Evolving IT Risk Governance: From Static Policies to AI-Driven Learning Systems
DOI:
https://doi.org/10.15662/IJARCST.2024.0703013Keywords:
AI Governance, Security, IT Risk Management, Compliance, Business Intelligence, AI Learning Systems, GDPR, HIPAA, PCI-DSS, Cloud-Native Environments, Compliance Automation, Data Privacy, Risk Detection, Decision-Making, Machine Learning, Deep LearningAbstract
The transformation of IT risk governance into AI-driven learning systems is one of the most significant changes towards risk, security, and compliance management by the organization. The use of traditional governance frameworks based on a set of rules and manual operations has found it challenging to keep abreast with the dynamic digital environment and the intricacy of current IT infrastructures. Conversely, AI-based learning systems do not cease to learn new data and adjust to the latest threats, which means that risk policies and proactive control of security and compliance are updated in real-time. This paper examines how AI has helped revolutionize IT risk governance and how it has been beneficial in improving decision-making and complying with the checks and security measures. Another aspect that has been explored in the paper is simulated scenarios, real-life scenarios, and limitations to the implementation of such systems, highlighting the possibility of AI transforming IT risk governance in organizations.
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