BMO Introduces Agentic AI Case Preparation for Credit Card Support – Unite.AI

BMO announced on November 6, 2026, the introduction of AI Agent Assist for employees handling credit card transaction requests from Canadian customers at its Virtual Connect contact center, with the goal of reducing resolution times by 20-30% for eligible requests and automatically processing approximately 40% of eligible credit refund requests.

Virtual Connect receives more than 500,000 such calls each year, and each one currently takes an average of 12-14 minutes to resolve. Against that baseline, implementation focuses on prep work within employee-assisted calls. The assistant is designed for internal use and provides relevant transaction information and guidance directly to team members so they can spend less time navigating systems.

Both goals are limited to eligible interactions and represent targets rather than results reported by contact centers. For qualifying requests, BMO says customers could receive their credit as soon as the same day, making faster refund processing a conditional outcome for the customer rather than a universal refund commitment.

How AI Agent Assist supports employees

AI Agent Assist combines AI-enabled transaction matching, policy retrieval, and case preparation for employee review. BMO intends for the consolidated workflow to reduce searches across systems, manual tasks and the need to put customers on hold while staff navigate those systems. Providing information and guidance at the point of use is also intended to help employees respond more quickly and support consistent service.

The design uses the human-in-the-loop principle. Customer service employees remain responsible for reviewing AI-generated information and making appropriate support decisions. Technology manages the collection and preparation of information, while the responsibility for the decision affecting the customer remains with people.

Reusable capabilities and goals of enterprise AI

BMO is designing the capabilities behind AI Agent Assist for reuse in other customer experiences and business processes. The contact center then provides a high-volume environment for the components the bank plans to insert into subsequent agent AI applications, extending the work beyond a single service process.

Greg Brown, Head of Enterprise AI Transformation and Chief Digital Officer for Personal and Business Banking Canada at BMO, described the work as expanding from individual use cases to large-scale AI, with clear barriers and people accountable for every decision.

Brown also linked this approach to protection and oversight as AI agents play a growing role in financial services. Security, privacy and human control are central to BMO’s approach as it builds its capabilities and creates the conditions for broader AI experiences.

The work supports BMO’s stated corporate goal of generating more than $1 billion in revenue growth, productivity improvements and operational efficiencies through AI by 2030. The figure covers the bank’s broader AI ambition, rather than a value assigned to AI Agent Assist alone.

The immediate test is whether AI-supported case preparation can shorten eligible calls and automate some eligible claims while employees retain responsibility for service decisions. Because the underlying capabilities are designed for reuse, the implementation links BMO’s service level objectives to a broader operational question: whether operational benefits, oversight and human accountability can remain together when the technology is applied to other processes.