AI-Powered Governments: The Role of Data Analytics and Visualization in Accelerating Digital Transformation

This study addresses the growing challenges faced by governments in utilising the potential of AI and data analytics for digital transformation, focusing on how these technologies can enhance public service delivery, transparency, and citizen engagement. Despite their transformative potential, majority of the governments struggle with the adoption and integration of AI-powered systems due to infrastructural, regulatory, and ethical concerns. The aim of this study is to investigate the role of data analytics and visualization tools in accelerating digital transformation within AI-powered governments. By synthesizing relevant theories such as the Unified Theory of Acceptance and Use of Technology (UTAUT), Institutional Theory, and the Dynamic Capabilities Framework, this conceptual paper provides a strong theoretical foundation for understanding AI adoption in governance. The methodology involves a comprehensive literature review, analysing past studies and theoretical frameworks related to AI, data analytics, and public sector digital transformation. The findings reveal that AI-powered systems can significantly improve governance outcomes by enabling real-time insights and decision-making, while visualization tools enhance transparency and accountability. However, challenges remain, particularly regarding data privacy, digital infrastructure, and equitable access to services. The study’s implications are both theoretical and practical. Theoretically, it contributes to understanding how AI and data analytics are reshaping governance, while practically, it highlights the need for governments to invest in digital infrastructure and develop dynamic capabilities to adapt to technological advancements. Future research should focus on addressing the specific challenges faced by emerging economies and exploring the ethical implications of AI in governance.