Every AI consultancy names a framework. Almost none shows one. We publish the Converge Methodology in full, with its artefacts, because a method you can inspect is one you can trust, and because the value is in the running of it, not the secret.
The deliverable at the end of discovery is a document, so here is what a good one contains, section by section, and the questions to ask of a consultancy's sample before you commission one.
Two hundred ideas is not a submission list. Why ideas that share a capability are consolidated into single use cases, how "one licence, many benefits" changes the economics, and what a submittable use case contains.
The first half of discovery is about breadth, not judgement: every idea, however small, captured with its pain and its current process. How we run the room so the people who know where the time goes actually say so.
Comparing AI ideas fairly needs one scale. These are the ten elements we score every idea on, what each one is really asking, and why the scores are offered as a straw man for the business to correct.
Plot how many ideas each AI theme attracts against how ready its data is, and the picture is uncomfortable: the two point in opposite directions. Why that is, and how to run a roadmap that respects it.
Research-led, product-led, system-embedded and data-foundation: every AI use case reaches deployment along one of four pathways, and treating them all as a licence to switch on is why AI programmes disappoint.
The tools for most AI opportunities already exist. What decides whether an opportunity can be delivered, and when, is whether the data it depends on exists in a usable form. How we assess it, and why it means sequencing by readiness rather than enthusiasm.
The words are used interchangeably, which is why AI conversations go in circles. One scenario shown at four levels makes the shift from AI that assists people to AI that owns outcomes concrete, and tells you which level each use case should reach.
A simple layered view of AI opportunities by time to deploy, why it stops programmes stalling, and how to use it alongside priority scoring.
What actually happens in an AI discovery programme, step by step, from the first divergent workshop to a roadmap the board can fund, using our most recent full programme as the worked example.