SKN | Bank of Montreal Introduces AI Agent Assist to Improve Contact Centre Efficiency

Key Takeaways:

• Bank of Montreal (TSX) has introduced AI Agent Assist within its Virtual Connect contact centre to support employees handling client interactions.
• The system brings transaction data, banking policies and case details into a consolidated view, helping staff manage eligible credit card enquiries more efficiently.
• BMO expects the technology to contribute to its broader AI strategy, with early performance indicators including a targeted 20% to 30% reduction in handling time and approximately 40% automated processing of eligible refund requests.

BMO Brings AI Assistance Into Client Support

Bank of Montreal is expanding the practical use of artificial intelligence across its banking operations with the introduction of AI Agent Assist in its Virtual Connect contact centre.

The tool is designed to support employees during client conversations by bringing relevant transaction information, banking policies and case details into a single view. It applies real-time transaction matching and case-handling capabilities, allowing staff to spend less time gathering information and more time addressing client needs.

The initial application focuses on credit card support in Canada. Virtual Connect handles more than 500,000 Canadian credit card calls annually, with average interactions lasting approximately 12 to 14 minutes. By automating parts of the transaction-matching and case-preparation process for eligible calls, BMO aims to improve service efficiency while retaining employees’ involvement in decisions and explanations.

The approach reflects a human-in-the-loop model, in which AI supports employees rather than independently replacing the customer-facing role.

Connecting AI Investment With Operational Efficiency

The launch fits into BMO’s wider strategy to integrate artificial intelligence into banking operations and generate measurable business benefits.

Management has linked its AI initiatives to an ambition of approximately $1 billion in AI-enabled revenue growth, productivity improvements and efficiency gains by 2030. Agent Assist provides a practical example of how that strategy could translate into improvements within a high-volume service function.

For a diversified North American bank with a market value of approximately CA$172.2 billion, operational improvements across customer service can have implications beyond individual contact centre interactions. More efficient case handling could help manage service demand, improve employee productivity and support a more consistent client experience.

However, the financial contribution will depend on whether productivity gains translate into measurable cost savings or improved service capacity. Technology investment could also place pressure on operating leverage if implementation and operating expenses rise faster than the benefits generated.

The Performance Indicators Investors Should Watch

The effectiveness of AI Agent Assist will ultimately depend on measurable operational outcomes rather than the launch itself.

Two indicators are particularly relevant: average handling time and the proportion of eligible credit card refund requests processed automatically.

BMO’s stated targets point to a potential 20% to 30% reduction in handling time and approximately 40% automated processing. Progress toward these objectives would provide an indication of whether the technology is delivering practical improvements in the contact centre.

A sustained reduction in call duration could allow employees to handle more interactions without proportionately increasing staffing requirements. Greater automation of eligible refund requests could also reduce repetitive administrative work, allowing employees to focus on more complex client situations.

The quality of those outcomes will matter alongside speed. Faster processing must remain consistent with accurate transaction handling, appropriate policy application and effective client communication.

Closing Insights

BMO’s AI Agent Assist represents a practical step in the bank’s broader effort to embed artificial intelligence into everyday financial services. Rather than positioning AI solely as a technology investment, the initiative connects automation directly with customer support, employee productivity and operational efficiency.

For investors, the next stage is evidence of execution. Improvements in handling times, automated refund processing and service quality will help determine whether the initiative can contribute meaningfully to BMO’s longer-term AI ambitions.

The broader strategic question is how effectively large banks can scale AI across their operations while maintaining human oversight, service standards and cost discipline. BMO’s rollout provides an example of that transition, but its long-term value will depend on measurable results.

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