Titanium alloys are strategic materials in key fields such as aerospace and marine equipment. However, theirtraditional research and development (R&D) model, which relies heavily on trial and error, is inefficient. The rise ofartificial intelligence (AI) is driving a paradigm shift in this field toward a "data and knowledge dual-driven" approach. Thisreview systematically elaborates on how the integration of knowledge and data drives full-chain innovation in advancedtitanium alloys, covering data construction, property prediction, and intelligent manufacturing. First, it analyses theparadigm shift brought by AI and the global strategic context. Second, the application of AI in constructing a titanium alloydomain knowledge system, the realization of machine learning in the intelligent design of titanium alloy compositions, thesupporting role of machine vision in intelligent welding and quality control, and the achievement of autonomous R&D byAI agents integrating knowledge, data, and execution capabilities are discussed. Finally, the future path of autonomousR&D for titanium alloys is anticipated. Despite challenges such as data quality, model interpretability, and industrialintegration, AI is expected to lead titanium alloy R&D into a new stage of autonomy through promoting data-knowledge fusion guidance and autonomous laboratory transformation, providing core momentum for the independent and controllabledevelopment of national high-end materials.