Artificial Intelligence and Entrepreneurship
Frank Fossen,
Trevor McLemore () and
Alina Sorgner
Additional contact information
Trevor McLemore: University of Nevada, Reno
No 17055, IZA Discussion Papers from Institute of Labor Economics (IZA)
Abstract:
This survey reviews emerging but fast-growing literature on impacts of artificial intelligence (AI) on entrepreneurship, providing a resource for researchers in entrepreneurship and neighboring disciplines. We begin with a review of definitions of AI and show that ambiguity and broadness of definitions adopted in empirical studies may result in obscured evidence on impacts of AI on en-trepreneurship. Against this background, we present and discuss existing theory and evidence on how AI technologies affect entrepreneurial opportunities and decision-making under uncertainty, the adoption of AI technologies by startups, entry barriers, and the performance of entrepreneurial businesses. We add an original empirical analysis of survey data from the German Socio-economic Panel revealing that entrepreneurs, particularly those with employees, are aware of and use AI technologies significantly more frequently than paid employees. Next, we discuss how AI may affect entrepreneurship indirectly through impacting local and sectoral labor markets. The reviewed evidence suggests that AI technologies that are designed to automate jobs are likely to result in a higher level of necessity entrepreneurship in a region, whereas AI technologies that transform jobs without necessarily displacing human workers increase the level of opportunity entrepreneurship. More generally, AI impacts regional entrepreneurship ecosystems (EE) in multiple ways by altering the importance of existing EE elements and processes, creating new ones, and potentially reducing the role of geography for entrepreneurship. Lastly, we address the question of how regulation of AI may affect the entrepreneurship landscape by focusing on the case of the European Union that has pioneered data protection and AI legislation. We conclude our survey by discussing implications for entrepreneurship research and policy.
Keywords: innovation; opportunity; digital entrepreneurship; AI startups; entrepreneurship; machine learning; artificial intelligence; entrepreneurship ecosystem; digital entrepreneurship ecosystem; AI regulation (search for similar items in EconPapers)
JEL-codes: J24 L26 O30 (search for similar items in EconPapers)
Pages: 123 pages
Date: 2024-06
New Economics Papers: this item is included in nep-ain, nep-big, nep-cse, nep-ent, nep-eur, nep-ino, nep-lma, nep-sbm and nep-tid
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://docs.iza.org/dp17055.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:iza:izadps:dp17055
Ordering information: This working paper can be ordered from
IZA, Margard Ody, P.O. Box 7240, D-53072 Bonn, Germany
Access Statistics for this paper
More papers in IZA Discussion Papers from Institute of Labor Economics (IZA) IZA, P.O. Box 7240, D-53072 Bonn, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Holger Hinte ().