在人工智能技术加速演进、科研范式持续升级和产业研发效率需求提升的背景下，全球及中国科学智能行业正迎来新的发展机遇。科学智能（AI for Science）正由传统辅助工具向科学智能体演进，在医药健康、新材料与能源、生物制造及基础科学等领域发挥重要作用，推动科研创新从经验驱动转向数据与模型驱动。
随着产业界对高维复杂问题求解、研发周期缩短、试错成本降低和高质量数据流通提出更高要求，科学智能正逐步嵌入科研与产业研发流程。AI Agent、可信数据空间、高性能计算及新型AI芯片等底层能力持续完善，推动行业由技术验证迈向规模化应用。同时，科学智能在问题定义、实验设计、模型迭代和结果分析等环节的应用不断深化，有望进一步释放产业化价值。
展望未来，全球及中国科学智能行业将在科研范式升级、产业研发需求增长、算力效率提升和数据要素价值释放等多重因素推动下保持稳步发展。
Against the backdrop of rapid advances in artificial intelligence, ongoing shifts in research paradigms, and the growing demand for greater R&D efficiency, the global and Chinese AI for Science industry is embracing new growth opportunities. AI for Science is evolving from a traditional supporting tool into AI-powered scientific agents that play an increasingly important role in healthcare, new materials and energy, biomanufacturing, and basic sciences, while driving scientific innovation from an experience-driven model toward a data- and model-driven approach.
As industries place higher requirements on solving high-dimensional complex problems, shortening R&D cycles, reducing trial-and-error costs, and enabling the trusted flow and utilization of high-quality data, AI for Science is gradually becoming embedded in scientific research and industrial R&D workflows. Foundational capabilities such as AI Agents, trusted data spaces, high-performance computing, and next-generation AI chips continue to improve, supporting the industry's transition from technical validation to scaled application. Meanwhile, AI for Science is deepening its application across problem definition, experimental design, model iteration, and result analysis, further unlocking its industrialization potential.
Looking ahead, the global and China AI for Science industry is expected to maintain sustained growth, supported by multiple drivers including research paradigm upgrades, rising industrial R&D demand, improvements in computing efficiency, and the release of data asset value.
如果您对全球及中国科学智能行业有进一步的研究需求，请联系我们：
沙利文 陆先生
E-mail: gabriel.lu@frostchina.com
