AI-driven data governance: Automating policy enforcement in the cloud

This article examines the emergence of AI-driven data governance as a transformative approach for enterprises adopting cloud-native Business Intelligence and data engineering architectures. As organizations navigate the complexities of multi-cloud and hybrid environments, traditional governance models prove insufficient for managing the scale, velocity, and variety of modern enterprise data. Artificial intelligence and machine learning technologies enable automated policy enforcement, enhance compliance monitoring, and strengthen security protocols in real-time. Implementation strategies across various industries demonstrate how AI-driven governance frameworks can integrate with existing cloud infrastructure while maintaining alignment with regulatory requirements such as GDPR, CCPA, HIPAA, and SOC 2. The insights provided contribute to the evolving discourse on intelligent data governance and offer actionable guidance for organizations seeking to modernize their governance practices in increasingly complex data ecosystems.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-05-20
DOI
https://doi.org/10.30574/wjaets.2025.15.2.0728
Citations
1
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
2.48
Controls
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article

AI-driven data governance: Automating policy enforcement in the cloud

Muruganantham Angamuthu
1 citations
World Journal of Advanced Engineering Technology and Sciences
Privacy-Preserving Technologies in Data
2.48
article

AI-driven data governance: Automating policy enforcement in the cloud

Muruganantham Angamuthu
article en
1 citations

Abstract

This article examines the emergence of AI-driven data governance as a transformative approach for enterprises adopting cloud-native Business Intelligence and data engineering architectures. As organizations navigate the complexities of multi-cloud and hybrid environments, traditional governance models prove insufficient for managing the scale, velocity, and variety of modern enterprise data. Artificial intelligence and machine learning technologies enable automated policy enforcement, enhance compliance monitoring, and strengthen security protocols in real-time. Implementation strategies across various industries demonstrate how AI-driven governance frameworks can integrate with existing cloud infrastructure while maintaining alignment with regulatory requirements such as GDPR, CCPA, HIPAA, and SOC 2. The insights provided contribute to the evolving discourse on intelligent data governance and offer actionable guidance for organizations seeking to modernize their governance practices in increasingly complex data ecosystems.

World Journal of Advanced Engineering Technology and SciencesVol. 15(2)
Openalex Percentile: Top 10%
Privacy-Preserving Technologies in Data
2.48
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AI-driven data governance: Automating policy enforcement in the cloud — Muruganantham Angamuthu · World Journal of Advanced Engineering Technology and Sciences (2025) | TGRS Research Map | TGRS