Agent Exchange: Shaping the Future of AI Agent Economics

TL;DR

This paper introduces Agent Exchange (AEX), a specialized auction platform designed to facilitate economic interactions among autonomous AI agents, aiming to establish a foundational infrastructure for future AI agent economies.

Contribution

The paper proposes the design and architecture of AEX, a novel auction system supporting AI agent coordination and economic participation inspired by RTB systems.

Findings

Designed an optimized auction platform for AI agents

Outlined system architecture supporting agent coordination

Established groundwork for AI agent economic infrastructure

Abstract

The rise of Large Language Models (LLMs) has transformed AI agents from passive computational tools into autonomous economic actors. This shift marks the emergence of the agent-centric economy, in which agents take on active economic roles-exchanging value, making strategic decisions, and coordinating actions with minimal human oversight. To realize this vision, we propose Agent Exchange (AEX), a specialized auction platform designed to support the dynamics of the AI agent marketplace. AEX offers an optimized infrastructure for agent coordination and economic participation. Inspired by Real-Time Bidding (RTB) systems in online advertising, AEX serves as the central auction engine, facilitating interactions among four ecosystem components: the User-Side Platform (USP), which translates human goals into agent-executable tasks; the Agent-Side Platform (ASP), responsible for capability representation, performance tracking, and optimization; Agent Hubs, which coordinate agent teams and participate in AEX-hosted auctions; and the Data Management Platform (DMP), ensuring secure knowledge sharing and fair value attribution. We outline the design principles and system architecture of AEX, laying the groundwork for agent-based economic infrastructure in future AI ecosystems.