From AI uncertainty to a prioritised, governed roadmap — in two structured days. No vendors in the room. No hype. Every AI commitment has a name next to it.
Your leadership team has sat through vendor demos. Someone’s built a business case. Three departments are running pilot projects nobody else knows about. Meanwhile, the board keeps asking for “the AI strategy” and getting a slide deck full of buzzwords.
The gap isn’t knowledge — it’s alignment. Your team can’t agree on which AI use cases are worth pursuing, how to govern AI responsibly without killing momentum, who owns AI decisions, or where to invest first.
Each phase is time-boxed, produces a written artefact, and builds on the one before it.
Surface everything your organisation is already doing with AI — the official projects, the shadow experiments, the vendor conversations. Map these against your strategic priorities. Identify the gaps between what you’re doing and what actually matters.
Generate AI use cases using structured ideation — silent-first to prevent anchoring, then collaborative to build on each other’s thinking. Every use case must be expressed as a business outcome, not a technology feature. “Reduce customer onboarding time by 40%” not “implement an LLM chatbot.”
Score every use case against a structured framework: strategic alignment, implementation feasibility, data readiness, risk profile, and expected ROI. This is where “we should do AI in marketing” becomes a ranked, evidence-based portfolio. The Decider selects the top 3-5 use cases.
Build the governance framework: who approves AI deployments, how you manage data and ethics, what your escalation path looks like. Assign named owners to the top use cases. Create the 90-day plan with decision checkpoints — not a 12-month strategy that will be obsolete by month 3.
Every use case is evaluated against your business priorities, not a platform’s feature list.
The best AI ideas aren’t coming from the loudest voice — they’re from the operations lead who’s watched the same process fail 200 times.
Use cases are framed as measurable outcomes, not technology features. This prevents solution-in-search-of-a-problem thinking.
Most organisations build governance after something goes wrong. You build it on Day 2, before a single model is deployed.
Every exercise has strict time limits. No drifting into “but what about blockchain” tangents.
Every sprint ends with a documented decision log, named owners, and a 90-day plan. No working groups.
The full AI Design Sprint with space for deeper exploration between days.
| Time | Activity | Duration |
|---|---|---|
| 09:00 | Welcome, context setting, ground rules | 15 min |
| 09:15 | AI landscape pre-work review and discussion | 30 min |
| 09:45 | Map the Landscape — Current AI initiatives, gaps, strategic alignment | 75 min |
| 11:00 | Break | 15 min |
| 11:15 | Discover Use Cases — Silent ideation, collaborative development, business outcome framing | 90 min |
| 12:45 | Lunch | 45 min |
| 13:30 | Evaluate & Prioritise — Scoring framework, ranking, Decider selection | 120 min |
| 15:30 | Break | 15 min |
| 15:45 | Milestone 1 review and Day 2 preparation | 30 min |
| 16:15 | Close Day 1 | — |
| Time | Activity | Duration |
|---|---|---|
| 09:00 | Day 1 recap, overnight reflections | 15 min |
| 09:15 | Governance Framework — Risk appetite, data governance, ethical guardrails, accountability | 90 min |
| 10:45 | Break | 15 min |
| 11:00 | Ownership & 90-Day Roadmap — Named owners, success metrics, decision checkpoints | 75 min |
| 12:15 | Lunch | 45 min |
| 13:00 | Roadmap refinement and resource planning | 60 min |
| 14:00 | Milestone 2 — Governance agreed, roadmap owned | 10 min |
| 14:10 | Break | 10 min |
| 14:20 | Executive summary and board-ready narrative | 40 min |
| 15:00 | Commitments review, next actions, close | 30 min |
| 15:30 | Close | — |
Every idea generated, evaluated, and ranked by business impact and implementation feasibility.
A practical one-page framework covering risk appetite, data governance, ethical guardrails, and accountability.
Top 3-5 use cases with named owners, success metrics, resource requirements, and decision checkpoints.
Your team leaves with shared vocabulary and the ability to evaluate AI proposals critically.
Every choice documented with rationale, owner, and timeline — the Echelon standard.
A structured summary you can take directly to your board or investors.
CEO or most senior decision-maker. Has final authority at every decision point. Must be present for the full sprint.
5-14 leaders across functions — strategy, operations, technology, finance, HR. Cross-functional perspective is essential for AI prioritisation.
Echelon’s neutral facilitator. Guides the process, prevents vendor bias, ensures decisions land.
All four phases in a single intensive day. Best for teams with a clear AI ambition who need to align and prioritise fast.
Deeper exploration with overnight reflection. Space for governance design and board-ready narrative.