Automating Life Cycle Assessments through Artificial Intelligence Agents and Integrated Assessment Models

Life cycle assessments (LCA) are a critical decision support tool for environmentally sustainable decision-making, but barriers such as time and resource intensity inhibit widespread application of LCA. To overcome these challenges, LCAs have been partially automated with integrated assessment models (IAM) and artificial intelligence (AI) agents, but existing literature reviews do not describe the potential for automation. We find that AI agents and IAMs offer tantalizing methods to automate all four stages of LCA with many avenues for future research, but adoption in the LCA community outside of the premise tool is minimal, despite the reliable results reported by the authors of several studies. Automated LCA can improve time and resource efficiency across all four stages of LCA, but there is insufficient research to rigorously assess the quality of automated LCA. To overcome the perceived untrustworthiness of automated LCA tools, the LCA community should democratically develop norms for use.