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This article explores the integration of AI governance and BI governance to improve strategic decision-making in Saudi Arabia.

May 27, 2026

Artificial Intelligence and Business Intelligence Governance for Strategic Decision Excellence in Saudi Arabia

Key Points

This article explores the integration of AI governance and BI governance to improve strategic decision-making in Saudi Arabia.
Extensive literature review of academic and government policies from 2020 to 2025.
Focus on AI and BI governance, decision-making quality, and digital government transformation.
Identification of articles related to sector-specific adoption and responsible AI practices.
Six governance pillars are identified as critical for strategic decision excellence: policy alignment, data quality, model governance, human involvement, regulatory compliance, and capabilities development.
BI offers insights into operations, while AI enhances these decisions through predictive and automated support.
Success in AI requires governance structures that establish clear data control and decision rights at executive levels.

Abstract

This article investigates how AI governance and BI governance can be combined to optimize strategic decision-making in Saudi Arabia. Although Saudi Vision 2030, the National Strategy for Data and AI, and the digital government transformation initiative have catalyzed the shift towards more data-driven practices, numerous challenges persist with respect to the integration of data governance, analytics maturity, model transparency, decision responsibility, and decision rights. As such, the key research question explored is how AI governance and BI governance could be designed to ensure accuracy, reliability, transparency, and actionability of insights produced for strategic decision-making purposes in both public and private institutions. An extensive literature review approach was taken, drawing from academic literature as well as from government policies published from 2020 to 2025. Articles relevant to the topic were identified based on their focus on AI and BI governance, decision-making quality improvement, digital government transformation in Saudi Arabia, sector-specific adoption practices, and responsible AI. Results demonstrate that strategic decision excellence requires the presence of six mutually reinforcing governance pillars – policy alignment, data quality stewardship, model and dashboard governance, human involvement, compliance with regulations and ethics, and enterprise-wide capabilities development. Furthermore, it is demonstrated that while BI provides necessary descriptive and diagnostic visibility into operations, the added value provided by AI consists in predictive, automated, optimized, and scenario-based decision support, and it can only be achieved when AI decisions rest upon BI-grade data control and proper decision responsibility defined at executive forums. This review provides an integration framework for AI governance and BI governance and recommendations for its adoption in healthcare, government agencies, financial institutions, and industries in Saudi Arabia.

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