The AI Payoff Starts With Workflow Redesign

Banks looking for value from AI may need to start with the work itself: how it moves, where it slows down, and where human judgment still matters most. 

In a recent episode of the ProSight Banking Strategies podcast, Lindsay Soergel, founder and principal of Apple PIE Consulting, says financial institutions miss the larger opportunity when they approach AI as a traditional software rollout or a simple cost-cutting exercise. The bigger value comes when banks redesign work around human-plus-AI collaboration—then help employees understand how that collaboration is supposed to function. 

Soergel explained several practical implications: 

AI has to fit the workflow. Soergel is direct: “AI adoption succeeds or fails at the workforce workflow level and not at the technology level.” That means banks should map each workflow carefully before layering AI into it, including the tasks, handoffs, and decision points the employee is expected to support. 

Leadership support cannot be passive. AI adoption “never even gets started adequately for real without full vocal support and advocacy and visible usage by the C-suite,” Soergel says. In her view, this is a major change-management effort. Senior leaders do not need to be the most technically proficient people in the institution, but they do need to set the tone and show that AI is part of how the organization is adapting. 

The people closest to the work should help shape the change. Frontline employees understand operational friction: where issues occur, where expectations are out of balance, and where human judgment is “absolutely irreplaceable.” That makes them valuable architects of AI-enabled workflows. As Soergel says, “people who are closest to the work are the most important architects of the transformation, not the technologists.” 

Productivity gains will not look the same everywhere. Workflow redesign can produce significant efficiency, including cases where institutions have seen “as much as an 80% productivity gain.” But each team does different work. Some functions will adapt AI more extensively than others, and the level of lift will vary. 

The goal is more capacity for higher-value work. AI can take on labor-intensive tasks in a collaborative way, freeing people for “the thinking, the judgment, creativity, operational expertise” that differentiate a financial institution. In customer-facing areas, that could mean relationship managers spend less time preparing data and more time deepening client relationships. 

The takeaway: Banks will not capture the full value of AI by installing tools and hoping workflows improve around them. The payoff starts when institutions redesign the work, involve the people who know it best, and make human-plus-AI collaboration part of how the organization operates.