About Trust Score
Methodology
Trust Score exists to answer one question: is this organization ready to apply AI to a real operational problem, or is it chasing hype without the governance, data, and process maturity to make it work?
The scoring model
- Structured maturity answers. Each of the 23 questions offers five options describing increasing operational maturity, mapped to values 1 through 5. There are no yes/no questions.
- Normalization. Each answer is converted to a 0–100 contribution and weighted within its dimension.
- Dimension scores. Six scores from 0 to 100 are produced, one per dimension.
- Overall Trust Score. The dimension scores are combined using dimension weights that reflect their influence on responsible deployment.
- Derived outputs. Readiness level, strategic impulse risk, strengths, risks, recommendations, next move, and pilot path are all derived from the same computed values by fixed rules.
Dimension weighting
Each dimension score is multiplied by its weight below, then the total is divided by the sum of the weights (6.70) to produce a weighted average. A higher weight means that dimension has more influence on the final Trust Score.
Use Case Clarity
Whether AI is being applied to a real operational task, workflow gap, efficiency opportunity, or risk mitigation need.
Operational Fit
Whether AI fits the organization's existing workflows, ownership model, decision points, and operational capacity.
Data Readiness
Whether data quality, access, structure, governance, and infrastructure support responsible AI use.
Governance and Risk Controls
Whether oversight, accountability, risk review, approval, human review, and controls exist.
Trustworthiness of Outputs
Whether outputs can be validated, explained, monitored, and trusted inside real workflows.
Change Management and Adoption
Whether leaders, teams, and users are prepared to adopt AI responsibly in the real work environment.
Readiness thresholds
A score in this range means the foundations required to deploy AI safely are not in place. Use case definition, data, ownership, or oversight are weak enough that an initiative launched now would be difficult to evaluate, defend, or unwind. This is a caution result, not a starting gun. Stop initiative work and rebuild the foundation before committing budget.
Real foundations exist, but material gaps remain. There is enough structure to attempt something narrow and heavily controlled, and not enough to survive production scope or an incident. Close the two weakest dimensions first, then consider a narrow controlled pilot.
Clarity, data foundation, ownership, and oversight are sufficient to responsibly pilot or expand a defined AI initiative with human review in place. Move forward with measurement, human review, and active risk monitoring.
Readiness is strong and consistent across strategy, operations, data, governance, output trust, and adoption. Scale responsibly across aligned workflows while continuously monitoring value and risk.
The separation between engine and interpretation
The deterministic engine owns scores, readiness levels, dimension scores, Strategic Impulse risk, strengths, weaknesses, and the recommended implementation stage. A future AI interpretation layer, grounded in the Trust Score Constitution, will add deeper executive commentary in The Drill Down section of the results. It will interpret the results only. It cannot change or override any number.
Do not upload confidential, proprietary, regulated, or sensitive personal information into this assessment. Trust Score provides strategic readiness guidance and does not replace legal, privacy, security, regulatory, or compliance review.
Want the model applied to your specific initiative rather than in the abstract? Request a 1:1 review