Overview
A structured framework for organizations navigating AI transformation — from strategy and governance through data readiness, workflow optimization, adoption, talent, and value measurement.
Organized into eight tracks plus a cross-cutting program layer. Each track contains a core framework, practitioner guides, and assessment tools.
How to Use This Resource¶
New to the topic → Start with the Executive Summary, then the Eight-Track Model.
Leading an AI program → Go to Track 01 (Strategy) and the Running the Program section.
Solving a specific problem → Jump directly to the relevant track.
Assessing your organization → Go to the Integrated Assessment in Running the Program.
Unfamiliar with a term → Check the Glossary.
The Eight Tracks¶
| # | Track | The core question |
|---|---|---|
| 01 | AI Strategy & Leadership | What are we trying to accomplish with AI, and how does it connect to how we compete? |
| 02 | AI Governance & Risk | How do we deploy AI responsibly, safely, and in compliance with regulation? |
| 03 | Data Readiness | Is the data that AI depends on accurate, accessible, governed, and fit for purpose? |
| 04 | Technology Architecture & Platform | Do we have a coherent AI platform, or a collection of disconnected point solutions? |
| 05 | Workflow Optimization & Automation | Which workflows should be redesigned with AI, and how do we do it? |
| 06 | AI Adoption & Culture | Are people actually using AI, and are they thinking differently about their work? |
| 07 | Talent & Capability Building | Do we have — or are we building — the competencies AI transformation requires? |
| 08 | Measurement & Value Realization | Can we prove AI is working, and are we using that signal to improve? |
Last updated: June 2026 · One Step Labs