AI technologies and employment: micro evidence from the supply side

ABSTRACT

In this work we investigate the possible job-creation impact of artificial intelligence (AI) technologies, focusing on the supply side, where the development of these technologies can be conceived as product innovations in upstream sectors. The empirical analysis is based on a worldwide longitudinal sample (obtained by merging the EPO PATSTAT and BvD-ORBIS databases) of more than 3,500 front-runner companies that patented AI-related inventions over the period 2000–2016. Based on system GMM estimates of dynamic panel models, our results show a positive and significant impact of AI patent families on employment, supporting the labour-friendly nature of AI product innovation.

KEYWORDS:

• Innovation
• artificial intelligence
• patents
• employment

JEL CLASSIFICATION:

• O33
• O31
• O30

Acknowledgments

We are very grateful to two anonymous referees for extensive comments that helped to improve the article considerably. We also thank the participants of the Workshop ‘The Economics and Management of AI Technologies’ (Bureau d’Economie Théorique et Appliquée, Université de Strasbourg) and of the GLO Virtual Seminar. Giacomo Damioli acknowledges the financial support from the European Union’s Horizon 2020 Framework Programme under the ‘Innova Measure IV’ project (Grant agreement no. 857088). Marco Vivarelli acknowledges support by the Italian Ministero dell’Istruzione, dell’Università e della Ricerca (PRIN-2017, project 201799ZJSN: ’Technological change, industry evolution and employment dynamics’; principal investigator: Marco Vivarelli).

Disclaimer statement

The scientific output expressed here does not imply a policy position of the European Commission or the International Telecommunication Union and their Member States. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

¹ Think, for instance, of the electronic industry where robots are produced, or scientific services where AI algorithms are conceived.

² An analogous approach to selecting AI patents was adopted by Cockburn, Henderson, and Stern (2019).

³ Results are available upon request.

Additional information

Funding

This work was supported by the Horizon 2020 Framework Programme [857088]; Ministero dell’Istruzione, dell’Università e della Ricerca [201799ZJSN].