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<p>The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) has led to the emergence of the Artificial Intelligence of Things (AIoT), a paradigm that enhances distributed intelligence across interconnected systems. This paper explores the evolutionary shift from AIoT towards the Internet of Artificial Intelligence Agents (IAIA), a transformative framework in which autonomous, networked AI agents engage in collaborative decision-making, real-time learning, and adaptive problem solving. By integrating edge computing, federated learning, and decentralized architectures, IAIA transcends the limitations of conventional IoT and AIoT models, enabling a scalable, resilient, and intelligent ecosystem. We analyze key enablers, including 5G/6G connectivity, blockchain for trust and security, and swarm intelligence for emerging behaviors. Furthermore, we discuss cross-domain applications that span smart cities, healthcare, industrial automation, and next-generation cyber-physical systems. Finally, we outline the critical challenges, such as governance, security, and ethical AI, and propose a roadmap for the widespread adoption of IAIA. This work provides a foundational perspective on the future of intelligent distributed systems, setting the stage for a new era of AI-driven, self-organizing networks.</p>

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The Internet of AI Agents (IAIA): A New Frontier in Networked and Distributed Intelligence

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月25日

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  • Patrizio Dazzi

摘要

The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) has led to the emergence of the Artificial Intelligence of Things (AIoT), a paradigm that enhances distributed intelligence across interconnected systems. This paper explores the evolutionary shift from AIoT towards the Internet of Artificial Intelligence Agents (IAIA), a transformative framework in which autonomous, networked AI agents engage in collaborative decision-making, real-time learning, and adaptive problem solving. By integrating edge computing, federated learning, and decentralized architectures, IAIA transcends the limitations of conventional IoT and AIoT models, enabling a scalable, resilient, and intelligent ecosystem. We analyze key enablers, including 5G/6G connectivity, blockchain for trust and security, and swarm intelligence for emerging behaviors. Furthermore, we discuss cross-domain applications that span smart cities, healthcare, industrial automation, and next-generation cyber-physical systems. Finally, we outline the critical challenges, such as governance, security, and ethical AI, and propose a roadmap for the widespread adoption of IAIA. This work provides a foundational perspective on the future of intelligent distributed systems, setting the stage for a new era of AI-driven, self-organizing networks.