A Unified Theoretical Model of AI-Driven Governance for Adaptive Digital Transformation - Bambang Saras Yulistiawan (Institute of Computer Science (IOCS), 2024)
The rapid advancement of artificial intelligence (AI), Internet of Things (IoT), cloud computing, big data analytics, and autonomous systems has accelerated digital transformation across various sectors, creating increasingly interconnected and intelligent digital ecosystems. However, the widespread adoption of AI technologies also generates complex governance challenges related to transparency, accountability, cybersecurity, data privacy, interoperability, and ethical compliance. Existing AI governance frameworks remain fragmented, sector-specific, and insufficiently integrated to address the adaptive and dynamic nature of modern digital environments. Therefore, this study aims to develop a unified theoretical model of AI-driven governance for adaptive digital transformation. This research employs a qualitative conceptual approach using a systematic and integrative literature review methodology. Relevant literature, governance frameworks, policy documents, and digital transformation studies were analyzed through thematic analysis and conceptual synthesis to identify the core dimensions of effective AI governance. The study integrates governance principles, ethical considerations, organizational structures, and technological mechanisms into a comprehensive multi-layered framework. The findings of the study propose a unified AI governance model consisting of interconnected dimensions, including transparency and explainability, accountability mechanisms, data governance and privacy, cybersecurity resilience, interoperability across systems, and adaptive feedback mechanisms. Compared to existing governance models, the proposed framework provides a more integrated and adaptive approach by bridging fragmented governance perspectives into a single coherent structure. In conclusion, the proposed unified AI governance model contributes theoretically to governance and AI ethics literature while providing practical guidance for governments, organizations, and technology developers in implementing responsible, transparent, and sustainable AI governance systems to support adaptive digital transformation.