Extending and Improving Current Frameworks for Risk Management and Decision Making: Incorporating Dynamic Aspects of Risk and Uncertainty in Saudi Arabia

An improved dynamic risk management approach designed for Saudi Arabia's quickly changing legislative and economic environment is put forth in this article. Adaptive and forward-looking risk measures are more important than ever in light of Vision 2030's lofty ambitions, especially the push for infrastructure megaprojects, privatization, and economic diversification. Current risk management methods, which are frequently linear and static, are inadequate in VUCA (volatility, uncertainty, complexity, and ambiguity) contexts. We address this by presenting a new integrative framework that combines AI-based predictive analytics, fuzzy logic, multi-criteria decision-making (MCDM), and real-time monitoring systems. The framework strengthens the robustness of strategic decision-making, increases stakeholder response, and promotes ongoing review by including these dynamic tools. The framework's applicability and policy consequences are illustrated by two case studies, one of which concerns the national COVID-19 reaction and the other a NEOM infrastructure program. Significant gains in agility, coordination, and outcome quality are demonstrated by the results, indicating that this strategy may find wider use in other Gulf Cooperation Council (GCC) countries.