"So despite all those PCs, it [productivity growth] was a lot lower. And [from] 2007 to 2019 it was 1.5 percent. If you look at these numbers, productivity is the foundation of job replacement and of job growth and a whole bunch of things. But when you look at this ... you begin to get the picture that information technology isn't measured always in as linear a way into productivity as people assume. It just isn't there."
"[Nobel Prize winning economist] Robert Solow said that by 1987 the effects of the PC revolution can be seen everywhere, except in the productivity statistics. That holds true today as well."
"The truth of the matter is that with the exception of 2001 to 2007 when productivity was 2.8 percent growth per year, we actually never did see the PC revolution, to the extent that you might imagine,"
Measured productivity growth did not rise with widespread PC adoption, with annual growth rates of 2.7% (1947–1973), 2.1% (1990–2001) and 1.5% (2007–2019), and a single uptick of 2.8% (2001–2007). Historical data illustrate a weak linkage between information technology adoption and measured productivity gains, a phenomenon often described as the Solow Paradox. No clear evidence shows current AI increasing productivity today, though future improvements in AI agents could change that. Estimates place potential displacement at 6% of jobs by 2030 (about 10.4 million) via RPA, business process automation, physical robotics and generative AI, and displaced jobs may not return.
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