The AI Agent Index

TL;DR

The paper introduces the AI Agent Index, a comprehensive public database documenting the components, uses, and safety practices of deployed agentic AI systems to improve transparency and safety assessment.

Contribution

It creates the first structured, publicly accessible database for documenting technical details, applications, and safety features of agentic AI systems.

Findings

Developers provide detailed info on capabilities and applications.

Safety and risk management info is limited.

The index promotes transparency and safety assessment.

Abstract

Leading AI developers and startups are increasingly deploying agentic AI systems that can plan and execute complex tasks with limited human involvement. However, there is currently no structured framework for documenting the technical components, intended uses, and safety features of agentic systems. To fill this gap, we introduce the AI Agent Index, the first public database to document information about currently deployed agentic AI systems. For each system that meets the criteria for inclusion in the index, we document the system's components (e.g., base model, reasoning implementation, tool use), application domains (e.g., computer use, software engineering), and risk management practices (e.g., evaluation results, guardrails), based on publicly available information and correspondence with developers. We find that while developers generally provide ample information regarding the capabilities and applications of agentic systems, they currently provide limited information regarding safety and risk management practices. The AI Agent Index is available online at https://aiagentindex.mit.edu/