The methodologies behind the work.
Five frameworks, applied across government infrastructure, enterprise AI deployments, and multi-jurisdiction governance programmes. Each is published here as a working reference, not a marketing summary — open one to read the full methodology.
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How to Prevent Enterprise AI Disasters
01Five-Dimension AI Readiness Assessment
Five operational dimensions, scored 1–4, that predict AI deployment failure before any budget is committed. A single low score blocks the initiative regardless of the others.
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02TRACE Framework
Five pre-deployment checks for whether a task is structurally appropriate to hand to an AI agent, before architecture or vendor decisions are made.
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03Four-Question AI Governance Baseline
Four diagnostic questions that expose structural governance gaps before deployment, not after an incident. The same four questions regardless of scale.
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04Return on Employee (RoE) Framework
Measures AI value through the increase in productive capacity per person, replacing headcount reduction as the default (and misleading) business-case metric.
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05Measurement-Before-Prediction Architecture
A five-step sequence for designing the measurement schema before data collection begins, so AI predictions don’t require months of recalibration after go-live.
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