Barriers to growth in developing Artificial Intelligence

11:00 am September 30, 2020


12:00 pm September 30, 2020

Artificial Intelligence products are expected to increase labor productivity and drive macroeconomic growth. For these gains to be realized, AI startups must be able to raise the funding needed to develop their underlying AI technologies and resulting products. Training data is important to startups developing AI; however, there is no consensus in the literature on aspects of training data that are most important to acquire needed funding. In this paper, we explore if startups that lack proprietary training from suppliers can acquire the funding needed to grow. We develop a framework for characterizing training data as a resource derived from relationships with customers and suppliers, and then use this framework to describe conditions under which such data can lead to competitive advantage. Using unique data from two waves of surveys of AI startups, we find that without additional training data from cloud services providers, above and beyond access to proprietary customer data, AI startups may not be able to acquire the funding needed to grow.

This event is open to faculty, doctoral students, academic researchers, and graduate students.

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