<p>Personalized and precision skincare is undergoing a profound transformation from concept to industrial implementation, driven by the deep integration of multi-omics detection technologies and artificial intelligence algorithms. This review systematically organizes the latest advancements and future trends in this field. First, the paper elaborates on a multidimensional skin-typing system based on genomics, proteomics, and metabolomics, revealing the molecular basis of skin phenotypes, dynamic states, and microenvironment characteristics, and providing a scientific rationale for precise interventions that transcend traditional empirical skin classification. Second, it focuses on how artificial intelligence technology empowers the entire chain of personalized skincare: at the data analysis stage, machine learning and deep learning algorithms integrate multi-source heterogeneous data to uncover complex gene-phenotype-environment associations; at the product and service stage, AI-driven intelligent skin condition monitoring, personalized formulation customization, virtual makeup try-on, and outcome prediction achieve a paradigm shift from “one formula fits all” to “one person, one formula”. By analyzing the technology layouts and innovation cases of leading international enterprises, this paper demonstrates the current state of industrialization of the “multi-omics-AI-product” closed-loop system. Finally, the paper discusses the challenges this field faces in data standardization, algorithm interpretability, clinical validation, and regulatory ethics. It outlines future development trends, including integration of skin-organ axes, real-time feedback from wearable devices, and digital twin technology. This review aims to provide a systematic theoretical framework and development pathway reference for academic research, technological innovation, and industrial upgrading in the cosmetics field.</p>