The paper "Cybersecurity Challenges in the Age of AI: Theoretical Approaches and Practical Solutions" by Babajide Tolulope Familoni explores the intricate relationship between artificial intelligence (AI) and cybersecurity. It highlights the dual nature of AI, which offers significant advancements in threat detection, authentication, and response mechanisms while also introducing new vulnerabilities and challenges. The theoretical framework delves into the interplay between AI algorithms, human behavior, and adversarial tactics, emphasizing the need for robust threat intelligence, adaptive defense mechanisms, and ethical considerations. Practical solutions include leveraging AI for enhanced detection capabilities, automating response actions, and augmenting human analysts' expertise. However, the paper also addresses the limitations of AI-driven systems, such as algorithmic biases, data privacy concerns, and the potential for AI-enabled attacks. Regulatory frameworks and industry standards are crucial for ensuring accountability, transparency, and compliance with ethical principles. Interdisciplinary collaboration and investment in cybersecurity education are vital for cultivating a skilled workforce equipped to navigate the evolving threat landscape. The paper concludes by emphasizing the importance of integrating theoretical insights with practical strategies to secure AI-driven systems effectively.The paper "Cybersecurity Challenges in the Age of AI: Theoretical Approaches and Practical Solutions" by Babajide Tolulope Familoni explores the intricate relationship between artificial intelligence (AI) and cybersecurity. It highlights the dual nature of AI, which offers significant advancements in threat detection, authentication, and response mechanisms while also introducing new vulnerabilities and challenges. The theoretical framework delves into the interplay between AI algorithms, human behavior, and adversarial tactics, emphasizing the need for robust threat intelligence, adaptive defense mechanisms, and ethical considerations. Practical solutions include leveraging AI for enhanced detection capabilities, automating response actions, and augmenting human analysts' expertise. However, the paper also addresses the limitations of AI-driven systems, such as algorithmic biases, data privacy concerns, and the potential for AI-enabled attacks. Regulatory frameworks and industry standards are crucial for ensuring accountability, transparency, and compliance with ethical principles. Interdisciplinary collaboration and investment in cybersecurity education are vital for cultivating a skilled workforce equipped to navigate the evolving threat landscape. The paper concludes by emphasizing the importance of integrating theoretical insights with practical strategies to secure AI-driven systems effectively.