Regulating AI in Cybersecurity: Balancing Challenges, Opportunities, and Global Frameworks

Abstract

Artificial Intelligence (AI) is simultaneously a transformative enabler and a regulatory challenge in the fast-evolving domain of cybersecurity. Artificial intelligence is gradually taking over human labour and decision-making. Numerous industries, including manufacturing, transportation, logistics, government, health, education, and commerce, have made substantial use of it. This study investigates how AI is currently deployed within cybersecurity frameworks, the ethical and legal risks it introduces, and the adequacy of emerging regulatory responses. Methodologically, a systematic literature review aligned with PRISMA principles was applied, drawing from peer-reviewed articles, regulatory reports, and international policy guidelines. Key findings show that while AI improves detection, automation, and cyber resilience, it also generates risks of algorithmic bias, data privacy breaches, and malicious misuse. Comparative analysis of the EU AI Act, the US NIST AI Risk Management Framework, China’s AI regulations, and OECD principles reveals fragmented governance. This paper contributes by proposing the AI-Cybersecurity Regulatory Integration Model, a conceptual framework aligning risk management, accountability, and cybersecurity safeguards. We conclude that effective governance requires harmonisation of global standards, operationalisation of ethical principles, and sustained cross-sector collaboration.