Abstract: Although the comprehensive, multi-level, and wide-ranging integration of artificial intelligence (AI) with pharmaceutical science has greatly advanced the development of the discipline, the majority of pharmaceutical professionals still have limited knowledge about the applications of AI in pharmacy. Particularly in recent years, the rapid development of generative AI technologies represented by large language models has introduced new paradigms for pharmaceutical knowledge acquisition, drug information mining, and intelligent education. Simultaneously, interdisciplinary talents in "AI + Pharmacy" play a crucial and irreplaceable role in the new drug development process.Faced with this reality, pharmaceutical educators should uphold the core philosophy of "AI empowerment, education first," actively disseminate cutting-edge AI concepts, and vigorously develop interdisciplinary advantages to address challenges in traditional pharmaceutical education. The core goal of cultivating innovative talents in "AI + Pharmacy" is to to nurture interdisciplinary professionals with solid pharmaceutical expertise, strong computational and data-driven thinking, and the ability to comprehensively apply AI technologies to solve complex problems in real-world research and application scenarios. To this end, his paper proposes a three-pillar "AI + Pharmacy" innovative talent cultivation model centered on "teaching restructuring, research-driven feedback, and faculty support," aiming to systematically promote comprehensive reforms in pharmaceutical education—from curriculum systems and teaching practices to faculty development. This approach seeks to gradually establish and continuously optimize a new paradigm for interdisciplinary pharmaceutical talent cultivation that aligns with contemporary demands, thereby providing sustainable talent support and innovative momentum for the overall advancement of pharmaceutical science and new drug development.