AI as an Innovation in the Method of Innovation: Implications for Productivity Growth in the US and Europe

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This paper estimates the possible AI contribution to future labor productivity growth assuming that AI is both a “general purpose technology” and an “innovation in the method of innovation.” The framework used in this paper separates an upstream innovation sector from a downstream production sector. The impact of AI is modelled as (a) boosting upstream total factor productivity (a “production effect”) and (b) enhancing intangible capital use downstream (a “use effect”). The framework can be used to show how AI’s boost to upstream total factor productivity growth can drive long-term labor productivity growth. We relate this framework to the “task accounting” framework commonly used. We have two main findings. First, we argue that AI can already be seen in productivity statistics for the United States. The production and use effects of software and software R&D (alone) contributed (a) 50 percent of the 2 percent average rate of growth in US nonfarm business labor productivity from 2017 to 2024 and (a) 50 percent of its 1.2 percentage point acceleration relative to the pace from 2012 to 2017. Second, taking additional intangibles and data assets into account, we calculate a long-run contribution of AI to labor productivity growth based on assumptions that follow from the recent trajectories of investments software, software R&D, other intangibles, and their contributions to growth in both US and Europe. Our central estimates are that AI will boost annual labor productivity growth by as much as 1 percentage point in the United States and about .3 percentage point in Europe.