How AI Adoption Can Drive Strategic Innovation with Government Financial Regulators and Public Sector Entities: A Case Study

Public sector institutions (such as regulatory agencies, central banks, and government ministries) must contend with increasing pressure to modernize technology in response to the accelerating pace of technological change and complex market dynamics. If not addressed promptly, public institutions may struggle to perform effectively, maintain oversight, and sustain the trust necessary to fulfill their roles in a rapidly evolving environment. This study, utilizing the dynamic capabilities framework, examines the strategic adoption of Artificial Intelligence (AI) within a financial government regulator, with a focus on its potential to drive institutional innovation and enhance governance structures. The research employs a mixed-methods approach to assess technological maturity, organizational readiness, and the development of robust data governance systems as critical enablers for the integration of AI. The findings highlight how AI adoption can enhance management capabilities, improve operational effectiveness, and support more adaptive, forward-looking institutions. Benchmarking against best practices and existing literature, the paper concludes by offering actionable insights for government organizations, including phased implementation, ongoing learning, and alignment with ethical and transparent standards. The research contributes to understanding the transformative role of AI in the public sector, particularly in governance-focused development contexts.