Artificial intelligence (AI) has emerged as a powerful tool for addressing environmental challenges through advanced data analysis and predictive modelling. This study examines the global research landscape of AI applications in environmental science using a bibliometric approach. A total of 11,199 records were retrieved from the Scopus database, of which 9,504 English-language research articles published between 2014 and 2023 met the inclusion criteria and were analysed using Bibliometrix (RStudio), VOSviewer, and Microsoft Excel. The study analysed publication trends, leading authors, journals, countries, institutions, collaboration networks, keywords, and citation patterns. The findings reveal a rapid growth in research output, particularly after 2018, with China leading global publications. Sustainability, Science of the Total Environment, and Journal of Cleaner Production were the most productive journals, while Machine Learning was the most frequently occurring author keyword. The study provides a comprehensive overview of AI applications in environmental science by identifying major research trends, collaboration patterns, and emerging directions for future research.