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In the evolving landscape of cybersecurity, traditional information technology (IT) infrastructures often struggle to meet the demands of modern risk management frameworks, which require enhanced security, scalability, and analytical capabilities. This paper proposes a novel artificial intelligence (AI)–driven IT infrastructure backed by blockchain technology, specifically designed to optimize risk management processes in diverse organizational environments. By leveraging artificial intelligence for predictive analytics, anomaly detection, and data-driven decision-making, combined with blockchain’s secure and immutable ledger for data integrity and transparency, the proposed infrastructure offers a robust solution to existing challenges in risk management. The infrastructure is adaptable and scalable to support a variety of risk management methodologies, providing a more secure, efficient, and intelligent system. The findings highlight significant improvements in the accuracy, speed, and reliability of risk management, underscoring the infrastructure’s capability to proactively address emerging cyber threats. To ensure the proposed model effectively addresses the most critical issues, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique will be used to analyze and evaluate the interrelationships among the existing critical factors. This approach evaluates the interrelationships and impacts of these factors, verifying the model’s comprehensiveness in managing organizational risk. This study lays the foundation for future research aimed at refining AI-driven infrastructures and exploring their broader applications in enhancing organizational cybersecurity.