Investigating the Future of Cybersecurity Post-Gen-AI Integration

The integration of Generative Artificial Intelligence (Gen-AI) into cybersecurity marks a paradigm shift that significantly transforms the threat landscape and defensive strategies of contemporary digital infrastructure. This study examines the long-term implications of Gen-AI technologies on cybersecurity by analysing emergent attack vectors, evolving defence mechanisms, and the broader transformation of the security ecosystem. Through a comprehensive review of current trends and anticipated developments, critical challenges are identified, including autonomous malware generation, large-scale sophisticated social engineering, adversarial machine learning attacks, and the widespread availability of advanced cyber weapons. In parallel, the paper explores defensive advancements, including AI-driven threat detection, automated incident response, and predictive security analytics. The analysis indicates that the post-Gen-AI cybersecurity environment will be defined by an intensified arms race between attackers and defenders, requiring a fundamental rethinking of security architectures, workforce training, and regulatory policies. The paper concludes with strategic recommendations for organisations, policymakers, and the research community to navigate this period of transformation effectively.