Unpacking McKinsey 2026 – Part 2
Most companies today are experimenting with AI, and that’s a good thing. The downside is that very few are capturing real value. According to McKinsey, nearly 90 percent of organizations are testing AI in some way, yet most report little bottom-line impact. This makes sense when we realize that these organizations are layering AI onto existing structures. It’s expedient; it feels doable. Ultimately, however, this effort is a distraction that hampers long-term gains in productivity and growth.
Leaders may feel their organization is trapped in an ongoing transformation loop, exacerbated by the demands of AI adoption. But AI isn’t the transformation—organizational design is. Without getting too meta, you might say that we should use AI to help us use AI. Instead of using AI to do work, we can use it to redesign how the work actually happens.
The mistake many well-intentioned leaders are making is that they treat AI as a technology project to automate a few tasks. That’s not a bad start. But unleashing the full value of AI must be seen as an operating model challenge. Real, long-term productivity gains happen when organizations rethink entire workflows. Adoption becomes adaptation.
Consider how Henry Ford’s moving assembly line transformed manufacturing by introducing rigid step-by-step tasking. Today, AI systems break from this traditional workflow model with self-optimizing systems that can adapt in real time, using live data to accommodate new priorities. If organizations hope to compete in this shifting marketplace, leaders must reimagine business strategy, structures, and processes in a way that effectively redistributes tasks between humans and machines.
The winners in the AI integration race will be those who redesign work by addressing these simple questions:
What should humans do?
What should machines do?
How might they work together?
The obvious, beautiful irony in the equation is that the rise of AI increases the importance of human leadership. Human beings excel where AI agents fail. These are the differentiators: judgment, creativity, empathy, and decision-making under uncertainty.
Technology scales intelligence: it analyzes massive amounts of data and builds shortcuts through the clutter to help us see what to do next. AI may even provide a detailed map. But leadership scales belief in the journey: is it worthwhile, is it ethical, is it good for me? It is belief in the journey that allows organizations to move through uncertainty, to sustain growth, and to prosper as human beings. Technology can point the way, but we need empathetic humans to lead the way.
