The transformational potential of Artificial Intelligence (AI) presents both un-precedented risks and unique opportunities for the global cybersecurity domain. As threat actors integrate generative AI into their offensive toolkits to automate polymorphic malware and execute sophisticated social engineering campaigns, traditional deep learning defense mechanisms exhibit fundamental limitations in explainability and conceptual grounding. This overview systematically investi-gates the contemporary cyber threat landscape spanning 2024–2025, detailing the evolution of Data-Oriented Attacks (DOA) and AI-enhanced social engineering. To address these vulnerabilities, we propose the Neuro-Symbolic (NeSy) ap-proach, which synergistically combines the statistical pattern-matching capabili-ties of neural networks with the rigorous logic of symbolic reasoning. Through formal semantic analysis, benchmarking of state-of-the-art Large Language Mod-els within Security Operations Centers (SOCs), and the application of the Grounding-Instructibility-Alignment (G-I-A) framework, this paper evaluates the efficacy of NeSy architectures. Finally, we outline a comprehensive research roadmap to 2030 directed toward the realization of fully cognitive, self-healing cyber defense systems.