The book explores how quantum computing can protect AI systems from sophisticated adversarial threats. As AI applications grow in sectors like finance, healthcare, and critical infrastructure, vulnerabilities such as data poisoning and model inversion pose significant security risks. This book investigates how quantum methods can effectively counter these challenges. Distinct from existing literature, it combines theoretical insights with practical applications, covering quantum-enhanced cryptography, quantum machine learning for threat detection, and advanced algorithms tailored for AI. It provides actionable solutions for AI practitioners while also meeting the academic needs of researchers with rigorous mathematical treatments. The book is targeted at academic researchers, professionals, and graduate students in computer science interested in AI and quantum computing. It goes beyond mathematical concepts to bridge quantum theory and its practical applications across sciences and industries. By offering both foundational principles and advanced quantum defense applications, this book serves as a vital resource for those developing AI systems with robust, quantum-enhanced security.