Artificial intelligence enabling chemical analysis: applications, challenges, and future prospects

With the rapid development of artificial intelligence (AI) technology, the field of chemical analysis is gradually integrated into AI technology, especially driven by deep learning and machine learning, the processing and analysis efficiency of chemical data has been significantly improved. Traditional chemical analysis methods rely on complex experimental operations and face problems of precision and human interference, and AI technology, especially the application of neural networks, has successfully solved these limitations. In this study, we analyzed the application trend of AI in the field of chemical analysis through bibliometric methods, selected relevant literature from 2015 to 2025, and analyzed the application progress of AI in chromatography and spectroscopy. It is found that since 2020, the application of AI in chemical analysis has ushered in rapid growth, especially in molecular excitation spectrum prediction and spectrum analysis. This paper also analyzes the main research countries, core authors and their collaborators, and reveals the frontier dynamics and future trends of the combination of AI and chemical analysis.