Using AI in Life Cycle Assessment Education: Insights from Higher Education and Guidelines for Responsible Integration

As artificial intelligence tools become increasingly present in academic contexts, with the advancement of large language models, their impact on the teaching and learning of life cycle assessment raises both opportunities and concerns. This paper presents the results of a case study conducted across higher education institutions, involving surveys and interviews with students and educators. The objective was to investigate how AI tools are currently used in LCA-related courses, assess their perceived benefits and limitations, and identify recommendations for responsible pedagogical integration. Findings reveal that AI supports accessibility, creativity, and exploration in learning LCA, but also introduces risks such as oversimplification, loss of critical thinking, and the reproduction of inaccurate or non-transparent results. Based on the collected insights, a structured set of recommendations was proposed in the form of a preliminary set of guidelines tailored for both educators and students. These guidelines aim to foster meaningful, ethical, and methodologically robust uses of AI in LCA education. By aligning AI-driven approaches with the rigor of LCA principles, this work contributes to shaping future pedagogical strategies that balance the benefits of AI with the integrity of sustainability education.