This chapter explores the pursuit of Artificial General Intelligence (AGI), focusing on the potential of Neuro-Symbolic AI to overcome current limitations in AI and advance towards this ambitious goal. AGI aims to replicate the broad cognitive abilities of humans, allowing machines to understand, learn, and apply knowledge across diverse tasks and domains with the versatility and adaptability of human intelligence. The chapter outlines the essential capabilities AGI systems must possess, such as perception, reasoning, learning, and planning, and discusses the profound ethical and societal implications of developing such systems. It highlights the integration of neural networks with symbolic reasoning, presenting Neuro-Symbolic AI as a promising approach that combines the strengths of both paradigms. Recent advancements in Neuro-Symbolic AI models, such as the Neuro-Vector-Symbolic Architecture (NVSA), Logical Neural Networks (LNNs), and the Neuro-Symbolic Concept Learner (NSCL), are examined for their contributions to enhancing AGI capabilities. Furthermore, the synergistic integration of Large Language Models (LLMs) with Knowledge Graphs (KGs) is discussed for its potential to improve factual accuracy and contextual understanding in AI systems. The chapter concludes by emphasizing the need for careful attention to technical, ethical, and societal challenges to ensure the responsible development of AGI, ultimately highlighting the transformative potential of AGI in revolutionizing industries and improving lives.