Based on reporting by Rafael Müller (Ad Hoc News).
BMO deploys AI agent to speed up credit card dispute resolution
Bank of Montreal (BMO) has launched a new internal tool called AI Agent Assist, designed to help its customer service representatives resolve credit card transaction issues faster. Announced on Friday, November 6, the system uses agentic artificial intelligence to streamline the workflow for employees at BMO’s Virtual Connect contact centre in Canada. The primary goal is to reduce the time clients spend waiting for resolutions and to automate the processing of eligible credit refund requests, potentially allowing customers to receive refunds on the same day.
What the new tool does
According to BMO, the Virtual Connect contact centre receives more than 500,000 calls annually from Canadian clients regarding credit card transactions. Currently, resolving these inquiries takes an average of 12 to 14 minutes per call. The new AI Agent Assist tool is built for in-house use by bank employees rather than direct interaction with customers. It provides workers with AI-enabled transaction matching, policy retrieval, and case preparation directly within their workflow.
By consolidating this information, the tool aims to reduce the time employees spend navigating between different internal systems. BMO stated that it expects the implementation to lower the time spent resolving client inquiries by 20% to 30%. Additionally, the system is designed to automatically process approximately 40% of eligible credit refund requests. For qualifying inquiries, this automation could mean clients receive their credit as soon as the same day, rather than waiting for manual processing.
Human oversight remains central
BMO emphasized that the tool is designed with a “human-in-the-loop” principle, ensuring that people remain at the center of key decisions. Holly Jackson, who heads Virtual Connect, explained that the goal is to give employees the necessary information and guidance so they can focus on helping the client rather than managing technical systems. “When clients call us about a credit card transaction, they want clarity and a quick resolution,” Jackson said. “AI Agent Assist gives our employees the information and guidance they need, so they can spend less time moving between systems and more time helping the client.”
Why this matters for the banking industry
The move highlights a broader trend in the financial sector where banks are adopting generative AI for analytical tasks but remain cautious about fully autonomous execution. Research from PYMNTS Intelligence indicates that while the use of generative AI for cash flow management surged from 16% in 2025 to 80% in 2026, the adoption of agentic AI, which acts independently, has dipped slightly from 6% to 5%. This suggests that while AI is becoming common in systems that analyze data and recommend actions, autonomous execution remains rare. BMO’s approach, which uses AI to assist human workers rather than replace them, aligns with this cautious industry stance.
For investors, this initiative represents a productivity and efficiency play. By reducing the average handle time for calls and automating a significant portion of refund requests, BMO aims to improve operational efficiency and enhance the customer experience. This can lead to higher customer satisfaction and retention, which are critical metrics for retail banking performance. The tool also reduces the need to place customers on hold, a common pain point in customer service interactions.
What to watch next
As BMO rolls out AI Agent Assist, the bank will likely monitor key performance indicators such as the average time to resolution, the percentage of automated refunds, and customer satisfaction scores. The success of this pilot will depend on how effectively the AI integrates with existing systems and whether it can consistently meet the 20-30% reduction in resolution time. Other financial institutions may look to BMO’s results as a benchmark for their own AI adoption strategies, particularly in customer service operations. The broader industry will continue to balance the benefits of AI automation with the need for human oversight, especially in areas involving financial transactions and customer trust.
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