Management and Economics
| Open Access | Orchestrating Digital Trust: A Comprehensive Framework for Integrating Data Governance, Cloud Architectures, and Artificial Intelligence Readiness
Elena V. Markovskaya , Independent Researcher, Strategic Management & Organizational Economics, Moscow, RussiaAbstract
Background: As organizations increasingly migrate to cloud environments and adopt artificial intelligence (AI) technologies, traditional data governance (DG) frameworks often fail to address the complexities of modern digital ecosystems. The lack of alignment between data management strategies, cloud security protocols, and AI ethical standards creates significant risks regarding data sovereignty, algorithmic bias, and digital forensic readiness.
Methods: This study employs a systematic literature review and theoretical synthesis of key sources ranging from 2014 to 2025. The research analyzes existing frameworks, including DMBOK and cloud-specific governance models, to identify Critical Success Factors (CSFs) and structural gaps. A meta-synthesis approach is used to categorize governance activities across banking, healthcare, and telecommunications sectors.
Results: The analysis reveals that successful DG adoption relies heavily on non-technical factors, specifically top-down leadership and organizational culture. Furthermore, current frameworks are often insufficient for Cloud DG due to jurisdictional ambiguities. The study proposes a unified "Digital Trust Framework" that integrates AI readiness and forensic capability as core governance outcomes rather than peripheral activities.
Conclusion: Effective governance in the AI era requires a pivot from static compliance to dynamic, continuous monitoring. The proposed framework offers a roadmap for organizations to operationalize ethics and security, ensuring that data assets remain trustworthy, compliant, and valuable in an automated future.
Keywords
Data Governance, Artificial Intelligence Adoption, Cloud Computing, Digital Forensics
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