Assessment & Measurement

Two tools for turning the Data Readiness framework into action: a diagnostic that tells you where you actually stand, and an economic model that tells you what inaction costs.

The AI Readiness Assessment Framework is a structured scoring session across seven dimensions (Data, Governance, Infrastructure, Talent, Process, Risk & Compliance, and Strategy & Culture), each rated 1–5 on evidence rather than stated intent. The output is a prioritized gap list — not a score to report upward, but a specific sequence of investments with a rationale you can defend. Use this to kick off a readiness program or to reorient one that has stalled.

The Total Cost of Data Debt quantifies what poor data readiness is already costing, and what it will cost as AI deployment scales. It provides a four-category debt framework and the financial formulas to turn gap findings into dollar figures. Use this to build the investment case once the assessment has identified the binding constraints.

In this section

Page	Last updated
AI Readiness Assessment Framework A use-case-first check for whether an AI initiative needs readiness work, plus an optional seven-dimension lens for organizations planning a portfolio at once.	Updated 2026-07-03
Total Cost of Data Debt How to quantify the accumulated cost of deferred data quality work in financial terms leadership can act on, and frame the investment case for fixing it.	Updated 2026-06-12