Can AI restore RMs to their role as trusted advisors?

Commercial banking's most valuable client-facing professionals are spending most of their time on work that doesn't require their expertise — and clients are starting to notice. Relationship managers (RMs) were hired to be trusted advisors: to anticipate needs, navigate complexity, and help businesses grow. In practice, many spend the bulk of their day as operational coordinators — chasing answers across fragmented systems, liaising with back-office teams, and piecing together responses to questions that should take seconds to answer. Has the wire arrived? Why did the payroll file fail? Who are the authorized signers on this account?

These inquiries sound routine. But in banks where deposits, payments, lending, and treasury services still live in separate systems, answering them triggers a familiar and exhausting sequence: log in, chase down, piece together, respond. Repeat.

That's not a skills problem. It's a systems problem — and AI is increasingly well-positioned to solve it. In a recent Backbase webinar on AI in commercial banking, Arun Ramamoorthy put a striking number on the opportunity: with the right tools, RMs could devote up to 90% of their time to client-facing activities rather than internal coordination. That would represent one of the most significant productivity shifts the industry has seen in decades.

But the real opportunity isn't just efficiency — it's elevation. When an RM becomes the reliable, informed point of contact who can answer any question instantly and accurately, something important shifts: the relationship itself. Trust deepens. And from that foundation, the RM moves from reactive problem-solver to proactive advisor — anticipating needs before clients articulate them, spotting opportunities in the data, and offering the kind of insight that no self-service portal can replicate.

Commercial clients increasingly expect digital-era responsiveness. When their banking relationship feels primarily like a support ticket queue, the perceived value of having a dedicated RM erodes.

The question for bank leaders isn't whether AI will change the RM role. It will. The real question is whether you're using it to simply automate manual tasks or to fundamentally redesign how your teams show up for clients.

How is your organization thinking about RM productivity? Are you optimizing existing workflows, or reimagining the relationship model entirely?