Make AI Decisions Visible And Accountable.

Determines which decisions are worth optimizing, which are distractions, and where leadership believes priorities are aligned when they are not

Examines how AI-mediated interfaces sit between people and systems, interpreting intent, presenting recommendations, and shaping real business decisions before execution.

Examines how predictive modelling influences forecasting decisions, where signal value decays, and how forecasts are trusted or overridden in practice.

Assesses how AI-informed decisions are executed across systems, workflows, and teams, and where execution diverges from intended outcomes.

Assesses where AI-driven decisions are trusted, where humans intervene or override outputs, and how those behaviors affect outcomes, risk, and accountability.

Assesses whether AI-influenced decisions have explicit ownership, whether risk is visible at the moment of commitment, and whether accountability is defensible when outcomes are challenged.