The integration of the Internet of Everything (IoX) and emerging Artificial General Intelligence (AGI) has given rise to a transformative paradigm aimed at addressing critical bottlenecks across the sensing, network, and application layers in Cyber-Physical-Social-Thinking (CPST) ecosystems. In this survey, we provide a systematic and comprehensive review of pre-AGI and AGI-inspired approaches for IoX, focusing on three key components: sensing-layer data management, network-layer protocol optimization, and application-layer decision-making frameworks. Specifically, this survey explores how pre-AGI and AGI-inspired strategies can mitigate IoX bottlenecks by leveraging adaptive sensor fusion, edge preprocessing, and selective attention mechanisms at the sensing layer. At the network layer, the survey examines solutions to challenges such as protocol heterogeneity and dynamic spectrum management, including approaches based on neuro-symbolic reasoning, active inference, and causal reasoning. Furthermore, the survey investigates AGI-inspired frameworks for managing identity and relationship explosion at the application layer. Key findings suggest that emerging AGI-inspired approaches offer novel solutions to sensing-layer data overload, network-layer protocol heterogeneity, and application-layer identity explosion. These solutions include adaptive sensor fusion, edge preprocessing, and semantic modeling. The survey underscores the importance of cross-layer integration, quantum-enabled communication, and ethical governance frameworks for future AGI-driven IoX systems. Finally, the survey identifies unresolved challenges, including computational requirements, scalability, and real-world validation, and calls for further research to fully realize AGI’s potential in addressing IoX bottlenecks. We believe that AGI-enhanced IoX is emerging as a critical research field at the intersection of interconnected systems and advanced AI.