It's Actually Too Early to See Widespread AI Productivity Gains

“Today, you don’t see AI in the employment data, productivity data or inflation data,” says Torsten Slok, Apollo chief economist. “Similarly, for the S&P 493, there are no signs of AI in profit margins or earnings expectations.”

That is not without precedent, as that lag in quantifiable productivity impact also happened when computing technology was applied at work. In fact, it often happens that productivity actually decelerates when a new computing or other general-purpose technology is introduced.

GPTs are "consequential" innovations that transform entire economies over time.


source: MIT

So that J curve is not unusual.

But it might also be the case that productivity measurements are outdated. “It’s possible that “current measures of productivity do not capture the increases in value added that these technologies promote,” the McKinsey co-authors state. “Many new benefits are incorporated into products or services free of charge, for example, which means productivity statistics do not capture them.”

The best available evidence suggests that mismeasurement might explain up to 10 percent of the overall slowdown in productivity growth, a relevant but comparatively small effect,” they say.

Here’s a look at expected productivity gains from artificial intelligence. The impact might be less than you would expect.

source: Apollo Academy

Looking only at generative AI, there are clear and significant time savings, for example.



source: Visual Capitalist



source: Visual Capitalist

But those gains do not translate linearly into firm productivity statistics. Among the reasons: the need to recraft whole business processes (requiring new skills, organizational structure changes).

“General purpose technologies (GPTs) such as AI enable and require significant complementary

investments, including co-invention of new processes, products, business models and human

Capital,” say the authors of a paper published by the National Bureau of Economic Research. “These complementary investments are often intangible and poorly measured in the national accounts, even when they create valuable assets for the firm.”

Also, keep in mind that “whole economy” productivity tends to improve at rates between one percent and two percent annually, over time.

source: St. Louis Federal Reserve

So some economists note that measurable or quantifiable gains from other earlier GPTs took decades, though the impact of computing technologies happened much faster.

source: JP Morgan.

As noted above, AI impact on tasks can be quite high, but the impact on gross national product or productivity will not track in linear fashion. Greater output with similar or less input leads to measurable productivity gains only when the output affects sales and other revenue-related activity.

Isolating the impact of particular inputs requires us to make judgments. When multiple processes change, how do we evaluate the individual impact? If sales channels, production processes, marketing, advertising, applied AI, headcount and customer demand all change at once, any estimation of input factor contribution is subjective.

But in any case, it actually is too early to document AI-driven productivity increases. And the actual impact could well be negative.