HEC Research Papers Series,
HEC Paris

Abstract: Industries that rely on data as production inputs may evolve differently from those described in prior models of industry development, which emphasized process investment as a barrier to entry. In today’s nascent artificial intelligence (AI) industry, startups depend heavily on shared data-related processes and infrastructure that are developed and controlled by established information technology (IT) incumbents. This paper uses survey data from 669 AI-producing startups to explore why firms may prefer to scale their innovations with the aid of large IT firms rather than independently. The results show that startups’ access to incumbent-owned processes can reshape the evolution of an industry by lowering entry barriers while leaving barriers to scale intact. Moreover, startups’ resource-sharing relationships and perceived technological fit with large technology suppliers are associated with their scaling strategies, exit intentions, and access to funding. These findings contribute to research on industry evolution, digital entrepreneurship, and complementary assets by identifying a boundary condition for prior models in data-centric industries: when data and data-related processes are central to production, process investment no longer constrains entry, but incumbent-controlled resources shape scaling and exit outcomes.

Keywords: Artificial intelligence; Information technology; Scaling strategies

JEL-codes: L14; L26; O33

43 pages, April 1, 2026

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