The rapid integration of artificial intelligence (AI) into enterprise systems has transformed the landscape of data governance, moving it beyond a narrow focus on regulatory compliance toward a multidimensional tool for organizational growth. Traditional models of governance often emphasize adherence to legal and industry standards; however, in an era where data is both a strategic asset and a potential liability, AI-powered governance introduces a paradigm shift. By leveraging machine learning, natural language processing, and predictive analytics, enterprises can establish governance frameworks that not only ensure compliance but also enhance decision-making precision, optimize resource allocation, and anticipate potential risks. This paper explores how AI-enabled data governance transcends the reactive nature of compliance-driven models by enabling proactive risk detection, adaptive policy enforcement, and real-time monitoring of data integrity. Moreover, it highlights the critical role of AI in fostering trust, transparency, and accountability across organizational data ecosystems. The capacity to process vast and complex datasets allows enterprises to identify hidden correlations, uncover emerging market trends, and generate actionable insights that improve strategic agility. Beyond risk mitigation, such capabilities position data governance as a driver of sustainable growth by aligning operational efficiency with ethical responsibility and long-term value creation. The discussion underscores the necessity for enterprises to embrace AI not solely as a technological upgrade but as a governance philosophy that balances compliance, innovation, and sustainability. In doing so, organizations can transform data governance from a burdensome requirement into a competitive differentiator. Ultimately, the paper argues that AI-powered governance represents the future of enterprise resilience, where compliance is merely the foundation for more dynamic and value-driven outcomes.
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Kenechukwu O. Agbodike
South Asian Journal of Social Studies and Economics
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Kenechukwu O. Agbodike (Sat,) studied this question.
www.synapsesocial.com/papers/68d46ac231b076d99fa681d5 — DOI: https://doi.org/10.9734/sajsse/2025/v22i91161