Agentic AI for Autonomous Internet-of-Everything: A Distributed Three-Tier Intelligence Ecosystem

The evolution toward Internet of Everything (IoE) ecosystems imposes unprecedented demands for adaptability, scalability, and trustworthiness in 6G networks. Traditional rule-based and centralized management paradigms are increasingly inadequate for distributed cloud-edge-device infrastructures, where a single intent may span sensing, communication, computing, and operational-process domains that no individual controller can fully observe. This article formalizes a cross-domain intent-assurance architecture for autonomous IoE systems: a hierarchical three-tier framework combining cloud LLM agents, edge SLM agents, and TinyML device agents. The framework integrates Agentic AI with Digital Twins (DTs) and Intent-Based Networking (IBN) to support intent translation, predictive validation, and coordinated enforcement across heterogeneous domains. Through two complementary case studies--an edge-centric cooperative-perception scenario and a cross-domain hospital smart-alarm scenario--we show that edge-resident SLM agents achieve cloud-level decision quality with substantially lower operational cost, reducing the per-decision carbon footprint by more than 90% while maintaining high intent satisfaction under increasing operational stress. We conclude by identifying key research challenges, including multi-agent scalability, trustworthy evaluation, explainability, security, and sustainable intelligence. Together, these contributions outline a practical roadmap toward resilient and trustworthy autonomous IoE networks.