Publications
Publications
- 2024
- HBS Working Paper Series
The Value of AI Innovations
By: Wilbur Xinyuan Chen, Terrence Tianshuo Shi and Suraj Srinivasan
Abstract
We study the value of AI innovations as it diffuses across general and application sectors, using the United States Patent and Trademark Office’s (USPTO) AI patent dataset. Investors value these innovations more than others, as AI patents exhibit a 9% value premium, and 26% higher forward citations compared to non-AI patents from the same patent classification and industry group. This value premium also increases over time, particularly in firms and industries where occupational tasks are more suited for AI. Due to the specialization in AI innovation across general and application sectors, we further find that policies that facilitate knowledge spillovers are key to increasing the value premium in these innovations. Specifically, we show that the value premium of AI innovations in application sectors, increases by 5% after the American Inventors Protection Act (AIPA) patent publication rule, and by 2% after the open sourcing of TensorFlow. Overall, our analysis illustrates the value of AI innovations to investors and highlights the importance of policies that foster knowledge spillovers for AI innovations.
Keywords
AI and Machine Learning; Valuation; Technological Innovation; Open Source Distribution; Patents; Policy; Knowledge Sharing; Technology Industry
Citation
Chen, Wilbur Xinyuan, Terrence Tianshuo Shi, and Suraj Srinivasan. "The Value of AI Innovations." Harvard Business School Working Paper, No. 24-069, May 2024.