Artificial Intelligence (AI) holds the promise of revolutionizing the Life Cycle Assessment (LCA) space in multiple ways. One of the most immediate impacts could be the automation of data collection and analysis, much like the work done at 2050 Materials today.
Right now, gathering the plethora of information needed for a comprehensive LCA in the built environment is time-consuming and often error-prone. AI algorithms can scrape, sort, and analyze massive sets of data in real-time, thereby not only speeding up the LCA process but also improving its accuracy. With machine learning, these algorithms could become increasingly sophisticated over time, learning from each LCA to make the next one more precise.
Beyond automation, AI could usher in the era of predictive LCAs. Instead of merely analyzing the sustainability of building materials and construction methods based on existing data, AI could forecast future impacts based on a wide array of variables like projected changes in energy costs, availability of raw materials, and even climate change scenarios. This would offer architects, engineers, and policymakers a more dynamic tool for sustainable decision-making. By enabling what could be termed “future-proof sustainability,” AI has the potential to make LCAs an even more integral part of the AEC industry’s toolkit for combating climate change and resource depletion.