I recently listened to an interview with strategy professor Rita McGrath on AI, and one idea stood out above all others: organizations may be focusing too much on AI itself and too little on how AI changes the way work is organized.
McGrath compared today’s AI boom to the arrival of electricity. Early factories simply replaced steam engines with electric motors while keeping the same structure. It took decades before managers realized electricity enabled entirely new ways of organizing work. Her argument is that we are making a similar mistake with AI.
This resonated strongly with the research I conducted for my master’s thesis on human-AI collaboration. Many of my interviewees used AI to improve existing tasks, like summarizing reports, drafting documents, and organizing information. While this was valuable, these applications are largely incremental. The more interesting question is whether AI will fundamentally change how organizations innovate, make decisions, and collaborate.
Another insight that aligned with my research was McGrath’s warning against measuring AI adoption. Organizations should not reward employees for using AI; they should reward outcomes. The best AI users in my study were not focused on using AI more often. They were focused on creating better results.
I think that one of the most important takeaways is that leaders must think less like controllers and more like architects. AI implementation is rarely a technology problem. It is a people problem involving trust, responsibility, motivation, and organizational design.
We are still in the early chapters of the AI story. The organizations that benefit most may not be those that adopt AI the fastest, but those that rethink how work itself is structured.