Patent landscape analysis on the use of artificial intelligence in carbon capture and utilization technologies

Rising global carbon dioxide (CO2) levels, driven by industrialization and fossil fuel use, significantly contribute to climate change. CO2 capture technologies are essential to mitigate greenhouse gas emissions, stabilize global temperatures, and meet international climate goals, ensuring a sustainable future through cleaner energy and reduced environmental impact. Carbon capture and utilization (CCU) technologies are now increasingly in demand with rising atmospheric CO2 levels. In this respect, Artificial Intelligence (AI) has made a big difference in achieving more efficient and effective solutions for CCU. Therefore, with the objective of examining the role of AI in CCU technologies, the present research offers an in-depth patent analysis focusing on innovation trends, notable contributors, and emerging technical applications. Results from the analysis of the top industrial sectors, regional patent distribution, and impacts of collaborations between the academia and business sectors are also reported. Patent analysis reveals rapid growth in this domain, with China, South Korea, and India leading advancements through academia–industry collaboration. AI techniques such as machine learning, deep learning, and optimization algorithms are being applied to process optimization, performance forecasting, and emissions prediction across physical, chemical, and biological CCU systems. This research points that AI/ML application has increasingly become an important player in the building of sustainable carbon management strategies. We have also enlisted the key challenges faced while using AI such as limited poor scalability and limited training data. Results from the analysis of the top industrial sectors, regional patent distribution, and impacts of collaborations between academia and business sectors have also been reported.