The rapid evolution of cyber threats has necessitated a paradigm shift in cybersecurity approaches, with a growing emphasis on leveraging artificial intelligence (AI) to bolster automated defense mechanisms. This research delves into the integration of AI technologies within cybersecurity frameworks, exploring their potential to enhance digital resilience against sophisticated cyber threats. By examining the current landscape of cyber attacks and the limitations of traditional defense strategies, the study underscores the need for intelligent, adaptive systems capable of learning from vast datasets and responding in real-time to emerging threats. The research focuses on the development and evaluation of AI-driven defense mechanisms, including machine learning algorithms for anomaly detection, predictive analytics for threat forecasting, and natural language processing for cyber threat intelligence. Through a series of controlled experiments and case studies, the effectiveness of these AI-enhanced systems is assessed in terms of their accuracy, speed, and adaptability to new attack vectors. Findings indicate that AI-augmented cybersecurity solutions can significantly improve the detection and mitigation of advanced persistent threats, zero-day exploits, and other complex cyber attacks. Moreover, the research highlights the importance of ethical considerations and the responsible use of AI in cybersecurity to prevent the misuse of powerful AI tools and ensure privacy and fairness. The study concludes with recommendations for the strategic implementation of AI in cybersecurity, emphasizing the need for a holistic approach that combines human expertise with AI capabilities to achieve robust digital resilience. By fostering a collaborative ecosystem between cybersecurity professionals, AI developers, and policymakers, this research aims to contribute to the ongoing effort to safeguard digital infrastructure against the ever-evolving landscape of cyber threats. © 2025 Elsevier B.V., All rights reserved.