It is often claimed that Artificial Intelligence (AI) is the next general purpose technology (GPT) with profound economic and societal impacts. However, without a consensus definition of AI and its empirical measurement, there are wide discrepancies in beliefs about its trajectory, diffusion, and ownership. In this study, we compare four AI patent classification approaches reflecting different technological trajectories, namely (1) short-range, (2) academic, (3) technical, and (4) broad interpretations of AI.

We use US patents granted between 1990-2019 to assess the extent to which each approach qualifies AI as a GPT, and study patterns of its concentration and agency.

Strikingly, the four trajectories overlap on only 1.36% of patents and vary in scale, accounting for shares of 3-17% of all US patents. Despite capturing the smallest set of AI patents, the short-range trajectory identified by the latest AI keywords demonstrates the strongest GPT characteristics of high intrinsic growth and generality. All trajectories agree, however, that AI inventions are highly concentrated within a few firms and this has consequences for competition policy and market regulation. Our study highlights how various methods of defining AI can lead to contrasting as well as similar conclusions about its impact.


Hötte, K., Tarannum, T., Verendel, V. & Bennett, L. (2023). 'AI Technological Trajectories in Patent Data: General Purpose Technology and Concentration of Actors'. INET Oxford Working Paper No. 2023-09.
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