The most attributable risk factor for the pathogenesis of neurodegenerative diseases is aging, which is also one of the greatest challenges in a super-aging society. With the development of biological and genetic research in recent years, our understanding of the molecular biology of neurodegenerative diseases has significantly advanced; however, for neurodegenerative diseases, especially for sporadic cases without an identifiable family history, which account for the majority of affected patients, effective models to investigate the pathogenesis have been needed. Patient-specific induced pluripotent stem cells (iPSC) generated by using reprogramming technology have the identical genetic background as that of the patients’ and can be differentiated into any cell types to construct a disease cell model. Analysis of the omics data, including cell-phenotype data, may lead to elucidation of the disease pathophysiology and identification of potential therapeutic targets. In addition, because these data are vast and complex, analyses using artificial intelligence (AI) are being pursued. In this review, we describe research using iPSC data and AI in the field of neurodegenerative diseases, including our own research to provide examples.