Manuscript Number : GISRRJ236415

Reviewing Data Governance Strategies for Privacy and Compliance in AI-Powered Business Analytics Ecosystems

Authors(4) :-Bamidele Samuel Adelusi, Abel Chukwuemeke Uzoka, Yewande Goodness Hassan, Favour Uche Ojika

The rise of artificial intelligence (AI)-powered business analytics ecosystems has introduced complex challenges surrounding data privacy, regulatory compliance, and effective data governance. As organizations increasingly rely on automated decision-making and machine learning models, the need for robust governance frameworks to ensure data integrity, security, and accountability has become critical. This review synthesizes diverse strategies from recent literature between 2019 and 2023, emphasizing privacy preservation, regulatory alignment (e.g., GDPR, HIPAA, and local data laws), and ethical AI usage. It explores frameworks that integrate AI governance models with traditional data governance principles, including metadata management, data lineage, and policy enforcement. Priority is given to frameworks proposed by LatifatAyanponle and collaborators, who have contributed significantly to advancing compliance-aware AI models, explainable AI (XAI), and strategic data stewardship. Furthermore, this study highlights the role of decentralized architectures, zero trust principles, and federated learning in enhancing compliance and resilience across global business ecosystems. The findings underscore the necessity of aligning AI model development with enterprise-wide data governance strategies to maintain transparency, reduce bias, and satisfy regulatory demands. This work contributes a synthesized roadmap for practitioners and policymakers to adapt AI governance strategies in increasingly data-driven business environments.

Authors and Affiliations

Bamidele Samuel Adelusi
Independent Researcher, Texas, USA
Abel Chukwuemeke Uzoka
United Parcel Service, Inc.(UPS), Parsippany, New Jersey, USA
Yewande Goodness Hassan
Casava MicroInsurance Ltd, Nigeria
Favour Uche Ojika
Independent Researcher, Minnesota, USA

Data Governance, AI Compliance, Privacy-Preserving Analytics, Regulatory Alignment, Ethical AI Systems

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Publication Details

Published in : Volume 6 | Issue 4 | July-August 2023
Date of Publication : 2023-07-15
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 101-118
Manuscript Number : GISRRJ236415
Publisher : Technoscience Academy

ISSN : 2582-0095

Cite This Article :

Bamidele Samuel Adelusi, Abel Chukwuemeke Uzoka, Yewande Goodness Hassan, Favour Uche Ojika, "Reviewing Data Governance Strategies for Privacy and Compliance in AI-Powered Business Analytics Ecosystems", Gyanshauryam, International Scientific Refereed Research Journal (GISRRJ), ISSN : 2582-0095, Volume 6, Issue 4, pp.101-118, July-August.2023
URL : https://gisrrj.com/GISRRJ236415

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