This paper discusses how the integration of the Internet of Things (IoX) and Artificial General Intelligence (AGI) presents an innovative paradigm to address bottlenecks occurring at the sensing, network, and application layers of the cyber-physical-social thinking (CPST) ecosystem. We provide a systematic and comprehensive review of AGI-enhanced IoX research, focusing on three major components: sensing layer data management, network layer protocol optimization, and application layer decision framework. In particular, we explore how AGI can alleviate bottleneck issues at the sensing layer by leveraging adaptive sensor fusion, edge preprocessing, and selective attention mechanisms, and how it addresses network layer protocol heterogeneity and dynamic spectrum management through neural symbolic inference, active inference, and causal inference. We also investigate a strategy for managing identity and relationship explosion using AGI-based frameworks. Our main findings suggest that AGI-based strategies such as adaptive sensor fusion, edge preprocessing, and semantic modeling provide novel solutions to sensing layer data overload, network layer protocol heterogeneity, and application layer identity explosion. We highlight the importance of cross-layer integration, quantum-enabled communication, and ethical governance frameworks for future AGI-enabled IoX systems. Finally, we identify unresolved challenges such as computational requirements, scalability, and real-world verification, and call for further research to fully realize the potential of AGI in solving IoX bottlenecks.
