A four-day workshop to redesign a workflow around AI so it delivers real business impact. A cross-functional team discovers how the work really runs, redesigns it, and tests a working prototype with the employees who will use it, ending with a scale, iterate, or stop decision backed by evidence.
AI projects usually start from the workflow as it exists. The team picks a step and automates it, workarounds, legacy steps, and unnecessary approvals included. Everything around that step stays the same, so the gain disappears at the next handoff.
And because the workflow was built around how people work today, the bigger opportunity never comes up. For the people doing the work, the only change is one more tool to fit around the old process, so they keep working the way they always have.
The organizations getting real value do the opposite. They redesign the workflow around what AI can do, then adapt the roles to fit the new way of working.
The AI Workflow Sprint is built for teams with a specific AI use case and a deadline to show results.
The workflow crosses teams, systems, and decision rights, like quote-to-order, claims, or onboarding.
You have to show measurable business value from AI, in numbers the business already tracks.
An AI pilot sped up one step, but cycle time, cost, and quality barely moved.
You're moving to AI agents that can handle whole sequences of work, and the old step-by-step process no longer fits.
A cross-functional team of 6–8 stakeholders maps the workflow as it actually runs today: the broken handoffs, the steps that belong to nobody, the decisions made on instinct. Then the team decides whether to improve the workflow or rebuild it from a clean sheet, before any AI is added.
The team defines success metrics, maps risk across different dimensions and designs the solution. The day closes with a storyboard: a frame-by-frame blueprint of how the AI will work with the employee.
A focused trio — AI engineer, UX designer, and subject matter expert — builds a working AI prototype from the storyboard. Real enough for an employee to sit with it and say whether it changes the way they work.
Five structured interviews with employees who do the work. What they say and do with the prototype informs the decision to scale, iterate, or stop.
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By the end of day four, the team has a redesigned workflow with clear roles for people and AI, a working prototype tested with five employees who do the work, and success metrics to measure impact once it's live. The research results show whether to scale, iterate, or stop.
That's what you take to your leadership: a new way of working, with the evidence to stand behind it.

Most teams start here: one real workflow, redesigned and tested in four days.
You bring the domain knowledge and the business context. DSA facilitates all four days: we get the right people involved, help the team see how the work really runs, and guide them through redesigning it around AI. The team leaves with a new way of working and the evidence to act on it.
Four days · 6–8 participants · On-site

Your people learn to guide a team through the AI Workflow Sprint, practicing on a real workflow from your own work. We tailor the training to the team and its context. Every participant leaves with the Playbook, Facilitation Slides, Agendas, and Worksheets, ready to lead the next workflow redesign.
Two days · Up to 15 participants · In-person at your organization

Experience the method before you bring it to your team. At the AI Facilitator Training in Berlin, you run AI Problem Framing and the AI Workflow Sprint over three days with practitioners from other companies. You leave with the full Facilitation Toolkit and a clear picture of how the method would work in your context.
Three days · Up to 8 participants · In-person in Berlin
How the AI Workflow Sprint works in practice — and what we’ve learned running it with teams across the globe.
