Artificial Intelligence in Environmental Research: Applications, Challenges and Future Directions A Narrative Review

Climate change, biodiversity loss, and pollution are producing environmental data whose volume, velocity, and complexity increasingly surpass the capabilities of conventional analytical methods. Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), is being rapidly adopted to analyse these data; however, evidence regarding its performance remains dispersed across disciplines. This narrative review synthesises peer-reviewed literature identified through structured searches of Scopus, Web of Science, and Google Scholar (1997–2026), selected according to explici