Papers in Innovation Studies,
Lund University, CIRCLE - Centre for Innovation Research

Abstract: This study analyzes the current state of artificial intelligence (AI) technologies for addressing and mitigating climate change in the manufacturing sector and provides an outlook on future developments. The research is grounded in the concept of general-purpose technologies (GPTs), motivated by a still limited understanding of innovation patterns for this application context. To this end, we focus on global patenting activity between 2011 and 2023 (5,919 granted patents classified for “mitigation or adaptation against climate change” in the “production or processing of goods”). We examined time trends, applicant characteristics, and underlying technologies. A topic modeling analysis was performed to identify emerging themes from the unstructured textual data of the patent abstracts. This allowed the identification of six AI application domains. For each of them, we built a network analysis and ran growth trend and forecasting models. Our results show that patenting activities are mostly oriented toward improving the efficiency and reliability of manufacturing processes in five out of six identified domains (“predictive analytics”, “material sorting”, “defect detection”, “advanced robotics”, and “scheduling”). Instead, AI within the “resource optimization” domain relates to energy management, showing an interplay with other climate-related technologies. Our results also highlight interdependent innovations peculiar to each domain around core AI technologies. Forecasts show that the more specific technologies are within domains, the longer it will take for them to mature. From a practical standpoint, the study sheds light on the role of AI within the broader cleantech innovation landscape and urges policymakers to consider synergies. Managers can find information to define technology portfolios and alliances considering technological co-evolution.

Keywords: artificial intelligence; AI; climate change; sustainability; patent analysis; technology foresight

JEL-codes: O14; O31; O32; O33; O34

Language: English

46 pages, October 21, 2024

Full text files

202412_podrecca.pdf  Full text

Download statistics

• Lund University, CIRCLE - Centre for Innovation Research
• Home page for this series

Questions (including download problems) about the papers in this series should be directed to Torben Schubert ()
Report other problems with accessing this service to Sune Karlsson ().

RePEc:hhs:lucirc:2024_012This page generated on 2024-10-21 15:31:24.