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Global Index on Responsible AI 2026 : Conceptual Framework and Methodology
- Source
- arXiv — Computers and Society
- Published
- Last verified
- 20 Aug 2026
- Confidence
- High
- Evidence
- Original document retained
- Reading time
- 1 min
- Country
- International
- Relevant to
- People & Capability, Risk & Compliance, Technology & Data, Operations & Delivery, Research & Evidence, Board & Governance
Executive summary
What happened, and why should leadership care?
The Global Index on Responsible AI (GIRAI), 2nd Edition, outlines a refined conceptual framework and methodology for assessing responsible AI governance. This updated edition distinguishes between the existence of AI frameworks and their practical implementation, expanding its structure to five thematic dimensions and introducing more detailed variables for evaluating framework quality. The methodology underwent an independent statistical pre-audit to ensure its robustness.
Why this matters
Why is this strategically important?
This framework offers a standardized and robust approach to evaluate responsible AI governance globally, enabling comparative analysis and identification of best practices. Organizations and nations can leverage this index to benchmark their AI governance efforts and strategically align with evolving international standards for ethical and sustainable AI deployment.
Key insights
What should be noted from the evidence?
- The GIRAI 2nd Edition strengthens the distinction between the mere existence of AI governance frameworks and their actual implementation.
- The thematic dimensions have been restructured from three to five, providing a more comprehensive assessment scope.
- More granular variables have been introduced to evaluate the quality of AI governance frameworks.
- A multi-stage review and validation process, including an independent statistical pre-audit, was conducted to ensure the framework's coherence and robustness.
- The five key dimensions of responsible AI governance assessed by GIRAI are: Inclusion and Diversity, Ethics and Sustainability, Labour and Skills, Trust and Safety, and Use of AI in Public Service.
Evidence and confidence
How far can this assessment be trusted?
High confidence. Named institution, original document retained and analysis corroborated.
Analysis is prepared editorially by Aziz Shuaib Ausi. The original publication remains the authoritative record, and executive judgement remains entirely human.
Source
Where does this originate?
Reported by arXiv — Computers and Society · International. This briefing summarises the publication for executive use; the document itself is not reproduced here.
Read the original publication