How can AI agents participate in digital markets?
BEYOND THE SUM: UNLOCKING AI AGENTS POTENTIAL THROUGH MARKET FORCES
This paper explores how to enable AI agents, powered by Large Language Models (LLMs), to participate in digital markets as independent economic actors. It analyzes the current digital infrastructure (identity, payments, service discovery, software interfaces) and identifies key limitations that prevent AI agents from operating effectively at machine speed and scale. Specifically, it highlights the human-centric design of these systems as a major bottleneck, arguing for new protocols and infrastructure optimized for AI agent interactions, including: decentralized identity management for ephemeral agents, machine-readable service descriptions, real-time payment and authorization systems, and unified interfaces that adapt to agent capabilities. The paper proposes leveraging technologies like capability-based security, context-aware authorization, and cryptographic attestation to overcome these challenges. It envisions emergent, decentralized market intelligence arising from the interactions of numerous specialized AI agents, drastically enhancing economic efficiency.