What if the biggest AI disruption isn’t at the entry level, but right in the middle of your org chart? Bill Banham sits down with Brian Kropp, VP of Global Insights at Heidrick and Struggles, to explore why the winners are treating AI as a people and change problem, not a tech project—and how that shift rewrites HR’s mandate.

We start with speed. Startups jump from idea to pilot in 30 days; large enterprises often take 270. Training alone won’t fix that gap. Brian lays out a concrete path: give teams specific tasks and roles to experiment with, shrink approvals, and track learning as a real return. He makes a sharp case for “R before ROI,” arguing that early value shows up as capability, not neat cost savings, and that CHROs should design experiments that surface where returns exist before scaling investment.

Then we tackle the middle manager shakeup. Scheduling, approvals, status updates, and first-line coaching are ripe for automation or AI agents. That could remove 30 to 50 percent of a manager’s workload, forcing a choice: fewer managers or a redesigned role focused on judgment, sensemaking, escalation, and culture. Brian Kropp warns that without a plan, finance will default to cuts that hurt long-term capacity. He also maps where job evolution is most visible—from call centers and finance ops to diagnostic work—and why liberal arts and market insight skills may surge as tech meets cultural change to create breakthrough opportunities.

The conversation closes with two pivotal moves: setting an explicit formula to split AI savings between margin and reinvestment in people, and standing up a new role—VP of AI Workforce Transformation. This team would own task design for automation vs augmentation, agent selection and “performance management,” and the operating system for fast, safe experimentation at scale. If you’re a CHRO, HR leader, or curious operator, this is a pragmatic playbook for turning demos into durable advantage.

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