Artificial Intelligence (AI) tools, applications, and capabilities have received tremendous attention from industry practitioners, scholars, and policymakers. Despite the substantial progress of the literature on AI, there is a considerable scarcity of research investigating the effects of AI capability, considering the importance of a data-driven culture and whether a data-driven culture truly mediates the relationship between AI capability and firm performance from a sustainable development perspective. Anchored by the resource-based theory (RBT), we developed a high-order model of AI capability and its resources (tangible, intangible, and human). We used a two-stage approach, with PLS-SEM in the first and fsQCA in the second. The findings from the first step suggest that AI capability directly impacts firm performance and that data-driven culture mediates the relationship between AI capability and firm performance. The results from the second step indicated that different configurations of AI resources could be considered for firms to achieve high performance but that AI infrastructure is a crucial resource. Our study advances the literature on AI capability and sustainable development goals. Similarly, it contributes to moving the RBT theory forward by suggesting that AI capability is a paramount variable that substantially influences firm performance. Simultaneously, it is harmoniously connected with SDG 9 (industry, innovation, and infrastructure) and SDG 12 (responsible consumption and production).

人工智能（AI）工具、应用和能力受到了行业从业者、学者和政策制定者的极大关注。尽管有关人工智能的文献取得了实质性进展，但考虑到数据驱动文化的重要性以及数据驱动文化是否真正调解人工智能能力与公司绩效之间的关系，调查人工智能能力影响的研究相当匮乏从可持续发展的角度来看。以基于资源的理论（RBT）为基础，我们开发了人工智能能力及其资源（有形、无形和人力）的高阶模型。我们使用了两阶段方法，第一阶段是 PLS-SEM，第二阶段是 fsQCA。第一步的研究结果表明，人工智能能力直接影响企业绩效，而数据驱动文化调节人工智能能力与企业绩效之间的关系。第二步的结果表明，企业可以考虑不同的人工智能资源配置来实现高性能，但人工智能基础设施是至关重要的资源。我们的研究推进了有关人工智能能力和可持续发展目标的文献。同样，它表明人工智能能力是对公司绩效产生重大影响的重要变量，从而有助于推动 RBT 理论的发展。同时，它与SDG 9（工业、创新和基础设施）和SDG 12（负责任的消费和生产）和谐相连。