Recent advances underscore the potential of integrating multi-omics, such as genomics, transcriptomics, proteomics, and metabolomics, and artificial intelligence to overcome limitations regarding early diagnosis and treatment of Parkinson's disease. Developing a comprehensive view of the complex molecular landscape of Parkinson's disease through artificial intelligence algorithms would enable the processing of extensive multi-omics datasets. Applying these integrative technologies to Parkinson's disease research would improve early diagnosis, support personalized therapeutic strategies, and drug discovery. This review explores the transformative potential of integrating multi-omics and artificial intelligence in Parkinson's disease, outlining a framework to advance diagnosis, treatment, and drug development in neurodegenerative diseases.