As major banks move beyond internal tools to systems that support actual customer interactions, AI agents are starting to play a more direct role in how financial advice is delivered.
According to Banking Dive, Bank of America is currently implementing an in-house AI-powered advisory platform for some of its financial advisors, which has been rolled out to approximately 1,000 financial advisors. The move is one of the clearer early examples of how AI is being used in core banking operations, rather than back-office operations or limited pilots. This also reflects a broader shift across industries, where AI is moving from basic assistance to systems that can support decision-making in real time.
The platform is based on Salesforce’s Agentforce and enables the creation of AI agents to handle tasks. It is designed to help advisors process client inquiries and prepare recommendations. It also helps you manage your daily workflow. According to Banking Dive, the system is part of a broader effort among major banks to test how AI agents can work together with human staff, rather than operating as standalone tools.
Bank of America is expanding its use of AI across its business. According to Banking Dive, the bank says its virtual assistant Erica handles the work of about 11,000 employees, and all 18,000 software developers use AI coding tools, increasing productivity by about 20%. These numbers demonstrate how widely AI is embedded in different parts of organizations.
AI agents move closer to financial decision-making
This approach differs from previous AI deployments in the banking industry, which primarily focused on chatbots and internal productivity tools. In these cases, AI was used to answer simple questions and automate mundane tasks. The new system is built to handle more complex tasks, such as analyzing customer data and suggesting next steps.
This shift will bring AI closer to the core of financial decision-making. Rather than acting as a support layer, this technology is now embedded in the advisory process itself.
Other major banks are moving in a similar direction. The same Banking Dive report notes that companies such as JPMorgan, Wells Fargo, and Goldman Sachs are also testing AI tools aimed at improving productivity and supporting staff in client-facing roles, although these efforts vary and do not always focus on advisor-specific AI agent systems. Although each bank takes a different approach, the common goal is to increase production without expanding headcount at the same rate.
Early data suggests these tools can improve efficiency, although results are mixed. In some cases, banks are reporting improved speeds for advisors to access information and prepare for meetings, based on industry reports and early rollout feedback cited by Banking Dive. At the same time, there are ongoing concerns about accuracy and oversight, especially when AI systems are used to inform financial decisions.
A broader pattern is emerging across financial services. While many institutions are investing in AI, they are often doing so in a controlled manner, with adoption limited to specific teams and use cases. The goal is to test how the technology works in a real-world environment before expanding it further.
Some analysts remain cautious about how quickly AI will change the banking industry. According to Banking Dive, Wells Fargo analyst Mike Mayo said recent developments have yet to produce any major new products and the current stage is “a little boring from a product perspective.”
Human surveillance remains central
Bank of America’s expansion is notable for its size and location. Financial advisors are at the heart of the bank-customer relationship, especially in wealth management. Introducing AI into the role signals an increased level of trust in technology. It also shows a willingness to influence how advice is produced and delivered.
At the same time, this system does not replace advisors. Instead, it is intended to work in conjunction with them. Human oversight remains an important part of the process, especially when dealing with complex financial decisions or high-value customers. Industry executives also acknowledge that AI is unlikely to completely replace the role of experts, especially in complex financial workflows where context and judgment remain important.
This hybrid model is becoming common in all sectors. Rather than removing humans from the loop, banks are looking to combine human judgment with machine-generated insights. Some companies are starting to treat AI as part of the workforce rather than a tool, with staff expected to work alongside these systems in their daily work.
Progress comes with limits and trade-offs
There are also practical challenges. AI systems rely on clean, structured data, but this isn’t always easy to achieve in large organizations with legacy systems. Integration with existing tools may take time, and staff training may be required to use the new system effectively.
Regulation adds further complexity. Financial institutions need to ensure that AI-powered recommendations meet compliance standards. You also need to be able to explain when asked by regulators. This requirement could limit the amount of autonomy provided to AI systems, especially in areas such as lending and investment advice.
Despite these constraints, banks are beginning to move beyond experimentation to operations, even if progress is uneven. Some estimates suggest that up to a third of banking operations, or a portion of them, could eventually be handled by AI, although the timeline remains uncertain.
Introducing AI agents into advisory roles also raises questions about how the work itself will change. As systems can handle more analytical work, advisors will be able to spend less time preparing and more time engaging with clients. Over time, the skills required for the role may change.
At the same time, reliance on AI brings new risks. Errors in data or model output can impact recommendations, and over-reliance on automated systems can reduce critical review by human staff. These issues continue to be studied as adoption expands.
It is not just the technology that determines the current stage, but where it is used. Incorporating AI into a front-line role suggests that banks view AI as a tool to shape outcomes, rather than simply improving efficiency behind the scenes.
Bank of America’s developments provide perspective on how that transition will play out. This shows large institutions testing the extent to which AI can be integrated into daily operations while maintaining human oversight.
As more banks follow a similar path, the focus is likely to shift from whether to use AI to how to manage it once it becomes part of core operations.
See also: Visa prepares payment system for AI agent-initiated transactions
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