The rapid development of artificial intelligence (AI) and machine learning (ML) technologies has ushered in a new era of challenges and opportunities for cybersecurity, particularly in the context of hybrid warfare and critical infrastructure protection. This paper explores the dual nature of ML in both offensive and defensive capacities within the evolving landscape of hybrid threats. A brief overview of key ML techniques is provided, including supervised and unsupervised learning, reinforcement learning, deep learning and natural language processing. This article then examines five primary battlefields where AI/ML plays a critical role: Social Media Manipulation, Deep Fakes and Synthetic Media, Targeted Phishing Attacks, Cyber Warfare, and Autonomous Weapons Systems. The background, development, original intentions, and current offensive and defensive applications of the relevant ML technologies are discussed for each area. It also addresses the ethical considerations and challenges of integrating AI into warfare and security, including accountability issues, escalation risks, privacy concerns and the need for human oversight.