The AI Productivity Illusion - by Matt Scherer - Hard Reset

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The AI Productivity Illusion<br>Productivity Is About (Much) More than Finishing Tasks Quickly

Matt Scherer<br>Jul 19, 2026

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Matt Scherer is a fellow at Open Markets Institute, where his research and advocacy focus on developing policy responses to the eventual bursting of the AI bubble. His Hard Reset pieces focus on highlighting the risks posed by the AI bubble and pushing back against the hype that is inflating it. The opinions expressed here are solely his own.<br>It’s easy to see why people think generative AI is a revolutionary technology. After all, lots of jobs involve writing, and ChatGPT, Claude, and other large-language-model-based systems can write faster than any human can. As a result, and in addition to the anecdotes from people saying, “I have 10Xed my productivity using AI,” there are empirical studies showing that people can complete certain tasks, such as coding, significantly faster with AI. Because AI so clearly makes lots of individual people more productive, it seems like a foregone conclusion that it will do the same for the economy as a whole.<br>So why is it that, four years after ChatGPT’s release, generative AI has not yet improved productivity at either the level of individual companies or across the economy as a whole?<br>Thanks for reading! This post is public so feel free to share it.

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Some have referred to this apparent disconnect as a “productivity paradox,” a phrase that economist Erik Brynjolfsson (building on an observation by Robert Solow) coined to refer to the period in the 1970s and 1980s when information technology was advancing rapidly but economy-wide productivity statistics barely budged. Once companies restructured their organizations and workflows to center the computer and Internet, productivity growth did indeed pick up (although less dramatically than it did during the Industrial Revolution and after World War II). Brynjolfsson and others think the same thing is happening with AI. Once companies rewire themselves for the AI era, they say, real productivity gains will come.<br>But there may be a much simpler explanation: the mere fact that AI allows people to work faster does not mean it is increasing productivity, at least not in the ways that truly matter.<br>In casual conversation, when someone says that they have increased their “productivity,” they typically mean they are producing more stuff in less time. In this context, productivity means:

But in the economic sense, which is the sense that matters in determining how a technology will affect businesses and economies, “productivity” (specifically, total factor productivity) is not about how much you produce or how quickly you produce it. It’s about the economic value of your inputs and outputs, rather like a large-scale version of return-on-investment:

To be sure, the colloquial and economic meanings of productivity overlap quite a bit. Looking at the numerators, more stuff typically translates to more economic value. A manufacturer can typically get more money by selling 1,000 widgets than it can by selling 500. Likewise, looking at the denominators, cutting down the time it takes to produce a good or service tends to increase economic productivity because time is a key economic input, especially if human labor is part of the production process. If you only need 10 hours to complete a $500 task that used to take you 20 hours, you have doubled both your casual/personal productivity and your true/economic productivity.<br>There is much more to economic productivity, however, than just quantity and speed. And that is where the disconnect between productivity in the more casual personal sense and productivity in the technical economic sense lies.<br>For starters, the economic value of a good or service depends on its quality, not just its quantity. Quantity certainly matters; the Industrial Revolution began with textiles in large part because new machines made it possible to produce vastly more clothing and other textiles in vastly less time by automating the various tasks involved in textile production. But, crucially, automating those tasks did not reduce the quality of the textiles. In fact, it usually improved it.<br>A scene in the musical Fiddler on the Roof contains a fictional-but-memorable illustration of this. In the scene, the tailor Motel gets a new sewing machine. Motel excitedly explains to his neighbors that the sewing machine “works twice as fast.” Holding up a swath of fabric, he points out “how close and even the stitches are” and exclaims, “from now on, my clothes will be perfect—made by machine!”

It was not just the machine’s speed that he valued; it was its precision and reliability. Regardless of how quickly it allowed him to work, Motel presumably would have preferred to stick with manual tailoring if his sewing machine frequently went rogue and produced shirts that were the wrong size, contained a third...