Global Index on Responsible AI 2026 : Conceptual Framework and Methodology

The index distinguishes between having AI policies and actually implementing them: The 2nd Edition strengthens the separation between framework existence and implementation, recognizing that many countries may have responsible AI policies on paper but lack effective enforcement—a critical distinction for assessing genuine governance.

Five key areas define responsible AI governance: The framework evaluates countries across Inclusion and Diversity, Ethics and Sustainability, Labour and Skills, Trust and Safety, and Use of AI in Public Service, with 38 total indicators providing a comprehensive view of what responsible AI governance should cover.

Implementation is assessed through multiple data sources and layers: The index uses 135 country-level researchers collecting primary data on government policies and civil society engagement, combined with secondary datasets on structural conditions, creating a more rigorous and multi-perspective assessment than relying on any single source.

Accountability mechanisms are built in: The framework includes a specific penalty indicator for government use of "Unacceptable Risk AI," ensuring that countries cannot score well on responsible AI governance if they themselves deploy high-risk AI systems irresponsibly.

The methodology underwent independent statistical validation: An independent pre-audit assessed the framework's coherence and robustness, suggesting the index was designed with transparency and rigor in mind rather than as a simple ranking tool.