AI strategy and discovery
Most AI programmes stall because they start with tools. Ours starts with where value and readiness meet: a published method, run with your own people, that turns a wide field of ideas into a small set of use cases the business trusts.
You will recognise the moment. Competitors are announcing AI initiatives. Staff are already using ChatGPT or Claude on personal accounts because the company has not decided what to allow. A pilot or two has run and nobody can say what it changed. The leadership team agrees AI matters and disagrees, or stays silent, about what to do.
This is the point at which a shared vocabulary, a structured discovery process and a readiness-sequenced roadmap pay for themselves many times over. It is where we start with most clients, from a global industrial group to a national magazine publisher.
They run in sequence as a full programme, or individually. Every engagement is scoped and fixed before it starts.
One day on site, two days of tailoring
A half- or full-day session for your leadership or functional teams that builds a shared understanding of AI, grounded in your sector: the inflection point, the competitor landscape, the AI Opportunity Pyramid, the four levels of AI, and the regulatory map.
Four to ten workshops over four to twelve weeks
Divergent workshops to surface every idea in each function, then convergent workshops where pre-clustered, pre-scored ideas are challenged and force-ranked by the people who do the work. Every idea captured, scored and traceable.
Included in a full programme, or standalone
Ideas sharing a capability are consolidated into single, submittable use cases, written in your own investment format, assigned an adoption pathway, and sequenced into a roadmap grouped by readiness, with a recommended first quarter.
Two to four weeks alongside a rollout
A governed-access model that replaces blanket blocks with sanctioned tools on no-training terms; responsible-AI principles; risk classification added to your existing evaluation template; and the AI-literacy plan the EU AI Act has required since February 2025.
250Ideas captured in our last full programme
27Consolidated use cases, ready for investment assessment
~70People across ten workshops in five functions
A full programme produces a findings report that stands up to scrutiny: every idea captured with the pain it addresses, how the work is done today, the AI capability it calls on and who benefits; the scored clusters per function; the appetite-versus-readiness view; the consolidated use cases, each with problem, opportunity, value, cost and complexity, data position, risks and candidate vendors; the four adoption pathways assigned; a roadmap grouped into ready now, nearly ready, strategic and research; and a recommended first quarter.
The scoring is our straw man, calibrated in the room; it is not an external verdict imposed on the business. Where you have an existing investment or technology-assessment process, the use cases are written so they drop straight into it without rework.
How Enceladus ran the full Converge Methodology across five functions of a global drives manufacturer: ten workshops, close to seventy people, 250 ideas consolidated into 27 prioritised use cases, and a readiness-sequenced roadmap with a first quarter the business could start on.
Equipping senior leadership at a global industrial motor control leader with a shared understanding of where AI can practically create value.
A readiness assessment scores your organisation against a generic maturity model. Discovery produces your own prioritised use cases, with the data position of each, so the output is a roadmap rather than a grade. We do assess readiness, but per opportunity, which is where it decides anything.
We maintain a landscape of over a hundred AI vendors across twelve functional areas and name candidates for each use case. They are candidates identified by market research, not selections; vendor choice belongs in your assessment process, and we hold no reseller relationships that would bias it.
It usually is not, for the most ambitious ideas; that is the most common finding of every programme. The method is designed for it: data- dependent use cases enter a research or data-foundation pathway first, while the data-in-hand opportunities proceed now, so the first quarter shows visible value while the foundations are laid.
Every engagement is scoped and its price fixed before it starts, so you know the cost before you commit. A leadership awareness session is a day on site with two days of preparation; a full discovery programme across five functions runs eight to twelve weeks. Tell us where you are and we will come back with a scope and a fixed price.
Yes. Our engineers build the knowledge assistants, support agents and workflow automations the roadmap identifies, and we run governed rollouts of the enterprise tools. We say plainly which use cases should be bought rather than built.
Half an hour is enough to tell you whether an awareness session or discovery is the right first step.