作为数字经济时代的重要战略资源，企业对数据要素的关注程度折射出其对新兴技术发展的战略重视，并在技术演进过程中发挥引导作用。本文以中国上市公司39 681个公司-年度面板数据为样本，采用固定效应模型、中介及调节效应分析方法，系统考察企业通过数据要素关注促进人工智能技术创新的内部路径，揭示外部环境条件对上述过程的作用边界。研究发现：（1）企业的数据要素关注对人工智能技术创新具有显著正向影响。（2）在内部机制上，数据要素关注主要通过激活非沉淀性冗余资源发挥作用，沉淀性冗余资源作用不明显。（3）在外部环境上，市场竞争强度与政府公共数据开放程度均强化了数据要素关注的创新促进效应。（4）在资本、管理与技术要素水平较高企业中，数据要素关注对人工智能技术创新的正向作用更为显著。研究拓展了数据要素价值实现的作用边界，对企业在不同资源结构与环境条件下的人工智能技术创新提供参考。

   As a key strategic resource in the digital economy era, the extent to which firms focus on data elements reflects their strategic emphasis on emerging technological development and plays a guiding role in shaping technology evolution. Using a panel dataset of 39,681 firm-year observations from Chinese listed companies, this study employed the fixed effects models as well as the mediation and moderation analyses to systematically examine the internal pathways through which data element focus promotes artificial intelligence (AI) technological innovation, and explored how external environmental conditions shape this process. The results revealed that: (1) enterprise-level data element focus has a significantly positive impact on AI technological innovation; (2) internally, this effect is primarily driven by the activation of non-precipitated slack resources, while the role of precipitated slack resources is less pronounced; (3) externally, both market competition intensity and the degree of government public data openness enhance the innovation-promoting effect of data focus; and (4) the positive effect of data elements focus is more significant in firms with higher levels of capital, managerial, and technological resources. This study has expanded the boundary of the mechanism of data element values and it will offer practical insights into AI innovation under varying resource structures and environmental conditions.