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The AI Agent Index is a research project and database that documents and compares selected deployed AI agents. It records information about systems’ origins, capabilities, autonomy, ecosystem connections, safety and developer disclosures. It is a dated catalog with edition-specific selection rules—not a universal definition of an AI agent, a live leaderboard or a test that proves which system is best.
What the AI Agent Index is
The project, hosted at aiagentindex.mit.edu, aims to make a fast-changing and inconsistently documented field easier to examine. It organizes publicly available information and developer correspondence into structured entries, so readers can compare what selected systems do and what their developers disclose about them. The project described its 2024 edition as the first public database to document currently deployed agentic systems.
The index is useful as a research and reference resource: it can help readers ask who is building prominent systems, where they are deployed, how they interact with tools, and what safety or evaluation information is available. It is not a performance benchmark, a safety certification or a census of every AI agent.
Does the index define what an AI agent is?
No. The project says there is no agreed-upon definition of “AI agent,” and the 2024 edition does not choose one definition or propose its own. Instead, each edition sets rules for deciding which systems to include. Those rules describe the index’s scope; they do not settle the meaning of the term for the entire field.
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The 2025 methodology describes the systems it focuses on as exhibiting, to a significant degree, four traits:
- Autonomy: operating with minimal human oversight.
- Goal complexity: pursuing higher-level objectives through planning and subgoals.
- Environmental interaction: directly affecting the world through tools and APIs.
- Generality: handling underspecified instructions and adapting to new tasks.
These are the 2025 edition’s screening dimensions, not a universal checklist that every organization must use to label a product an agent.
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How the 2024 and 2025 editions differ
The count and scope depend on the edition. The 2025 list is smaller than the 2024 list because the project changed its criteria and annotation approach and focused on fewer systems in greater depth; the change does not establish that fewer agents existed in 2025.
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| Edition | Snapshot and collection period | Systems and organization | Selection and annotation approach |
|---|---|---|---|
| 2024 | Snapshot as of December 31, 2024; collection work ran from August 2024 to January 2025, according to the project. | 67 systems across six categories: software, computer use, universal, research, robotics and other. | Used a framework based on underspecification, directness of impact, goal-directedness and long-term planning. |
| 2025 | Criteria evaluated as of December 31, 2025, according to the project. | 30 agents grouped as chat applications with agentic tools, browser-based agents and enterprise workflow agents; annotated in 45 fields across six categories. | Required all four agency dimensions, at least one impact criterion, and all practicality criteria. |
The 2025 fields cover product overview; company and accountability; technical capabilities; autonomy and control; ecosystem interaction; and safety, evaluation and impact. For inclusion, a system needed at least one of these impact characteristics: public interest, market significance or developer significance. It also had to meet all three practicality conditions: public availability, off-the-shelf deployability and general-purpose use. These are not the 2024 rules, so the edition counts should not be treated as a like-for-like measurement of the whole agent market.
What readers can compare in the index
The structured entries are intended to make public evidence easier to inspect across systems: what they can do, how much control they exercise, how they connect to tools or other ecosystems, and what their developers say about safety and evaluation. That makes the index particularly useful for identifying differences in disclosure as well as differences in described capabilities.
The 2025 project summary reports several findings about its selected set. They should be read as project-specific results, not as market-wide rates or an independent census:
- The project reported that seven subject-matter annotators worked on the 2025 edition.
- Among 13 agents the project classified as exhibiting frontier autonomy, 4 disclosed any agentic safety evaluations.
- It associated 21 of the 30 indexed systems with the United States and 5 with China, using its own attribution method.
- It reported that almost all indexed agents depended on GPT, Claude or Gemini model families.
These figures illustrate what a structured catalog can surface, but they do not show that one agent is safer or more capable than another. The project’s summaries and methodology are available on the official AI Agent Index site.
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Each edition is a dated snapshot with a stated cutoff, not a continuously updated leaderboard. The 2024 collection has an explicit December 31, 2024 snapshot date, and the 2025 edition says its criteria were evaluated as of December 31, 2025. A system, feature or disclosure can change after the relevant cutoff.
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The project also cautions that eligible systems may be omitted and annotations may contain inaccuracies. Use the index to understand the documented systems and evidence within a particular edition, then check the project’s current pages and the developers’ own materials when a recent product change matters.
How to use it without overreading the entries
- Identify the edition. Note its snapshot date before relying on a count or description.
- Read the inclusion rules. A system’s presence or absence reflects that edition’s selection criteria, not a universal judgment about whether it is an agent.
- Separate disclosure from demonstrated performance. An entry can document developer claims and available evaluations; that alone does not establish comparative capability or safety.
- Check details that may have changed. For decisions that depend on current behavior, verify the relevant capability, safety information or availability with the developer.
Distinguishing it from a similarly named directory
The MIT-hosted AI Agent Index is a research project. A separate site, theaiagentindex.com, presents a commercial directory for businesses evaluating AI agents. The two should not be confused: the MIT project’s edition dates, selection rules and findings do not describe that separate directory, and claims about one do not establish claims about the other.
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