The Fundraising of AI Startups: Evidence from web data

         
Author Name ZHU Chen (University of Tokyo) / MOTOHASHI Kazuyuki (Faculty Fellow, RIETI)
Creation Date/NO. February 2024 24-E-021
Research Project Research on Digital Innovation Models
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Abstract

Startups have emerged as pivotal innovators in the commercialization of AI technology. Nonetheless, these nascent enterprises often require substantial capital infusion to realize the economic returns from their innovations. This study examines the role of prototypes in facilitating their fundraising process. We utilized historical web content to identify the presence of prototypes and employed web traffic data to monitor their customer growth. Our findings indicate that prototyping positively affects the potential customer attraction process, signaling the feasibility and profitability of their business hypotheses to potential investors. In addition, as a technologically intensive industry, most AI startups begin with a technology-centric approach. While a technology-led starting point underscores competitiveness, it also inherently introduces uncertainty. We offer quantitative evidence demonstrating how prototyping acts as a moderating factor, reducing the impact of such uncertainty by expediting investor decision-making.