Our method
The Consultaix AI Adoption Ladder™
A proprietary framework developed from direct research into AI adoption in SMEs and small-island economies. Four rungs, five dimensions. It gives a defensible, evidence-based answer to "where are we, and what's next", not a consultant's opinion.
Place yourself to see what each rung measures.
Four rungs. Choose the one that sounds most like your organisation today. The panel opposite shows what an Assess engagement scores at that rung across the five dimensions, and what has to be true to move up one. Most organisations sit on different rungs for different dimensions, which is why the full assessment reports a profile rather than a single score.
The five dimensions we measure
The matrix
Every rung, every dimension.
An organisation rarely sits on the same rung for every dimension. An Assess engagement reports the profile, and the roadmap addresses the lowest rung first.
| Dimension | AwareAI is on the agenda. Nothing is owned or funded. | ExploringIndividual experiments. No policy, no shared data. | AdoptingA funded use case is live. Capability is concentrated. | ScalingA governed portfolio with measured outcomes. |
|---|---|---|---|---|
| StrategyIs there a decision, and who made it? | AI appears in board discussion. No stated objective ties it to a business outcome. | Interest is bottom-up. Leadership tolerates experiments without directing them. | One use case has a named sponsor and a target. The rest of the organisation is not in scope. | AI priorities are set against the business plan and reviewed on a cycle. |
| GovernanceWho is accountable, and for what? | No policy. No view on where AI is already in use through vendors. | Staff use public tools with company data. Risk is unrecorded. | A draft policy exists. Responsibility sits with the sponsor of the live use case. | Policy, risk register and review cadence are in force and align to local regulation. |
| DataCan the organisation feed a model? | Data is not inventoried. Access is by request to whoever holds the spreadsheet. | Data is located but quality, ownership and consent are unknown. | The live use case has a clean, owned dataset. Everything else is as before. | Data ownership, quality checks and access rules are standard across functions. |
| CapabilityWho can actually do the work? | No one in the organisation has run an AI project. | A few enthusiasts. Skills are personal, not organisational. | Delivery depends on two or three people, or on an external vendor. | Capability is distributed across functions with a plan for keeping it current. |
| ExecutionIs anything in production, and does it hold? | Nothing in production. | Unfunded pilots that stop when the enthusiast is busy. | One use case in production. Adoption measured informally, if at all. | Multiple use cases live, with adoption and outcome metrics reported to leadership. |
Move the cursor across a column to read one rung end to end.
Definitions
What the Ladder measures, and what it does not.
What is AI readiness?
AI readiness is the degree to which an organisation can absorb AI and sustain value from it: whether a decision on AI has been made and owned, whether accountability and risk are governed, whether the data can feed a model, whether people can do the work, and whether anything is in production and holding. The Ladder scores each of those five dimensions separately.
AI readiness versus AI maturity
Maturity describes how far an organisation has travelled with AI. Readiness describes whether it can take the next step. A company can be mature in one function and unready everywhere else, which is why the Ladder reports a profile across dimensions rather than a single maturity score. Readiness is the question to assess first, because maturity is what you get afterwards.
Why it was built for SMEs and small economies
Global maturity models assume a data team, a compliance function and a market of specialist suppliers. Most Mauritian organisations have none of those, and neither do most organisations in other Small Island Developing States. The Ladder was developed from doctoral research on AI readiness in Mauritian SMEs and treats those constraints as the starting point.
Next step
Find out where you stand.
An Assess engagement scores all five dimensions, places you on the Ladder with evidence, and gives you a prioritised roadmap.
See the readiness assessment Talk to usFurther reading: What data does a non-technical organisation need before it starts with AI?, An AI governance framework for a 20 to 200 person organisation, Your staff are already using generative AI. A 30-day plan for managers.
Further reading: What data does a non-technical organisation need before it starts with AI?, An AI governance framework for a 20 to 200 person organisation, Your staff are already using generative AI. A 30-day plan for managers.
Further reading: What data does a non-technical organisation need before it starts with AI?, An AI governance framework for a 20 to 200 person organisation, Your staff are already using generative AI. A 30-day plan for managers.
Related services: AI governance, AI implementation, AI training and change management.