Journal of Management Information Systems

Volume 41 Number 2 2024 pp. 422-452

Abnormal Returns to Artificial Intelligence Patent Infringement Litigations

Teli, John Sudeep, Rai, Arun, and Lin, Yu-Kai

ABSTRACT:

Artificial intelligence (AI) has become an important driver of economic growth and innovation. With rapid advances in AI, firms have a strategic opportunity to re-envision the cognitive reapportionment of tasks between humans, AI, and non-AI technologies. In doing so, firms can transform and dramatically elevate value creation through their business models, processes, and market offerings. We focus on a key risk, patent infringement litigation (PIL), that can adversely impact a firm’s value creation with AI. We posit and demonstrate that firms facing AI-PILs would have more negative short term abnormal returns compared to firms facing non-AI PILs. We further suggest that the abnormal returns are moderated by the types of plaintiffs and AI patents in which the abnormal returns are more negative when the plaintiffs are non-practicing entities (versus practicing entities) and when the AI patents at suit concern expertise-driven (versus data-driven) AI. Exploring the moderators jointly, we find evidence that for data-driven AI patents, the negative abnormal returns are stronger when the plaintiffs are practicing entities, but for expertise-driven AI patents, the negative abnormal returns are stronger when the plaintiffs are non-practicing entities.

Key words and phrases: AI, artificial intelligence, patent infringement, intellectual property, patent litigation, AI patents, event study