For decades, technologies have largely been built as tools, extensions of human intent and control that have helped us lift, calculate, store, move, and much more. But those tools, even the most revolutionary ones, have always waited for us to ‘use’ them, assisting us in doing the work—whether manufacturing a car, sending an email, or dynamically managing inventory—rather than doing it on their own.

With recent advances in AI, however, that underlying logic is shifting. “For the very first time, technology is now able to do work,” Nvidia CEO Jensen Huang recently observed. “[For example], inside every robotaxi is an invisible AI chauffeur. That chauffeur is doing the work; the tool it uses is the car.”

This idea captures the transition underway today. AI is no longer just an instrument for human use: Rather, it is becoming an active operator and orchestrator of “the work” itself, not only capable of predicting and generating, but also planning, acting, and learning. This emerging class—“agentic” AI—represents the next wave of artificial intelligence. Agents can coordinate across workflows, make decisions, and adapt with experience. In doing so, they also blur the line between machine and teammate.

For business leaders, that means agentic AI upends the fundamental management calculation around technology deployment. Their job is no longer simply installing smarter tools but guiding organizations where entire portions of the workforce are synthetic, distributed, and continuously evolving. With agents on board, companies must rethink their very makeup: how work is designed, how decisions are made, and how value is created when AI can execute on its own. How organizations redesign themselves around these agentic capabilities will determine whether AI becomes not just a more efficient technology, but a new basis for strategic differentiation altogether.

To better understand how executives are navigating this shift, BCG and MIT Sloan Management Review conducted a global study of more than 2,000 leaders from 100+ countries. The findings show that while organizations are rapidly exploring agentic AI, most enterprises still need to define the overall strategies and operating models needed to integrate AI agents into their daily operations.