Research supporting evidence-based AI governance.
AIGR draws on the published methodology and sector research of AIGX Research. Publications are versioned and distinguish published work from material still in review or development.
Selected AIGX Research publications and programs.
Responsible AI Governance: 2026 Market Outlook
Examines evidence-based governance, standards convergence, sector evidence thresholds and the emerging assurance layer.
Responsible AI Governance: Enterprise Benchmark
Focuses on control coverage, evidence completeness and open gate states across completed assessments under consent and confidentiality rules.
Responsible AI Governance: Healthcare Framework
Addresses clinical safety, model validation, human oversight, monitoring, third-party controls and data privacy.
Responsible AI Governance: Government Framework
Develops controls for public accountability, transparency, rights and safety, records and oversight.
Different sectors. One evidence model.
Health
Clinical safety, evidence traceability, human oversight, privacy and lifecycle monitoring.
Finance
Model risk, explainability, fairness, third-party controls and regulatory reporting.
Agentic AI
Delegated authority, tool access, action boundaries, escalation and observability.
Government
Public accountability, transparency, rights and safety, records and oversight.
AIGR platform outputs and AIGX Research publications support governance evaluation and decision-making. They do not constitute certifications, regulatory approvals, legal opinions or attestations of compliance.