Evidence before assertion
Material findings should be supported by assessment responses, supplied evidence or clearly identified professional interpretation.
QUALITY & ASSURANCE CHARTER
Professional judgement supported by visible controls.
This charter describes how ARI findings are handled, reviewed and released. It does not disclose the protected questions, weightings or decision rules.
Proportionate judgement
Recommendations should reflect organisational scale, context, ambition, risk and delivery capacity.
Human professional review
Technology may support consistency, but unchecked automated output is not released as a client report.
Limitations made visible
Assumptions, evidence gaps and matters requiring specialist legal, security or sector advice are identified.
Controlled release
Reports carry a reference, version, status and confidentiality marking to distinguish controlled output from working material.
Continuous improvement
Feedback, delivery experience and relevant external guidance are reviewed without silently changing released client reports.
INDEPENDENCE COMMITMENT
The recommendation must serve the client decision.
- unoui is vendor-neutral and does not sell software licences.
- ARI may conclude that AI is not appropriate for a proposed problem.
- Assessment purchase does not require implementation purchase.
- Implementation is separately scoped only after priorities are visible.
- No undisclosed supplier commission should influence a recommendation.
REFERENCE FRAMEWORKS
Informed by recognised principles—not presented as certification.
ARI is an independent readiness assessment. Reference to an external framework does not imply certification, accreditation, approval or endorsement by its publisher.
UK Government AI Risk Management ToolkitRisk identification, assessment, treatment, monitoring and reporting inform ARI's approach to organisation-specific AI risk.Official source ↗NIST AI RMFGovern, Map, Measure and Manage provide useful reference principles for risk-aware decision making.Official source ↗ISO/IEC 42001:2023AI management-system principles inform attention to policy, accountability, risk, opportunity and continual improvement.Official source ↗ICO guidanceUK data-protection expectations inform attention to lawful, fair, transparent and accountable use of personal data.Official source ↗UK Responsible AI ToolkitGovernment assurance resources inform proportionate evidence and responsible deployment considerations.Official source ↗
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