科技成果转化成效，不仅依赖研发投入，更取决于识别、评估、定价、融资等环节的协同水平。当前，人工智能正由辅助工具升级为科技服务业的关键基础设施，通过降低信息成本、精准画像成果、优化供需匹配，推动成果从“可展示”迈向“可交易、可融资、可产业化”。其赋能关键在于构建“数据底座+场景验证+专业服务+制度治理”协同体系，而非替代专业人员。为此，需加快制定成果数据标准，开放概念验证与中试场景，完善AI辅助评价与责任机制，培育复合型服务主体，切实提升转化效益与产业贡献。

The effectiveness of turning technological achievements into real-world results doesn’t just rely on R&D investment; it also depends on how well different steps like identification, evaluation, pricing, and financing work together. Right now, AI is upgrading from a helpful tool to a key infrastructure in the tech service industry. By lowering information costs, accurately profiling results, and optimizing supply-demand matching, it’s helping achievements move from being “just presentable” to “tradeable, fundable, and industrializable.” Its real power lies in building a collaborative system of “data foundation, scenario validation, professional services, and governance,” rather than replacing experts. To make this happen, we need to speed up setting standards for achievement data, open up proof of-concept and pilot scenarios, improve AI-assisted evaluation and accountability mechanisms, and nurture multi skilled service providers to truly boost the impact and industrial contribution of these achievements.