While many U.S. banks race to deploy AI tools, some bank executives say the biggest workforce impact will be how to save the institutional knowledge that could be lost as industry veterans retire. 

Nearly 40% of financial advisers are expected to retire within the next decade — and in more than 25% of the cases, there is no set plan to replace them, according to an April report from consultancy firm Wolters Kluwer. 

The dynamic is already shaping how banks think about AI implementation, Carissa Robb, managing partner of the banking practice at consultancy SolomonEdwards, told FinAi News.

“It’s not really about getting rid of the people, it’s about retaining the institutional knowledge that you will lose, whether that is your decision or their decision,” Robb said. 

“If you lose that institutional knowledge, your model, your agent will never be as successful with the edge cases and complex judgment calls.” 

Robb said the retirement wave predates AI and has been picking up steam in the past few years, but automation is accelerating the stakes around it. 

“That historical context, that’s what we’re losing,” she said. “I think that the institutions that are making room for those employees not to exit the workforce but to retool their experience in influencing and training and monitoring the AI tools will be most impactful, instead of saying your skills are no longer needed. 

“In fact, they are. They’re needed in a human training component for the AI capacity,” Robb said. 

Robb cautioned that FIs remain accountable if the tech doesn’t work. 

“Your vendor owns the technology, but you own the risk,” she said. “The bank owns the risk. The bank owns the judgment call. The bank owns the outcome.” 

Employees have to opt in to any AI-driven program to capture their institutional knowledge to avoid backlash, Robb said. “It’s more about knowledge retention than a shadow AI that surveils you.” 

One way of using AI for knowledge retention is keeping experience humans in the loop from the design phase to understand nuances and edge cases, Robb said.  

Another is deploying Claude or Copilot or other AI tools that work side by side employees and learn from their actions on how they go about their tasks, she said. 

AI in onboarding 

While SolomonEdwards is focused on retaining knowledge, other vendors say AI can  compress the time it takes new hires to become productive and limit the errors that come with manual, disconnected systems. 

With AI, “their jobs will get easier,” Justin DiPietro, chief strategy officer at customer service AI provider Glia DiPietro told FinAi News. “So onboarding time, the time to serve a customer decreases and the chance of error, plummets.” 

“If you translate knowledge and access back to the roots, I can give everyone their knowledge by just using all their past conversations,” DiPietro said. “And their access is really trust that will follow the procedures correctly.  

“So, I could put the procedures in our identity workflow and make sure everyone will use them.” 

AI can help level the playing field, too, DiPietro said, adding that new hires can get institutional knowledge access as quickly as on Day One rather than spending months and years collecting the relevant information. 

BMO, for one, reported during the bank’s fiscal third quarter earnings call on Aug. 25, that the bank’s frontline chatbot, Lumi Assistant, is “simplifying access to policy information across Canadian personal and business banking, increasing productivity amongst new employees by 17%.” 

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