The megamanager era: AI is doubling bosses’ workloads—and the costs are just beginning to show

The expertise paradox

The average American manager now oversees 12 direct reports, and the data suggest AI is both the cause and justification for this quiet but seismic shift in how the U.S. workplace is organized. It is one of the starkest structural changes in the modern American office, and it is happening with relatively little public debate about what, exactly, is being traded away in the name of efficiency.

Neil Thompson, a research scientist at MIT who studies how AI capabilities evolve across the economy, offers a more nuanced frame for understanding what’s actually at stake. In his research—which evaluated 40 AI models across thousands of real-world job tasks, each assessed by practitioners in the relevant field—Thompson and his colleagues find that automation doesn’t affect all parts of a job equally. The critical variable is whether the tasks being automated are the expert parts of a role or the administrative scaffolding around them.

“If part of your job gets automated, and it’s something that really didn’t use the expertise that you needed, that’s great,” Thompson said. “You get to spend more of your time on the part of your job that is really valuable.” His research, coauthored with MIT economist David Autor, finds that when automation eliminates the lower-expertise components of a job, wages for the remaining workers actually tend to rise: There are fewer of them, but they’re doing more of what makes them irreplaceable. The danger, Thompson warns, is the opposite scenario: When AI targets the expert core of a role—the way GPS wiped out the navigational mastery that once defined a taxi driver’s craft; wages fall, and the profession’s identity hollows out.

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