AI Driven Cloud Security and Anomaly Detection in Saudi Arabia

Abstract

The growing dependence of organizations on cloud computing has expanded both operational efficiency and the surface of cybersecurity risk. Artificial Intelligence (AI) now offers the analytical power to recognize complex patterns of malicious activity that conventional rule-based tools cannot detect. This paper explores how AI-driven anomaly detection can strengthen the security posture of Saudi Arabia’s rapidly evolving cloud ecosystem and support the national objectives of Vision 2030. Using a qualitative, theory-based review of academic and policy sources (2020–2025), the study integrates technical, organizational, and policy dimensions into a conceptual framework linking AI innovation with national cybersecurity governance. The findings suggest that intelligent automation can significantly enhance threat-detection accuracy, reduce incident-response latency, and increase public trust in digital systems—provided that implementation is guided by transparent governance, human-in-the-loop supervision, and clear data-sovereignty principles. The paper concludes that AI-enabled cloud security is not merely a technological upgrade but a strategic requirement for sustainable digital transformation in the Kingdom. Corresponding Author: [email protected]