AI Agents Enter Banking Roles at Bank of America

Muhammad Zulhusni, AI News
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AI agents are starting to take on a more direct role in how financial advice is delivered, as large banks move into systems that support client interactions.

Bank of America is now deploying an internal AI-powered advisory platform to a subset of financial advisers, rolled out to around 1,000 financial advisers, according to Banking Dive. The move is one of the clearer early examples of how AI is being used in core banking roles, where systems support decision-making in real time.

The platform is based on Salesforce’s Agentforce, which enables the creation of AI agents to handle tasks. It is designed to help advisers handle client queries and prepare recommendations. It can also help manage daily workflows. According to Banking Dive, the system is part of a wider push among major banks to test how AI agents can work alongside human staff.

Bank of America has been expanding its use of AI in its business. It’s said its virtual assistant Erica handles work equivalent to about 11,000 employees, while 18,000 software developers use AI coding tools that have improved productivity by around 20%.

AI agents move to financial decision-making
The approach differs from earlier deployments of AI in banking, which focused mainly on chatbots or internal productivity tools. In those cases, AI was used to answer simple questions or automate routine tasks. The newer systems are built to handle more complex work, including analysing client data.

Firms like JPMorgan, Wells Fargo, and Goldman Sachs are also testing AI tools aimed at improving productivity and helping staff in client-facing roles, though these efforts vary and are not always focused on advisor-specific AI agent systems. While each bank is taking a different approach, the common goal is to increase output without expanding headcount.

Banks report gains in how quickly advisers can access information or prepare for meetings, based on industry reporting and early deployment feedback. Yet there are ongoing concerns about accuracy and oversight, especially when AI systems are used to suggest financial decisions.

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