Abstract: Gastric cancer, which has high incidence and mortality rates worldwide, faces numerous challenges in its diagnosis and treatment. In recent years, the combination of multi-omics technology and artificial intelligence (AI) algorithms has brought new hope for the diagnosis and treatment of this malignant disease. Multi-omics technology encompasses the fields of genomics, transcriptomics, proteomics, metabolomics, and radiomics, and can comprehensively reveal the biological characteristics of gastric cancer. AI algorithms, particularly machine-and deep-learning methods, possess powerful data integration, feature extraction, and pattern recognition capabilities, enabling the extraction of the most valuable information from vast and complex multi-omics data. Such technology can aid in the early screening, precise diagnosis, personalized treatment, and prognostic assessment of gastric cancer. In this article, research progress on AI-based multi-omics technology for the diagnosis and treatment of gastric canceris reviewed, and current applications of such technology at different diagnostic and therapeutic stages, the challenges faced, and future development directions are discussed, with the aim of providing new ideas and methods for the diagnosis and treatment of this malignant disease.