The 2025 AI Agent Index: Documenting Technical and Safety Features of Deployed Agentic AI Systems

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Authors: Leon Staufer, K. J. Kevin Feng, Kevin Wei, Luke Bailey, Yawen Duan, Mick Yang, A. Pinar Ozisik, Stephen Casper, Noam Kolt
Cited by: 3
References: 33

Abstract

Agentic AI systems are increasingly capable of performing professional and personal tasks with limited human involvement. However, tracking these developments is difficult because the AI agent ecosystem is complex, rapidly evolving, and inconsistently documented, posing obstacles to both researchers and policymakers. To address these challenges, this paper presents the 2025 AI Agent Index. The Index documents information regarding the origins, design, capabilities, ecosystem, and safety features of 30 state-of-the-art AI agents based on publicly available information and email correspondence with developers. In addition to documenting information about individual agents, the Index illuminates broader trends in the development of agents, their capabilities, and the level of transparency of developers. Notably, we find that transparency varies substantially across agent developers and observe that most developers share little information about safety, evaluations, and societal impacts. The 2025 AI Agent Index is available online at https://aiagentindex.mit.edu.

Fields of Study & Subjects

Multi-Agent Systems and Negotiation Ethics and Social Impacts of AI Reinforcement Learning in Robotics

Publication details

Journal / source
Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency
Publisher
ACM
Pages
1536–1576
Publication date
23 June 2026