Abstract: Gastric cancer exhibits significant molecular heterogeneity, varied treatment res-ponses, and a high risk of recurrence. The traditional management model relying on TNM staging and empirical therapy is no longer sufficient to meet the demands of precision surgical management. With advances in molecular subtyping, liquid biopsy, radiomics, digital pathology, multimodal artificial intelligence, and circulating tumor DNA‑based minimal residual disease monitoring, precision oncology for gastric cancer is evolving from a "target‑drug matching" approach primarily for advanced disease to a comprehensive, dynamic management strategy covering the entire disease course, including early identification, precise staging, treatment selection, surgical decision‑making, postoperative monitoring, and molecular reclassification after recurrence. The authors discuss the clinical translation pathways for precision surgical management of gastric cancer, focusing on early risk recognition, pretreatment stratification, systemic therapy optimization, precision surgery, multimodal efficacy prediction, minimal residual disease monitoring, and dynamic molecular reclassification after recurrence. In the future, the core of precision oncology for gastric cancer will not lie in the mere accumulation of individual technologies, but in integrating molecular, imaging, pathological, and clinical information into actionable clinical workflows. This will enable diagnostic information to be translated into clear therapeutic decisions at key decision points, driving the shift from experience‑driven management to whole‑course, patient‑centered individualized decision-making that maximizes patient benefit.