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Research governance

Research Disclaimer

Important limitations governing AI Governance Ratings research, methodology analysis, third-party data, standards references and decision use.

Last reviewed: August 25, 2026

Research, not an issued rating

Publications on AIGovernanceRatings.com are institutional research, category analysis and methodology analysis unless expressly identified otherwise. Publication of research about AI Governance Ratings does not issue, affirm, upgrade, downgrade, suspend or withdraw an AIGR™ rating for any organization, system, product or jurisdiction.

No professional advice or regulatory determination

Research is not legal advice, regulatory guidance, an audit or assurance opinion, accredited certification, cybersecurity certification, investment advice, insurance advice, credit analysis or a determination that an AI system is safe, lawful, secure or fit for a particular purpose.

Data and source limitations

Research may rely on public laws, regulations, standards, official frameworks, external datasets, vendor information, academic research and related institutional publications. Source materials may contain errors, use different definitions, cover different periods or be revised after publication. Readers should consult the underlying source and current authoritative requirements before making a material decision.

Standards and regulatory references

References to NIST, ISO, OECD, the European Union, regulators, standards bodies or other organizations are for research and analytical context. They do not imply sponsorship, affiliation, endorsement, accreditation or certification by those organizations.

Related organizations and methodology

AIGX Research™ may be cited for related Responsible AI governance research, sector frameworks or benchmark methodology. AIGR™ Global maintains the operative Artificial Intelligence Governance Ratings methodology. AIGovernanceRatings.com should not be interpreted as an unrelated independent third party to those disclosed relationships.

Emerging and forward-looking subjects

Research on emerging regulation, agentic AI, market practices or developing standards may discuss expected directions, implementation questions or analytical scenarios. Such discussion is inherently subject to change and should not be interpreted as a prediction or commitment regarding future regulation, technology performance or rating outcomes.

Corrections and updates

Material factual errors should be corrected after verification. Research references, versions and review dates are intended to help readers identify the material in effect at a particular time. See the Editorial & Research Policy and Data Sources & Citation Policy.