
The five levels of AI readiness — and why most companies are at level two
Before choosing a use case, know where your data, processes and people actually are.
Read more →A structured assessment of data, processes, skills and governance, producing a maturity level, a prioritised list of use cases and the pre-requisites for each.
Maturity assessment (5 levels)
Data and systems review
Use-case workshops with business teams
Prioritised backlog with value / effort
Risk and governance requirements
Roadmap for the first two pilots
Mandate to “do AI” without a defined problem.
Documents scattered, no single source of truth.
Demos that never reach production.
Where a human must stay accountable.
Five-level maturity map, data and process review, prioritised use cases.
Scope, data set, owners, guardrails and acceptance criteria.
Run in parallel with the current process; measure quality and time.
Roll out with training, monitoring and a governance cadence.
Admin dashboards, programme reporting and planning data for public bodies and agri-trade.
E-commerce, cross-department ERP, AI assistants and field apps for tour operators.
Newsroom CRM, Telegram AI bots and content operations for media teams.
Membership academies, learning platforms and training programmes.
MVPs, internal tools, market research and go-to-market for tech teams.
Industrial IoT, monitoring and forecasting — capability profiles and pilots.
3–5 weeks including workshops.
Yes — it recommends use cases, not tools.
The roadmap then starts with data and process work; that is a valid outcome.
A short online self-assessment is available on our AI Studio site.
Bring us the problem nobody on your team has time to own. We will scope it, price it and start with a pilot you can measure.

Before choosing a use case, know where your data, processes and people actually are.
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