Intellectual Property Management in the Age of Artificial Intelligence: Exploring the Value and Organizational Implications of AI in Patent Management

Abstract

Artificial intelligence (AI) is rapidly changing how organizations handle knowledgeintensive and analytical tasks. Within patent management, increasing amounts of patent data, growing technological complexity, and rising competitive pressure have resulted in a growing interest in how AI can support intellectual property (IP) work. At the same time, the integration of AI into patent management raises new organizational challenges. While previous research has demonstrated promising technical applications of AI in patent-related activities, there is still limited understanding of how AI is currently used, perceived, and implemented in practice within corporate patent management functions. Building on a qualitative research approach, this study is based on 32 interviews with professionals from corporate IP departments, IP firms, and AI tool providers to examine current applications and the potential of AI in patent management. The findings illustrated that AI is perceived to hold significant potential across several patent management activities, particularly in search optimization, drafting support, portfolio analysis, and analytical work involving large amounts of data. However, despite strong interest and optimism surrounding AI, implementation remains relatively limited. Several organizational barriers were identified, including confidentiality concerns, lack of trust in AI, fear of losing professional judgment and expertise, psychological inertia, unrealistic expectations regarding AI performance and introduction of bottlenecks. The study concludes that the challenge of integrating AI into patent management is not primarily about whether AI has potential, but about organizations’ ability to adapt in ways that allow this potential to be realized without compromising the requirements and professional standards under which patent management operates. The study thereby contributes to the emerging literature on AI in patent management by providing empirical insights into how organizations currently approach AI adoption and the organizational conditions shaping implementation in practice.