The role of data for AI startup growth

James Bessen, Stephen Michael Impink, Lydia Reichensperger and Robert Seamans

Research Policy, 2022, vol. 51, issue 5

Abstract: Artificial intelligence (AI)-enabled products are expected to drive economic growth. Training data are important for firms developing AI-enabled products; without training data, firms cannot develop or refine their algorithms. This is particularly the case for AI startups developing new algorithms and products. However, there is no consensus in the literature on which aspects of training data are most important. Using unique survey data of AI startups, we find a positive correlation between having proprietary training data and obtaining future venture capital funding. Moreover, this correlation is greater for startups in markets where data is a major advantage and for startups using more sophisticated algorithms, such as neural networks and ensemble learning.

Keywords: Artificial intelligence; Competition; Data; Algorithms; Venture capital (search for similar items in EconPapers)
JEL-codes: J21 L10 L26 O33 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:respol:v:51:y:2022:i:5:s0048733322000415

DOI: 10.1016/j.respol.2022.104513

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