This chapter explores Neuro-Symbolic AI and its role in enhancing common sense reasoning in AI systems. Addressing the limitations of traditional AI in mimicking human-like reasoning, it delves into how NeSy combines neural networks’ learning capabilities with symbolic AI’s logical reasoning to create more nuanced and intelligent systems. The chapter discusses applications in knowledge-based question answering, cognitive systems, and conversational AI, illustrating the practical implications of NeSy. It also highlights the influence of cognitive science theories, such as mental models, prototype theory, and analogical reasoning, on AI development. Key properties like explainability, robustness, collaboration, and responsibility are examined alongside emerging trends such as anticipatory thinking and multilingualism. Finally, the chapter looks at future directions and the potential of NeSy in various domains, emphasizing its role in building AI systems that are not only technically proficient but also ethically sound and aligned with human cognition.