Artificial Intelligence Capability: A Systematic Review of Research Framework and Application Scenarios
DOI:
https://doi.org/10.54097/45x3r360Keywords:
AI Capability, Resource-Based View, Dynamic Capabilities Theory, Organizational Performance, Innovation ManagementAbstract
Against the backdrop of the deepening development of the digital economy and the ongoing integration of the digital and physical worlds, artificial intelligence has evolved from a single-function technical tool into a core strategic capability that supports organizations in building long-term competitive advantages. As a core construct that explains differences in the value transformation of AI technology, AI capability has become a hot topic of research in the fields of strategic management and information systems. However, existing research is scattered across diverse disciplinary perspectives and application scenarios, and has yet to form a unified research framework or theoretical system. Based on 33 core publications in the field of AI capabilities, this paper conducts a systematic review following the logical framework of “conceptual evolution-theoretical foundations-application scenarios-research outlook.” The study traces the evolutionary path of AI capabilities, from their origins in IT capability research to the development of a general three-dimensional construct, and further expansion into specialized technological forms and specific application scenarios; it synthesizes a theoretical framework centered on the resource-based view and dynamic capabilities theory, complemented by multiple theoretical perspectives; and summarizes the application progress and heterogeneity in value realization of AI capabilities across eight major scenarios, including green innovation, supply chain management, public governance, and business model innovation; Finally, it identifies limitations in existing research regarding research design, theoretical perspectives, scenario coverage, and risk governance, and proposes future research directions. This paper integrates and constructs a comprehensive research framework for AI capabilities, clarifies the field’s consensus and research gaps, and not only enriches the theoretical research landscape in the field of AI capabilities but also provides practical guidance for organizations of various types to systematically build AI capabilities and achieve the transformation of technological value.
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