Lead cross-functional teams to the decisions that matter: which AI use case is worth building, then how to build and validate the new workflow around it.
The AI Problem Framing Kit helps you guide a team to one AI use case they can stand behind — in a day. The AI Workflow Sprint Kit helps you build and validate the new workflow around it — in four.
You're stepping into the role every organization is about to need - the AI Orchestrator - the connective tissue that drives AI work with cross-functional teams making AI adoption stick.
Align a divided team on one shared decision.
Steer the team toward AI use cases worth the business's money — and their time.
Guide the team to redesign how the work gets done around AI.
Help the team validate an AI agent with the people who'll actually use it.
Own a framework that works for any AI workflow, in any industry.
Win repeatable client work — especially in highly standardized industries.
Not for lack of ambition, or tools. For lack of a clear way to decide. Organizations still don't have a path for making decisions around AI.
Leadership has ambitions. Teams have different definitions of what “good” looks like. Employees are skeptical about new ways of working. Progress is slow, and the ROI is nowhere.
This gap doesn't close on its own — and it doesn't close by doing more of the same. More AI pilots. More licenses. More people trained to prompt and vibe-code. None of that decides what's actually worth building.
It closes when cross-functional teams come together to make AI decisions as a team — when they look at the whole system and redesign the work around what AI can now do.
Someone has to bring those teams together and guide them there. That's the AI Facilitator.
A facilitator producing strategy-grade outputs at the speed of a workshop.
Someone has to bring the right people together and guide them there. You'll see the role under different titles — AI Champion, AI Adoption Manager, AI Transformation Lead — but the job is the same. Here's what it looks like, start to finish.
Sit down with leadership and gather the areas where AI could actually move the business. Turn a broad mandate into a shortlist of opportunities worth exploring.
Pull together a temporary, cross-functional team — product, IT, legal, data, operations — assembled for one purpose: to make the decision or solve the problem, then disband.
Guide the Pod through the right session for the decision at hand.
Capture what was decided and what changed, and bring the results back to leadership — so the next decision starts from evidence, not opinion.
You're sitting on a pile of AI use cases with no way to rank them. Or you just got handed an AI session to lead — and you've never run one like it.
Either way, you're the one who now owns the room where AI decisions get made: a facilitator, consultant, AI champion, or adoption or transformation lead.
A general workshop is judged by the session — energy, ideas, engagement. AI facilitation is judged by what's left after: the quality of the decision, the team's commitment to it, a workflow actually redesigned around AI, and an agent MVP validated with real users. Against that bar, some of the moves facilitators rely on quietly work against you.
Loose worked when ideas came one at a time. AI floods the room with more than anyone can read, and a loose session has no way to sort signal from noise. You end with energy and no decision.
Those surface ideas. An AI decision needs more: is it wanted, can you build it, is it safe — weighed together, in one call. The old tools were never built to get you there.
Engagement isn't commitment. People nod in the session and quietly opt out of the new workflow later. Commitment comes from how the decision gets made — not how good the room felt.
An AI workflow isn't the old workflow plus a model. Redesign the work around what AI changes, or you ship a slower version of what you already had.
A demo proves it runs. It doesn't prove the people who'll use it will. Only an MVP validated with real users tells you that.
It's the opposite. Everyone arrives with their own AI answer, and they don't match. Your day becomes reconciling ten machine outputs into one call the team shares — that takes more prep, not less.
None of this is a talent gap. It's a method gap — and it's the one a structured method closes.
You don't waste time designing a new AI workshop format — we've done that for you. These methods come from ten-plus years of running Problem Framing and Design Sprints across the globe, with some of the biggest brands in the world.
ALEC Holdings trained its internal AI champions in Problem Framing and the AI Workflow Sprint, then handed them these kits to run the sessions themselves.
“Being an ALEC Innovation Champion comes with a responsibility to stay ahead — and this workshop reinforced exactly why we champion a culture of continuous learning and forward-thinking.”
You already run a strong workshop — that was never the question. What changes is what happens after the room: with a method, you own the decision, not just the discussion.
Here's what that's worth to you:
The math is simple: one AI engagement you win with this covers the Stack several times over. One bad pilot you kill early saves a client months.
A toolkit. No lessons to sit through, no cohort, no schedule. You get the complete method — playbooks, minute-by-minute agendas, 350+ slides, worksheets, logistics sheets — ready to run. It's built for facilitators who already know how to hold a room and want the AI-specific method in their hands. If you'd rather practice these methods and test them out first, we run the AI Facilitator Training in Berlin — an in-person program for a small, exclusive group of facilitators.
They're two decisions in sequence.
AI Problem Framing (1 day) gets a team to one prioritized AI use case they can stand behind.
The AI Workflow Sprint (4 days) takes that decision and makes it real: you redesign the workflow around the AI and validate a working agent with the people who'll actually use it.
Problem Framing decides what's worth doing; the Workflow Sprint builds it.
The Stack gives you both, so you can run the full path from question to validated workflow.
No. The AI Workflow Sprint redesigns how employees work — internal processes and workflows.
Customer-facing AI product work is a separate method, the AI Design Sprint, which isn't part of this Stack.
You can. It'll just take you a long time and a lot of trial and error. We started running these workshops with clients at DSA two years ago and refined them after every engagement — and the ten years of Problem Framing and Design Sprints we've run across industries and cultures are all embedded in this kit.
You can build that experience from scratch, or you can start from ours. Totally up to you.
No. You need enough AI fluency to follow the conversation, not to build the agent. This is a facilitation kit — for facilitators guiding decision-making and problem-solving. It isn't a kit for building with AI.
Yes, if you've run workshops before. Each kit includes the full script, slides, and agenda, so the structure is handled. If you've facilitated a discovery session, a design sprint, or any problem-solving workshop, you have the foundation — the playbook carries the AI-specific parts you haven't done before.
Yes. The method is industry-agnostic — it works for any context, any challenge, in any sector.
The clearest proof is construction, about as far from a tech setting as you can get: at ALEC, a Gulf construction firm, internal champions used these exact kits to take 45+ AI ideas down to six validated use cases. If anything, the method pays off most in highly standardized industries, where a repeatable way to decide is worth even more.
They're proven at enterprise scale. Turner Construction — one of the largest general contractors in the US, at 11,000 employees — used these methods to build an AI operating model that now runs on its own: 400+ AI applications built by their own people, and 70,000+ hours of annual capacity unlocked.
Underneath that sits a ten-plus-year track record of Problem Framing and Design Sprints run inside Google, the World Bank, HSBC, Adidas, SAP, and eBay. The kits package that same structure so you can run it yourself.
John and Dana Vetan, the founders of Design Sprint Academy. They're built from DSA's own client engagements — the same Problem Framing and Design Sprint work run inside organizations like Google, HSBC, eBay, SAP, and the World Bank — not theory, and not repackaged from someone else's framework. What's in the kit is what DSA actually runs in the room.
In person. Both the AI Problem Framing session (1 day) and the AI Workflow Sprint (4 days) are built to run in the room — the cross-functional alignment and hands-on redesign depend on people being together. They're designed for guiding a cross-functional group, not solo or one-on-one work.
Each sells on its own: the AI Problem Framing Kit is €499 , the AI Workflow Sprint Kit is €599 . The Stack bundles both for €897 — it saves €200 and gives you the full sequence from decision to validated workflow.
Every two months. These aren't static files — we're actively facilitating these workshops inside organizations, and every couple of months we fold the latest learnings from that live client work back into the kits. You keep getting the current version of the method, not the one frozen at your purchase date.