The AI Agent Index
This addresses the problem of transparency and safety assessment for AI developers and researchers, but it is incremental as it organizes existing information without new methods.
The authors tackled the lack of a structured framework for documenting agentic AI systems by introducing the AI Agent Index, a public database that records technical components, applications, and safety features, finding that developers provide ample capability information but limited safety details.
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/