Pancreatic cancer, a highly malignant tumor of digestive system, is characterized by challenges in early detection and limited therapeutic efficacy. Currently, artificial intelligence (AI) technologies—such as machine learning, deep learning, and natural language processing (NLP)—are providing innovative strategies to address key bottlenecks in the diagnosis and treatment of pancreatic cancer. Based on databases such as PubMed, Web of Science, and CNKI, this study conducted literature retrieval and screening, initially obtaining 128 articles related to AI-powered pancreatic cancer diagnosis and treatment. After in-depth review, 38 journal papers and research reports were ultimately included, covering key aspects such as AI-based disease risk prediction models, intelligent screening of medical imaging and pathological assistance diagnosis, personalized treatment strategy recommendations, efficacy monitoring, and recurrence prediction. The study systematically reviews the integration and application of AI technologies throughout the entire process of pancreatic cancer diagnosis and treatment. By conducting a meta-analysis of current practices and evidence regardin AI in pancreatic cancer diagnosis and treatment, this paper aims to provide academic references for promoting the effective translation of AI technologies into clinical practice for pancreatic cancer.