人工智能（Artificial Intelligence,以下简称AI）技术正有力推动公共管理服务的智能化、流程标准化以及系统数智化进程。在医药集采领域,部分地方已在资质审核、药品挂网、价格治理、智能问答、价格监测乃至全流程监管等环节进行了初步探索,AI技术已彰显出提高服务质量、提升流程效率、增强透明度、优化成本以及辅助监测等重要价值,但也面临模型算力需求、行业数据汇集、数据安全与确权以及模型地区适用性等四个方面的挑战。可从前瞻研究、国家引领、创新驱动、持续迭代、共建共享等维度,推动AI技术在医药集中采购领域的应用,助力构建更公平、高效、可持续的医药集采体系。

Artificial intelligence (AI) technology is powerfully promoting the intelligence of public management services, standardization of processes, and digitalization of systems. In the field of centralized drug procurement, some regions have conducted preliminary explorations in areas such as qualification review, drug listing, price regulation, intelligent Q&A, price monitoring, and even full-process supervision. AI technology has demonstrated significant value in improving service quality, enhancing process efficiency, increasing transparency, optimizing costs, and assisting in monitoring. However, it also faces challenges in four areas: model computing power requirements, industry data aggregation, data security and ownership, and regional applicability of models. AI applications in centralized drug procurement can be promoted from perspectives such as prospective study, national guidance, innovation-driven development, continuous iteration, and shared collaboration, helping to build a fairer, more efficient, and more sustainable drug procurement system.