Applied AI engagement
AI value discovery
Decide where AI is worth pursuing before anyone builds anything. A short engagement that ends with a prioritised portfolio of opportunities, each with a value hypothesis, a measure and a recommendation to proceed, reshape or stop.
The problem
Most organisations have a list of AI ideas and no reliable way to rank them. The list is usually technology-led, so the first project is the easiest demo rather than the most valuable change.
Target outcome
A ranked set of opportunities that leadership can fund with confidence, each tied to a business measure and a baseline.
When this engagement fits
Value discovery is the right first step when you have more ideas than evidence. It fits when a leadership team wants an AI programme but does not yet agree on what it is for, or when an earlier pilot produced a demo and no decision.
It is the wrong step when you already have one well-defined problem with an owner and a measure. In that case go straight to a proof of value.
What we do
We interview the people who do the work and the people accountable for its results. We map the workflow as it actually runs, including the exceptions and the workarounds. For each candidate opportunity we write down the decision or step that would change, the measure that would move, and the baseline today.
We then review data readiness, integration dependencies, security and regulatory constraints, and the operating change each opportunity would require. The result is a ranking that reflects value, cost, risk and time to evidence.
What you receive
A short written portfolio. Each entry states the value hypothesis in one sentence, the measure and baseline, the delivery options, the dependencies, the risks and a recommendation. The recommendation is one of three words: proceed, reshape or stop.
Decision gate
Discovery ends with a leadership session. For each opportunity you decide whether to fund a proof of value, change the scope, or close it. Nothing proceeds without a named owner for the measure.
FAQ
Questions people ask
How long does value discovery take?
Typically three to six weeks, depending on how many workflows are in scope and how quickly we can reach the people who run them.
Do we need clean data first?
No. Part of discovery is finding out what data exists and how usable it is. Data readiness is an input to the ranking, not a precondition.
Will you recommend specific AI products?
Only where a product choice changes the economics of an opportunity. The output is a decision about where value is, not a vendor shortlist.
Start with the outcome