Legitimizing AI-Driven Business Model Innovation: An Institutional Perspective on Governance and Compliance
Keywords:
AI-driven business model innovation, institutional theory, organizational legitimacy, responsible AI governance, governance mechanisms, artificial intelligence strategyAbstract
Artificial intelligence is rapidly transforming organizational business models by enabling data-driven value creation, automated decision processes, and intelligent service ecosystems. Despite growing research on AI-driven business model innovation, existing studies primarily emphasize technological capabilities and organizational resources while giving limited attention to the institutional conditions shaping the acceptance and sustainability of AI-enabled innovations. This article addresses that gap by developing a mechanism-based conceptual framework explaining how institutional pressures influence the legitimacy and viability of AI-driven business model innovation. Drawing on institutional theory, responsible AI governance research, and business model innovation literature, the study conceptualizes governance as the organizational mechanism through which firms translate institutional expectations into legitimate AI-enabled value architectures. The framework proposes a sequential process in which institutional pressures shape AI governance practices, governance practices generate cognitive, moral, and pragmatic legitimacy, and legitimacy enables the implementation, stabilization, and diffusion of AI-driven business model innovation outcomes. By integrating previously fragmented research streams, the article contributes a theoretically grounded explanation of how organizations align technological innovation with institutional expectations. The framework offers a foundation for future empirical research examining how governance and legitimacy mechanisms shape the evolution and scalability of AI-enabled business models across institutional contexts.
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