Toward an Integrated Intelligent Data Governance Architecture for Decision-Centric Digital Systems - Bambang Saras Yulistiawan (Institute of Computer Science (IOCS), 2023)
The rapid advancement of artificial intelligence (AI), big data analytics, cloud computing, Internet of Things (IoT), and autonomous digital technologies has transformed modern digital ecosystems into highly interconnected and decision-centric environments. However, the widespread adoption of intelligent systems has also introduced significant governance challenges, including fragmented data governance, cybersecurity risks, interoperability limitations, privacy concerns, algorithmic bias, lack of transparency, and weak accountability mechanisms. Existing governance frameworks often operate independently across data governance, AI governance, cybersecurity, and decision-support systems, making them inadequate for managing dynamic and intelligent digital infrastructures. This study aims to propose an integrated intelligent data governance architecture that supports adaptive, secure, transparent, and decision-centric digital systems. This study employs a qualitative-conceptual methodology using Design Science Research (DSR), Systematic Literature Review (SLR), and framework development approaches. Secondary data were collected from scientific journals, conference proceedings, governance frameworks, industry reports, and international standards such as ISO, OECD AI Principles, NIST AI RMF, GDPR, COBIT, and DAMA-DMBOK. Data analysis was conducted using thematic analysis, comparative analysis, architectural analysis, and governance layer modeling. The findings reveal that intelligent digital ecosystems require integrated governance mechanisms combining data governance, AI governance, cybersecurity, explainable AI, interoperability, decision intelligence, and adaptive feedback systems. The proposed architecture consists of seven interconnected layers that collectively improve governance transparency, accountability, operational resilience, digital trust, and decision quality. The study concludes that integrated intelligent governance architectures are essential for supporting sustainable, secure, and trustworthy digital transformation in modern AI-driven environments.