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The role of data for AI startup growth

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

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.

Suggested Citation

  • Bessen, James & Impink, Stephen Michael & Reichensperger, Lydia & Seamans, Robert, 2022. "The role of data for AI startup growth," Research Policy, Elsevier, vol. 51(5).
    • Handle: RePEc:eee:respol:v:51:y:2022:i:5:s0048733322000415
    DOI: 10.1016/j.respol.2022.104513
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    Cited by:

    1. Alessandra Colombelli & Elettra D’Amico & Emilio Paolucci, 2023. "When computer science is not enough: universities knowledge specializations behind artificial intelligence startups in Italy," The Journal of Technology Transfer, Springer, vol. 48(5), pages 1599-1627, October.
    2. Kristina McElheran & J. Frank Li & Erik Brynjolfsson & Zachary Kroff & Emin Dinlersoz & Lucia Foster & Nikolas Zolas, 2024. "AI adoption in America: Who, what, and where," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 375-415, March.
    3. Igna, Ioana & Venturini, Francesco, 2023. "The determinants of AI innovation across European firms," Research Policy, Elsevier, vol. 52(2).
    4. Fossen, Frank M. & McLemore, Trevor & Sorgner, Alina, 2024. "Artificial Intelligence and Entrepreneurship," IZA Discussion Papers 17055, Institute of Labor Economics (IZA).
    5. ZHU Chen & MOTOHASHI Kazuyuki, 2024. "The Fundraising of AI Startups: Evidence from web data," Discussion papers 24021, Research Institute of Economy, Trade and Industry (RIETI).
    6. Christian Peukert & Margaritha Windisch, 2023. "The Economics of Copyright in the Digital Age," CESifo Working Paper Series 10687, CESifo.
    7. Emin Dinlersoz & Can Dogan & Nikolas Zolas, 2024. "Starting Up AI," Working Papers 24-09, Center for Economic Studies, U.S. Census Bureau.
    8. Flavio Calvino & Luca Fontanelli, 2023. "Artificial intelligence, complementary assets and productivity: evidence from French firms," LEM Papers Series 2023/35, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Nam, Jinyoung & Kim, Junghwan & Jung, Yoonhyuk, 2023. "Understandings of the AI business ecosystem in South Korea: AI startups' perspective," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 278005, International Telecommunications Society (ITS).

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    More about this item

    Keywords

    Artificial intelligence; Competition; Data; Algorithms; Venture capital;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L26 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Entrepreneurship

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