Cybersecurity Audit Readiness for Resilient Artificial Intelligence Systems: Status Quo and Future Directions

Artificial intelligence is increasingly embedded in day-to-day operations, including highly regulated and sensitive sectors, such as autonomous systems, legal practice, healthcare, and cyber-physical environments. As with any technological evolution, its adoption offers opportunities for operational efficiency and effectiveness but also brings significant, complex, and stealthy cybersecurity concerns. Cybersecurity audit readiness has, therefore, become essential for responsible and secure deployment that balances the enhancements of artificial intelligence against sound cybersecurity readiness, particularly as no area is exempt from this wave. This study systematically assesses the cybersecurity audit-readiness evidence reported in publications on systems enabled by artificial intelligence. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework, 22 studies were selected and assessed using a structured Cybersecurity Audit Readiness Algorithm covering eight assessment dimensions. Nine studies (40.9%) reported evidence classified as High readiness, nine (40.9%) as Moderate readiness, and four (18.2%) as Low readiness; these classifications reflect the strength of documented evidence rather than independently verified operational maturity. The synthesis identifies recurring challenges concerning governance integration, audit traceability, assurance measurement, and continuous monitoring. In response, the study proposes a structured research agenda for advancing the design, evaluation, and implementation of measurable, auditable, and cyber-resilient artificial intelligence systems.