The Illusionary Model of Relative Economic Growth in the Era of Artificial Intelligence
Gianmario Strappati · Advances in Management and Applied Economics · 19 Jun 2026
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Where this sits in the debate
- Will AI actually boost productivity and growth? · its finding goes against the claim (why studies differ)
Direction of the finding as read from the abstract by an AI model (AI-written).
Key takeaway AI-written
A cross-country panel study using OECD productivity, patent and intangible-capital data to test whether AI innovation raises aggregate productivity. It finds AI patent intensity has weak, statistically insignificant links to total factor productivity, while intangible capital is tied to localized sectoral gains, suggesting AI's efficiency effects diffuse only weakly across economies.
Abstract
Artificial Intelligence (AI) is increasingly viewed as a major driver of productivity growth and economic transformation. This paper challenges the assumption that AI-related technological expansion necessarily generates widespread macroeconomic productivity gains. Drawing on endogenous growth theory and the productivity paradox literature, it introduces the Relative Economic Growth Illusion (REGI) framework, which argues that contemporary AI-driven growth may operate through concentrated and intangible-intensive economic structures rather than through broad productivity diffusion across the economy. Using cross-country evidence from OECD Productivity, OECD STAN, OECD Patents, INTAN-Invest, and Functional Urban Areas (FUAs) databases, the study combines descriptive analysis with panel and robust regression techniques to examine the relationship between AI innovation, productivity, and intangible capital accumulation. The results show that AI patent intensity has weak and statistically insignificant associations with aggregate Total Factor Productivity (TFP), while intangible capital accumulation remains strongly linked to localized sectoral productivity gains. Evidence also reveals a marked geographical concentration of AI-related innovation within a limited number of technologically advanced economies. These findings suggest that AI-driven technological progress generates localized efficiency improvements while diffusing only weakly across the broader economy. As a result, observed economic expansion may increasingly reflect concentrated growth driven by intangible capital and technological concentration rather than broad-based productivity improvements. JEL classification numbers: O33, O47, D43. Keywords: Artificial Intelligence, Economic Growth, Productivity Paradox, Intangible Capital, Market Concentration, Technological Diffusion, Relative Growth.
About this publication
Academic journal. Published in an academic journal — typically peer-reviewed before publication, though indexing alone doesn't guarantee review depth.
- Published
- 2026 (4 months ago)
- Citations
- 0 (OpenAlex)
0 citations recorded by OpenAlex — too few 2026 papers in this collection for a fair comparison.
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