The building sector strongly influences climate change due to its significant environmental footprint. A fundamental method for assessing and reducing these impacts is Life cycle assessment, while artificial intelligence (AI) offers new ways to improve the accuracy and efficiency of such analyses. Although these two concepts have been studied extensively, their intersection within the framework of sustainable construction is still underexplored. This study intends to map the evolution of this field to provide a global understanding of how AI is redefining LCA studies in the construction sector. The bibliometric study was conducted using Biblioshiny. The data was extracted from Scopus, which included articles published in English between 2014 and 2024. The analysis focused on publications related to AI, LCA and buildings. The results reveal growth in scientific production in these topics with 310 articles appearing in 2024. The Journal of Cleaner Production is leading with 98 publications. China and the USA were the main contributors. Key themes identified through trend topics analysis showed that machine learning and energy efficiency emerged as the most frequently discussed topics. These results show that AI is increasingly being applied to refine the accuracy of LCA studies in the field of construction particularly in environmental impact prediction and prevention. They can also help researchers identify emerging trends, guide practitioners in applying AI to LCA, and support better decisions for sustainable building practices.