2025/12 | LEM Working Paper Series | ||||||||||||||||
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Predictive AI and productivity growth dynamics: evidence from French firms |
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Luca Fontanelli, Mattia Guerini, Raffaele Miniaci and Angelo Secchi |
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Keywords | |||||||||||||||||
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Artificial intelligence, productivity growth volatility, coarsened exact matching
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JEL Classifications | |||||||||||||||||
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D20, O14, O33
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Abstract | |||||||||||||||||
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While artificial intelligence (AI) adoption holds the potential to
enhance business operations through improved forecasting and
automation, its relation with average productivity growth remain
highly heterogeneous across firms. This paper shifts the focus and
investigates the impact of predictive artificial intelligence (AI) on
the volatility of firms' productivity growth rates. Using firm-level
data from the 2019 French ICT survey, we provide robust evidence that
AI use is associated with increased volatility. This relationship
persists across multiple robustness checks, including analyses
addressing causality concerns. To propose a possible mechanisms
underlying this effect, we compare firms that purchase AI from
external providers ("AI buyers") and those that develop AI in-house
("AI developers"). Our results show that heightened volatility is
concentrated among AI buyers, whereas firms that develop AI internally
experience no such effect. Finally, we find that AI-induced volatility
among "AI buyers" is mitigated in firms with a higher share of ICT
engineers and technicians, suggesting that AI's successful integration
requires complementary human capital.
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