Journal of AI, Data Science and Cyber Systems

AI Governance, Compliance, and Cyber Risk Management includes the development and implementation of policies, organizational processes, and technical controls to assure the ethical, secure, legal, and risk-aligned operation of AI systems. As AIs take on more vital roles in decision-making and driving automation, governance frameworks establish responsibilities and accountability concerning data usage, model building, model deployment, and monitoring. This includes establishing responsibilities concerning the data’s quality, fairness, transparency, explain ability, human oversight, and the data system’s compliance with regulations, industry standards, and organizational policies. Relative to AI governance from a cyber risk perspective, integrating risk assessment, threat modelling, and ongoing auditing, among other things, helps capture and mitigate data leakage, model manipulation, bias and misuse, and other risk exposure. Compliance mechanisms, along with documentation, data and process traceability, and automated controls, ensure adherence to the applicable privacy, security, and legislation sector mandates. With the consolidation of governance, compliance, and cyber risk management, organizations are equipped to support the responsible use of AI, particularly in innovation and trust, as well as the accountability and adaptability in tightly regulated and high-impact areas such as finance, healthcare, critical infrastructure, and public sector systems.