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.
Original language | English (US) |
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Article number | 104513 |
Journal | Research Policy |
Volume | 51 |
Issue number | 5 |
DOIs | |
State | Published - Jun 2022 |
Keywords
- Algorithms
- Artificial intelligence
- Competition
- Data
- Venture capital
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research
- Management of Technology and Innovation