party and financial-crime risks facing Canadian financial institutions.

The issue extends beyond individual banks. If multiple institutions rely on similar models, technologies or third-party providers, problems with those systems could potentially affect a wider portion of the financial system.

The Canadian financial sector appears to be entering a phase in which AI becomes less of a standalone experiment and more of an underlying technology within everyday operations.

The Bank of Canada’s survey suggests that institutions expect to increase their use of AI while remaining cautious about allowing it to replace human judgment in critical decisions.

That balance may ultimately determine how quickly the technology transforms banking. The question is no longer simply whether financial institutions can use AI, but where it can deliver meaningful benefits, how those benefits can be measured and what controls are necessary to manage the associated risks.

For Canadian banks, the transition will involve more than adopting new software. It will require changes to technology infrastructure, data practices, employee skills and governance.

AI may not fundamentally change banking overnight. But as the technology becomes incorporated into more processes, from internal operations and financial crime prevention to customer service and analysis, it is likely to become an increasingly ordinary part of how Canadian financial institutions do business.