“Amy has the what. I help with the how”: Inside Bank of America’s data and AI partnership

Amy Avery, Managing Director, Analytics, Modeling and Insights, took her job at Bank of America because of a number. When she interviewed at Bank of America, she was told that the bank interfaced with, at the time, 67 million clients. “Gosh, that’s so much information,” she remembers thinking. “Think about what you could do with that.” She started in January 2020. Two months later, the pandemic made that abstraction very literal: the bank suddenly needed to know, in real time, how its customers were doing, thinking, and coping. Avery’s job was to figure out how to answer that.

Michelle Boston, Head of Data Management Technology & Enterprise Architecture, arrived by a different route entirely. She built her career in enterprise technology, rose to CIO of a startup that was eventually built and sold, and came to Bank of America first as a contractor to lead an information architecture practice. “Data has always kind of been in my blood,” she said. At Bank of America, she works at a scale few other organizations have and builds the platforms that serve as the enabling force for Avery’s work. 

Despite a very different set of starting points, the two describe a partnership that has essentially erased the line between their jobs. “We probably know each other’s jobs better now than before generative AI showed up”, Avery said, because the pace of the last two years has forced her strategy team and Boston’s engineering team to make decisions in near lockstep. 

Listen to the full episode to hear how Avery and Boston have built a shared language across the two functions, and how they’re stress-testing it against a technology cycle that seems to wait for no one.

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