AI strategy and discovery
A half- or full-day session for boards, leadership teams and functional heads, tailored to your sector, that replaces hype and vague unease with a common vocabulary, a clear view of what competitors are already doing, and a frame for deciding where AI belongs in your business.
By the time a leadership team asks us in, the question is rarely whether to use AI. It is where AI could deliver real commercial and operational value, how to tell deployable AI from hype, what competitors are embedding at scale, how to adopt it within regulatory and governance constraints, and how it fits the evaluation frameworks and data the business already has.
The session is built to answer those questions for your sector and your business, and to leave the room with a shared mental model that makes every later AI conversation shorter and better. It is the first phase of the Converge Methodology, and the one most clients start with.
A half-day version covers the first four parts.
Why 2025 to 2026 marks a structural shift from experimentation to enterprise deployment: transformer architectures, compute at scale, internet-scale data and sustained investment rather than cyclical hype. What the adoption and productivity numbers actually show, and the 80% of organisations not yet seeing enterprise-wide impact.
Machine learning, large language models and what changed with transformers, explained in engineering-familiar terms. Generative AI as one branch of a wider toolkit alongside classical machine learning, computer vision, optimisation and digital twins, which in industrial settings often return faster.
One scenario from your own business shown as a copilot, an assistant, an agent and an agentic system, so the shift from AI that assists people to AI that owns governed outcomes becomes concrete.
Four layers of time-to-deploy, from off-the-shelf copilots to embedded and bespoke AI, used live to place the opportunities the room raises. The frame the rest of the programme hangs on.
A researched landscape of how your peers are deploying AI: copilots for engineers, predictive maintenance, embedded intelligence, agentic supply-chain operations, or the publishing, retail and agency equivalents. AI reframed from future roadmap to current competitive baseline.
Over a hundred AI vendors evaluated across twelve functional areas, from productivity and knowledge management to manufacturing, sales, finance and legal, drawing on analyst research and market intelligence, and marked against what you already own.
The EU AI Act's risk-based framework and what it means for UK businesses; the five responsible-AI principles; sector-specific considerations such as safety-critical AI, IP protection and workforce impact; and how AI assessment slots into the governance structures you already have.
Where the opportunities the room raised sit on the pyramid, what the sensible first quarter looks like, and how discovery would take the conversation from "should we?" to "where, and how?"
Two days of preparation go into every session: researching your competitors' AI announcements and deployments, mapping the vendor landscape to your functions, choosing the scenario for the four-levels exercise, and reading up on your governance and evaluation processes so the session speaks your language. For an industrial manufacturer that meant competitor intelligence on Siemens, ABB and Schneider Electric and a quote-configuration scenario; for a magazine publisher, editorial, subscription and advertising use cases and the online-versus-print distinction.
Participants leave with the materials, the vendor landscape and a one-page summary of the opportunities raised, placed on the pyramid.
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.
Full day or half day on site, with two days of sector tailoring beforehand and the materials, vendor landscape and one-page opportunity summary to keep afterwards. Travel within the UK included. Scoped and fixed before it starts.
The leadership team for the main session: directors and functional heads, typically eight to fifteen people. A second, functional session for the wider management group is a common follow-on and sets up discovery.
It is leadership AI literacy, which is one kind of training, and it meets the EU AI Act's literacy duty for the people in the room. It is not tool training; that comes with the rollout.
No. The session is designed for teams at the start, including those whose only AI use so far is unofficial. Teams further along use it to align a leadership group that has moved at different speeds.
Most clients move into discovery workshops across their functions, or straight to a governed tool rollout where the session has shown that access is the blocker. Some simply use the shared vocabulary and the pyramid to run their own prioritisation.
It can, but the full-day version works best in a room. The four- levels exercise and the pyramid placement rely on discussion.
One day, tailored to your sector, with the artefacts to keep.