AI readiness and transformation planning
Choose the right first project before committing to an implementation.
Why it matters
Most AI programmes fail before they start, by choosing a first project that is too broad, has no owner, or depends on information nobody is allowed to use. A short, structured assessment removes those failure modes before any engineering money is spent.
Who this is for
Business leaders who need a practical view of where AI can improve a process, what their data can support, and who should own the change.
What we do
- Interview process owners and map the current workflow, hand-offs and recurring exceptions.
- Review available data, existing systems, access permissions and integration constraints.
- Rank candidate use cases by business value, feasibility, operational risk and readiness.
What you receive
- Current-state process map with baseline measures.
- Prioritised use-case shortlist with a recommended pilot.
- Implementation brief covering scope, ownership, dependencies and acceptance criteria.
How it runs
Discover
Agree the business question and meet the people doing the work.
Assess
Test assumptions against sample tasks and authorised information.
Plan
Define a bounded pilot, responsibilities and a review point before expansion.
Who you will work with
A delivery manager leads the assessment with a forward deployed engineer who sits with your process owners and looks at the real systems and data, not slide descriptions of them.
An example
A regional insurer wanted to “use AI in claims”. The assessment mapped four claims workflows, found that two depended on scanned documents nobody had rights to process, and recommended a bounded pilot on first-notice triage with a named claims manager as owner. (Illustrative example.)
Questions
What should we prepare?
Do we need to replace our systems?
Start with one workflow.
Tell us the process, the people who run it and what you would like to change. We will suggest the right first conversation, with no obligation.