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As AI becomes more embedded in the workplace, it’s reshaping roles, responsibilities, and the overall design of work. Middle management is one area feeling this shift acutely, as tasks that once defined these roles—such as status updates, performance tracking, project coordination, and operational decisions—are now increasingly handled by AI-powered dashboards, copilots, and workflow assistants. A new Harvard Business School study, referenced in this HBR article, analyzed over 50,000 developers using GitHub Copilot and found that generative AI is accelerating a shift in task distribution, with individual contributors spending more time on core work (coding) and less on project management—once the domain of their managers. Specifically, coding activity as a share of total work rose by 5%, while project management fell by 10%. As AI enables employees to work more independently, it reduces the need for constant managerial oversight. This shift can help flatten hierarchies and allow middle managers to focus on higher-value work. To realize these benefits, organizations can begin by examining how work actually gets done—evaluating workflows, recognizing how AI is already in use, and having candid conversations with managers about how it can elevate their roles. While the article offers helpful ideas, I’m also resharing my one-page cheat sheet to help organizations think through AI’s implications for work task execution.
