A model for AI adoption built around identity, not tooling — because the thing that stops capable people from going further is rarely a skill gap. It's a self-concept gap.
This repository is the canonical source for the model. Every AI Tutorium playbook that references "the six stages" links here rather than copying it, so there's one version, maintained in one place.
Last reviewed: 2026-07-24. See sources and verification notes.
- Who this is for
- The six stages
- Start here: locate yourself
- Where this came from
- Scope
- Related resources
- How to cite
- Free vs done-with-you
- Part of a series
- Professionals trying to work out why they've stalled, when they've clearly got the capability.
- Leaders and L&D teams who've run the training and bought the tools and still can't explain why adoption is uneven.
- Anyone building an adoption programme who wants a diagnosis that goes deeper than "give them another course."
If you've ever thought I know enough — I'm just not sure I'm the one who does this, this model is about you specifically.
Sorted by internal experience, not tools deployed:
- Nomad — defensive. "Why now, and why for someone like me?"
- Observer — curious but stuck. "Is it safe to start?"
- Dabbler — excited but inconsistent. "Is the investment worth what I'll get back?"
- Integrator — quietly confident. "What could I build with this, for other people?"
- Architect — restless but hesitant. "Do I actually believe I'm the kind of person who does this?"
- Innovator — building outward. "What's broken in my field that nobody fixes?"
The gap that matters most isn't Stage 1 to Stage 6. It's Stage 4 to Stage 5 — and it has almost nothing to do with skill.
📖 Read the full spec: framework/the-six-stages.md
The stage locator is a two-minute self-assessment. Pick the statement you recognise before you've finished reasoning about it — that's usually your stage, and it tells you what's actually holding you (which is rarely what you'd guess).
This isn't a whiteboard model. It comes from years of building and delivering AI training and adoption work — including an AI literacy programme built for small businesses and a multi-session AI programme for a national ministry team — and from watching the same pattern surface across roles and sectors: many people who stalled were not simply short on skill. They were waiting for permission.
The stages describe that pattern. The Architect stage, in particular, names a transition that tool-maturity models often underplay: the move from using AI for your own work to building something useful for others.
The model is practitioner-built. It is useful for reflection, facilitation, and adoption design; it is not a validated psychometric instrument. Evidence boundaries and related references are listed in sources.md.
Use this model to start better conversations about AI adoption, not to label people permanently. A person's stage may differ by task, tool, role, confidence, risk level, organisational culture, and available support.
This repository does not provide legal, HR, procurement, data-protection, psychological, or regulated professional advice. Pair it with appropriate governance and risk guidance when using AI in an organisation.
- AI Adoption Playbooks
- AI Adoption Toolkit
- AI Adoption for Leaders
- AI Adoption for Professionals
- AI-Era Data & Privacy Playbook
- AI Governance Kit
Please do — that's what the CC BY licence is for. See CITATION.cff for the structured citation, or use:
Osondu, V. (2026). The Six Stages of AI Adoption: a model built around identity, not tooling. AI Tutorium.
Permanent archive (DOI). Each tagged release of this repo is archived on Zenodo, which mints a permanent, versioned DOI. Cite the DOI when you need a stable, dated reference — it's the version-of-record and won't move if the repo does. The DOI badge above links to the latest archived version once the first release is published (see RELEASING.md).
The model, the locator, and everything in this repo are free to use, adapt, and cite under CC BY 4.0.
If you want help applying it inside an organisation — mapping your team, designing a rollout that meets people at the right stage, or the compliance and certification layer on top — that's what AI Tutorium does as paid work. The framework is the free part. The done-with-you delivery is the service.
This is a reference asset in the AI Adoption Playbooks series. The index — with the audience playbooks (SMB, education, ministry, leaders and more), the toolkit, and related work — lives at ai-adoption-playbooks.
"Every expert in AI was once a beginner who decided to start experimenting."
Maintained by Victor Osondu, Founder, AI Tutorium. Corrections and translations welcome — see CONTRIBUTING.md.