Two of the largest U.S. banks rolled out artificial intelligence tools, each aimed at cutting friction from a different part of daily operations.
Bank of America embedded AI into the full life cycle of wealth management client meetings. U.S. Bank introduced an in-house AI tool to speed up its digital design process. Both moves signal that banks are no longer treating AI as a standalone feature but as working infrastructure inside core teams.
BofA Automates the Meeting
Merrill Wealth Management and Bank of America Private Bank announced the full-scale rollout of AI-Powered Meeting Journey, a workflow tool that handles preparation, note-taking and follow-up for financial advisers. The bank says the capability can save advisers up to four hours per client meeting, across millions of meetings annually.
The tool works in three stages. Before a meeting, it pulls together client relationship data and recent account activity into ready-to-use briefing materials. During online meetings, with client consent, it records and summarizes the conversation. Afterward, it produces task lists and documentation based on the discussion.
Patricio Diaz, chief operating officer at Merrill, said the rollout moves advisers away from administrative preparation and toward client strategy and relationship work. Shimna Sameer, head of products, solutions and platforms at Bank of America Private Bank, said early users reported measurable time savings in their daily workflows.
The launch builds on the bank’s infrastructure, developed over more than a decade. As reported by PYMNTS, CEO Brian Moynihan has pointed to Erica, the bank’s AI-driven virtual assistant, as proof that AI tools are moving beyond customer-facing features into functions that directly affect staffing and productivity decisions. The bank spends $4 billion annually on new technology initiatives, including AI, out of a total technology budget of $13.5 billion.
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AI-Powered Meeting Journey runs on the same platform as ask MERRILL and ask Private Banking, internal AI tools advisers already use to find information and connect with colleagues. The bank is layering new capabilities onto existing systems rather than standing up separate ones, a pattern that keeps deployment costs down and speeds rollout across the enterprise.
U.S. Bank Brings AI Into Design
U.S. Bank is using AI to solve a problem that sits earlier in the product life cycle: how long it takes to move a digital product from concept to customer.
As reported by Banking Exchange, the bank introduced Design Assistant, an in-house AI tool that reviews designers’ work, flags likely issues and suggests improvements across its digital products.
The initiative grew out of a mid-2025 internal review of design workflows, during which teams mapped existing processes and identified the most common delays. According to Banking Exchange, a key question was how AI could shorten the path from initial idea to a live product that customers actually use.
Design Assistant draws on performance data to identify where problems typically surface, whether during early design, at the handoff to engineering, or after a product goes live. Embedding those patterns directly into the tool means teams spot issues earlier, before they generate rework or delay releases.
The approach shows a broader pattern in how banks are deploying AI inside technology teams. As covered by PYMNTS, Royal Bank of Canada is targeting up to $1 billion in AI-generated value by 2027, in part by using AI coding tools to compress development cycles and accelerate product delivery across its engineering team. U.S. Bank’s Design Assistant targets a comparable layer: the handoff between design, engineering and production, where delays accumulate and quality problems originate.
The competitive picture continues to widen. As reported by PYMNTS, Citigroup launched an upgraded internal AI platform that lets employees compress multistep tasks across systems into a single request. Bank of America and U.S. Bank are extending that same logic, but in opposite directions: one into client-facing adviser workflows, one into the internal build process that produces digital products in the first place.
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