Artificial Intelligence and Firm Innovation: The Resource-Allocation Perspective

Alessandra Colombelli (), Maksim Belitski () and D’Amico, Elettra ()
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D’Amico, Elettra: University of Turin, http://www.est.unito.it/

Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio Carlo Alberto. WP series from University of Turin

Abstract: Extant research has established that firms increase absorptive capacity to engage in knowledge sourcing and technology adoption and to create knowledge internally to achieve two strategically important objectives: to become more innovative and commercialize innovation. We shift this conversation to a new direction by asking the question of how the adoption of Artificial Intelligence (AI) technology changes firm’s choice on resource allocation and shapes innovation performance. Using novel data on 14,143 UK firms over 2004-2020 and the two-step procedure to deal with endogeneity in innovation function, we find an inverted U-shape relationship between internal and external resource allocation and firm innovation and AI reduces the cost of knowledge investment, when these costs are high. Taken together, these results call for a fundamental rethinking of the resource allocation mechanisms and strategies used for firm innovation.

Pages: pages 57
Date: 2023-10
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