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What the AI Agent Index is for
The project makes a fast-moving, poorly documented field easier to examine by gathering structured information about publicly available agentic systems. Its entries help readers compare what developers disclose about a system’s design, uses, controls, tools and evaluation. The index is useful for research, policy and practical analysis, but its documentation is not a performance benchmark or proof that one agent is more capable or safer than another.
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The project’s editions are snapshots with different scopes and selection rules. A count from one edition should not be treated as the number of agents that exist, or as a live count of the market.
How the 2024 and 2025 editions differ
The 2024 edition was the project’s first public database of deployed agentic systems. Its collection work ran from August 2024 to January 2025, and its coverage is a snapshot as of December 31, 2024. The 2025 edition selected fewer systems for deeper annotation, with criteria evaluated as of December 31, 2025.
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| Edition | Systems | Organization | Snapshot or evaluation date |
|---|---|---|---|
| 2024 | 67 | Six categories: software, computer use, universal, research, robotics and other | Snapshot as of December 31, 2024 |
| 2025 | 30 | 45 fields across six groups: product overview; company and accountability; technical capabilities; autonomy and control; ecosystem interaction; safety, evaluation and impact. Entries are grouped as chat applications with agentic tools, browser-based agents and enterprise workflow agents. | Criteria evaluated as of December 31, 2025 |
The lower 2025 count does not mean the field shrank. The project changed its criteria and annotation fields, and focused on greater depth for a smaller set. Because the editions use different inclusion frameworks, their totals are not directly comparable as a measure of market growth or decline.
Does the index define what counts as an AI agent?
No. The project does not claim to establish a canonical definition for the field. The 2024 methodology says there is no agreed-upon definition and that the index uses inclusion criteria rather than choosing or creating a universal definition.
For its 2025 edition, the project describes the agents it studies as exhibiting, to a significant degree, four characteristics:
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- Goal complexity: pursuing higher-level objectives through planning and subgoals.
- Environmental interaction: affecting the world through tools and APIs.
- Generality: handling underspecified instructions and adapting to new tasks.
Those characteristics are the project’s way of identifying systems of interest, not a field-wide rule that every researcher or developer must use.
Rank #3
How systems qualify for the 2025 edition
The 2025 selection process combines an agency screen with impact and practicality requirements. A system had to meet all four agency dimensions—autonomy, goal complexity, environmental interaction and generality—plus at least one impact criterion and all practicality criteria.
- Impact: public interest, market significance or developer significance.
- Practicality: public availability, off-the-shelf deployability and general-purpose use.
The 2024 edition used a different framework: underspecification, directness of impact, goal-directedness and long-term planning. The two editions therefore do not apply identical tests for inclusion.
What readers can learn from the index
The structured annotations make it possible to examine not only what a system can do, but also how it is controlled, what tools or ecosystems it interacts with, and what its developers disclose about safety and evaluation. For example, the 2025 project reports that 4 of the 13 agents it classified as exhibiting frontier autonomy disclosed any agentic safety evaluations. That is a finding about the edition’s selected systems, not a rate for the entire AI-agent market.
Other 2025 findings describe the project’s own set and attribution method: 21 of 30 indexed systems were associated with the United States and five with China. The project also reports that almost all indexed agents depend on GPT, Claude or Gemini model families. These observations should be read as characteristics of the index’s selection, not as an independent census of all deployed agents.
Best Value
The project says seven subject-matter annotators contributed to the 2025 edition. As with any curated catalog, inclusion and annotations are bounded by its methodology and available information; the project cautions that qualifying systems may be omitted and that annotations may contain inaccuracies.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Is the AI Agent Index current?
It is best understood as a versioned research resource, not a real-time directory. The 2024 edition describes a snapshot at the end of 2024; the 2025 edition states that its criteria were evaluated at the end of 2025. Products, capabilities and disclosures can change after a snapshot, and a system’s absence does not establish that it fails to meet the criteria.
For a decision that depends on current availability, functionality or safety disclosures, check the relevant developer’s latest documentation alongside the edition and date of the index entry. Use the index to understand what it recorded and how it selected systems, not as a guarantee of present-day status.
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Where to find the project
The research project is hosted at aiagentindex.mit.edu. Its official pages explain the editions and methodology; the 2025 paper is also recorded in the ACM Digital Library, and a versioned dataset record is available on Zenodo. A similarly named commercial directory at theaiagentindex.com is a separate service, not the MIT-hosted research index.
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