Democratizing environmental impact assessment: An AI-augmented framework for sustainable building design

The construction sector contributes significantly to greenhouse gas emissions, yet designers often lack tools that make life cycle assessment (LCA) accessible during routine decision-making. This study presents an AI-augmented framework that embeds automated, interpretable LCA within the building information modeling environment. The system links material quantities extracted from Revit with programmatic inventory modeling and an endpoint module that allows users to adjust time horizons to reflect different cultural risk perspectives. A conversational interface enables designers and stakeholders to explore trade-offs, visualize environmental impacts, and receive plain-language interpretations of results. Using a residential building model, the framework reproduced expert SimaPro outputs with less than 2.1% variation across indicators. By integrating environmental intelligence directly into early-stage design workflows, the approach supports more informed material choices, streamlines green permitting, and provides a foundation for policy tools that encourage lower-carbon construction.