open-ai-transformation-maturity-model

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Getting Started

If you’ve just landed here and aren’t sure where to begin, this page is meant to point you in roughly the right direction. You don’t need to read everything in order. Most people don’t.

Pick the path that matches why you’re here.

Quick Start (Leadership Teams)

If you’re trying to understand what this means for the organization as a whole:

  1. Read (or at least skim) the 5-Level Maturity Model
  2. Look at the Assessment Framework to see what gets evaluated
  3. Run a short self-assessment session — even a rough one is useful
  4. Agree on where you actually are today (this part can get… lively)
  5. Identify a few realistic next steps instead of a massive transformation plan

Quick Start (Practitioners)

For engineers, architects, delivery leads, etc.:

  1. Read the level definitions properly — details matter here
  2. Check the scoring guide so you know how maturity is judged
  3. Map your current practices against the seven pillars
  4. Figure out what’s slowing you down the most
  5. Suggest specific improvements rather than vague “we should use more AI” ideas

Quick Start (Researchers)

If you’re looking at this from an academic or analytical angle:

  1. Review the assumptions behind the model
  2. Compare it with other maturity frameworks
  3. Share data or case studies if you have them
  4. Challenge anything that doesn’t seem to hold up

Suggested Workshop Flow

Most organizations end up doing something like this:

Don’t treat this as a script. Every group does it differently.

Important Note

Higher maturity is not automatically better.

In some contexts — especially regulated or safety-critical ones — moving too fast can backfire. Progress only makes sense if your architecture, governance, and testing capabilities can keep up.

Where to Contribute

If you want to help improve the project:

If you’re unsure where to start, opening a discussion is perfectly fine.


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