On June 3, 2025, the OECD introduced a new framework called AI Capability Indicators that compares AI capabilities to human abilities. The framework is intended to help policymakers assess the progress of AI systems and enable informed policy responses to new AI advancements. The indicators are designed to help non-technical policymakers understand the degree of advancement of different AI capabilities. AI researchers, policymakers, and other stakeholder groups, including economists, psychologists, and education specialists, are invited to submit their feedback to the current beta-framework.

There are nine categories of AI capability indicators, each one presented on a five-level scale mapping AI progression toward full human equivalence, with level 5 representing the most challenging capabilities for AI systems to attain. Each category rates AI performance and assumes human equivalent capability according to the latest available evidence as follows:

1. Language – ranges from basic keyword recognition (Level 1) to contextually aware discourse generation and open-ended creative writing (Level 5). The OECD considers that the capability level of currently available AI systems is Level 3: reliable understanding and generation of semantic meaning using multi-modal language.

• Social interaction – ranges from social cue interpretation (Level 1) to representation of sophisticated emotion intelligence and multi-party conversational fluency (Level 5). The OECD considers that the capability level of currently available AI systems is Level 2: basic social perception with the ability to slightly adapt based on experience, emotions detected through tone and context, and limited social memory.

• Problem solving – ranges from rule-based task execution (Level 1) to new scenarios that require adaptive reasoning, long-term planning, and multi-step inference (Level 5). The OECD considers that the capability level of currently available AI systems is Level 2: integration of qualitative and quantitative reasoning to address complex problems and capable of handling multiple qualitative states and predicting how systems may evolve or change over time.

• Creativity – measures originality and generative capacity in art ranging from template-based generation (Level 1) to creation of entirely novel concepts (Level 5). The OECD considers that the capability level of currently available AI systems is Level 3: generation of output that deviates considerably from the training data and generalization of skills to new tasks and integrate ideas across domains.

• Metacognition and critical thinking – ranges from basic interpretation or recognition of information (Level 1) to managing complex trade-offs between goals, resources, and necessary skills (Level 5). The OECD considers that the capability level of currently available AI systems is Level 2: monitoring and adjustment of the system’s own understanding and approach according to each problem.

• Knowledge, learning, and memory – ranges from data ingestion efficiency and retention (Level 1) to insight-generation from disparate knowledge sources (Level 5). The OECD considers that the capability level of currently available AI systems is Level 3: understanding semantics of information through distributed representations and generalization to novel situations.

• Vision – ranges from basic object recognition (Level 1) to dynamic scene understanding and multi-object tracking under varied environmental conditions (Level 5). The OECD considers that the capability level of currently available AI systems is Level 3: adapting to variations in target object appearance and lighting, performing multiple subtasks, and coping with known variations in data and situations.

• Manipulation – ranges from fine motor control in robotics like picking up simple items (Level 1) to dexterous manipulation of deformable objects (Level 5). The OECD considers that the capability level of currently available AI systems is Level 2: handling different object shapes and moderately pliable materials and operating in controlled environments with low to moderate clutter.

• Robotic intelligence – integrates multiple subdomains like navigation, manipulation, and perception ranging from pre-programmed action (Level 1) to fully autonomous, self-learning robotic agents (Level 5). The OECD considers that the capability level of currently available robotic systems is Level 2: operating in partially known and semi-structured environments with some well-defined variability.

Next Steps

After refining the beta indicators using external feedback, the OECD will implement a procedure for regularly updating AI results on existing benchmark tests and continue identifying new benchmarks tests for missing levels on each scale. As part of this new procedure, the OECD is launching an online repository to systematically collect evidence from benchmarks that test AI capabilities associated with each indicator. AI researchers can submit new benchmarks and other forms of AI evaluation for review and potential integration in future updates of the capability scales. The OECD will host a workshop in 2026 specifically aimed at developing new benchmarks to accurately assess AI capabilities in areas where current tests fall short.

The OECD further announced its intention to recruit experts through a formal periodic expert survey to provide review and input on key statements about AI’s capabilities. The recruitment process is set to begin in 2025 with a panel launch projected for 2026.

The Covington team continues to monitor regulatory developments on AI, and we regularly advise the world’s top technology companies on their most challenging regulatory and compliance issues in the EU and other major markets. If you have questions about AI regulation, or other tech regulatory matters, we are happy to assist with any queries.

This article was written with assistance from Harshana Ghoorhoo.