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Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data

Christian Rammer, Gastón P. Fernández and Dirk Czarnitzki

No 674605, Working Papers of Department of Economics, Leuven from KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven

Abstract: Artificial Intelligence (AI) represents a set of techniques that enable new ways of innovation and allows firms to offer new features of products and services, to improve production, marketing and administration processes, and to introduce new business models. This paper analyses the extent to which the use of AI contributes to the innovation performance of firms. Based on firmlevel data from the German part of the Community Innovation Survey (CIS) 2018, we examine the contribution of different AI methods and applications to product and process innovation outcomes. The representative nature of the survey allows extrapolating the findings to the macroeconomic level. The results show that 5.8% of firms in Germany were actively using AI in their business operations or products and services in 2019. The use of AI generated additional sales with world-first product innovations in these firms of about €16 billion, which corresponds to 18% of total sales of world-first innovations in the German business sector. Firms that developed AI by combining in-house and external resources obtained significantly higher innovation results. The same is true for firms that apply AI in a broad way and have already several years of experience in using AI.

Keywords: Artificial Intelligence; Innovation; CIS data; Germany (search for similar items in EconPapers)
Pages: 38
Date: 2021-04-30
Note: paper number MSI_2105
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Published in FEB Research Report MSI_2105, pages 1-38

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https://lirias.kuleuven.be/retrieve/618929 Published version (application/pdf)

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Working Paper: Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data (2021) Downloads
Working Paper: Artificial intelligence and industrial innovation: Evidence from firm-level data (2021) Downloads
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