#productivity-paradox

#productivity-paradox

Your company has rolled out AI like it's a new office uniform. Everyone's using it. And unlike most uniforms, people are using it even when they are told not to. As a result, your inbox clears itself, your reports write themselves, and meetings collapse into neat little summaries at the click of a button. You may be even be fantasizing about sending your digital clone to those pointless meetings, and perhaps your colleagues have done so already (which may explain their perfect attendance record).

But many engineering teams are noticing a trend: even as individual developers produce code faster, overall project delivery timelines are not shortening. This isn't just a feeling. A recent METR study found that AI coding assistants decreased experienced software developers' productivity by 19%. "After completing the study, developers estimate that allowing AI reduced completion time by 20%," the report noted. "Surprisingly, we find that allowing AI actually increases completion time by 19%-AI tooling slowed developers down."

When Peter Drucker first met IBM CEO Thomas J. Watson in the 1930s, the legendary management thinker and journalist was somewhat baffled. "He began talking about something called data processing," Drucker recalled, "and it made absolutely no sense to me. I took it back and told my editor, and he said that Watson was a nut, and threw the interview away."

In a 1987 article in the Times Book Review, Robert Solow, a Nobel-winning economist at M.I.T., commented, "You can see the computer age everywhere but in the productivity statistics." Despite massive increases in computing power and the rising popularity of personal computers, government figures showed that over-all output per worker, a key determinant of wages and living standards, had stagnated for more than a decade.