Collaborative Agentic AI Needs Interoperability Across Ecosystems

2025-05-25

AI Summary

Collaborative autonomous AI systems suffer from severe fragmentation due to the absence of interoperability standards, hindering openness, security, and scalable deployment. To address this, we propose *Agent Web*, the first lightweight, cross-ecosystem interoperability framework for autonomous agents. It defines four core components: standardized message passing, interaction protocols, state management, and agent discovery. Methodologically, Agent Web leverages mature web standards—including HTTP, JSON-LD, Decentralized Identifiers (DIDs), and OAuth 2.1—integrated with decentralized identity and semantic message protocols to enable secure, verifiable communication among heterogeneous agents. Our key contributions are: (1) a minimally viable, incrementally compatible interoperability solution that avoids vendor lock-in; and (2) a concrete, immediately actionable implementation roadmap that mitigates ecosystem fragmentation and advances collaborative AI toward open, trustworthy, large-scale coordination.

Technology Category

• Multiagent Systems: Agent Communication
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Application Domains: Web

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Agentic search

Abstract

Collaborative agentic AI is projected to transform entire industries by enabling AI-powered agents to autonomously perceive, plan, and act within digital environments. Yet, current solutions in this field are all built in isolation, and we are rapidly heading toward a landscape of fragmented, incompatible ecosystems. In this position paper, we argue that interoperability, achieved by the adoption of minimal standards, is essential to ensure open, secure, web-scale, and widely-adopted agentic ecosystems. To this end, we devise a minimal architectural foundation for collaborative agentic AI, named Web of Agents, which is composed of four components: agent-to-agent messaging, interaction interoperability, state management, and agent discovery. Web of Agents adopts existing standards and reuses existing infrastructure where possible. With Web of Agents, we take the first but critical step toward interoperable agentic systems and offer a pragmatic path forward before ecosystem fragmentation becomes the norm.

Problem

• Addressing fragmented ecosystems in collaborative agentic AI
• Promoting interoperability through minimal standards adoption
• Proposing Web of Agents foundation for unified systems

Innovation

• Adopts minimal standards for interoperability
• Introduces Web of Agents architecture
• Reuses existing infrastructure and standards