design and test how work gets done with ai.
Take one promising AI opportunity from idea to evidence in four days.
The AI Solution Sprint brings business, users and technology together to redesign the work, build a prototype and test whether it delivers real business value.
Learn fast what works before you invest bigger.
the gap between ai opportunity and business IMPACT.
You’ve identified a promising AI opportunity with the potential to create real business value.
But a promising opportunity is not yet a solution that works in practice.
Before investing in building it, there are still important assumptions to test.
Can AI do what you need it to do? Is the right data available? How should people and AI work together? Will people adopt the new way of working? And will the redesigned workflow actually deliver the business outcome you are aiming for?
Too often, organisations start building before they have answers to these questions.
Requirements are defined, technical teams get involved and the solution enters the delivery backlog. The most important assumptions may only be tested weeks or months later, after significant time, money and scarce technical capacity have already been invested.
The challenge is not to build AI faster.
It is to learn faster what works, what doesn’t and what it takes to create real business impact.
AI solution sprint at a glance
WHAT YOU ACHIEVE
- Evaluate one important AI opportunity in four days, not months.
- Align Business and IT around one business outcome.
- Test a redesigned human + AI way of working.
- Gain evidence before committing larger investment.
WHAT YOU LEAVE WITH
- A redesigned human + AI workflow.
- A believable AI-enabled prototype or Agent MVP.
- Evidence from real users.
- Key assumptions, risks and constraints made visible.
- A clear decision: invest, adapt or stop.
IDEAL FOR
- A promising AI opportunity that needs fast validation.
- An important workflow with clear improvement potential.
- Business and IT teams that need to align.
- Leaders who want evidence before investing further.
LESS SUITABLE IF
- You have not yet identified your strongest AI opportunities.
It is a simple AI quick win that you can test without significant investment.
The right people from business and technology, the workflow owner and real users are not available to participate.
learn faster before you invest bigger
An AI Solution Sprint helps you test a promising AI opportunity before committing to further development.
In four focused days, business, employees and technology work together to redesign the workflow, build a prototype and test the most important assumptions with real users.
You keep the business outcome and end-to-end workflow in view. Instead of simply adding AI to the way work is done today, you challenge unnecessary steps, handovers and old assumptions and redesign the work around what is now possible.
The result is evidence, not just an idea.
You learn what works, what doesn’t and what needs to change before committing scarce technical capacity and larger investment.
In four days, you move from opportunity to evidence, with a clearer decision to invest, adapt or stop.
how does an ai solution sprint work?
An AI Solution Sprint is a focused four-day process to redesign and test how an important workflow or opportunity could work better with AI.
Business, employees and technology work together to move from understanding the current workflow to designing a better way of working, building a prototype and testing it with real users.
In four days, you move from opportunity to evidence about what works and whether it is worth investing further.
1. DISCOVER
Understand the desired business outcome, the people involved and how the work really happens today. Identify friction, waiting, handovers, repetitive work and key constraints.
2. DESIGN
Rethink the workflow around the desired outcome. Decide what people should do, where AI can add value and where human judgement matters.
3. BUILD
Create a believable AI-enabled prototype or Agent MVP that brings the new workflow to life without building a production solution.
4. TEST
Test it with real employees or users. Learn what works, what does not and what the evidence says about value, usability, feasibility and adoption.
The result: evidence to decide whether to SCALE, ITERATE or STOP.
Smart preparation makes the AI Solution Sprint count
Before the Sprint, we agree on the starting point: the selected AI opportunity.
We clarify the business outcome, workflow scope, workshop team and the evidence needed for a useful decision.
We gather what already exists: relevant goals and KPIs, workflow or process information, known user insights, available AI ideas, data and important technical, legal, security or compliance constraints.
Where useful, selected employees or users are interviewed beforehand. The aim is to arrive with enough context to spend the Sprint learning and making decisions, not reconstructing the brief.
Preparation typically starts with a short kick-off around one week before the Sprint.
who should be in the room?
A strong AI solution cannot be designed from one perspective. The Sprint brings together the people who understand the business, the work and the technology, so they can challenge assumptions and make decisions quickly.
Business / Decider
Owns the desired business outcome, makes trade-offs and decides what happens next.
Workflow owner and employees
Understand how the work really happens, including exceptions, workarounds, handovers and judgement calls.
AI / Technical expertise
Understands current AI capabilities, challenges feasibility and helps create the prototype or Agent MVP.
Data / Systems
Understands the relevant data, systems and integrations.
Risk / Governance
Brings legal, compliance, security, privacy or other constraints into the conversation early.
Facilitated by Jens Broetzmann
I guide the team through the Sprint, connect the different perspectives and keep the focus on moving from assumptions to evidence.
The exact team depends on the workflow or AI opportunity.
What matters is that Business, employees and technology work together from the start, rather than handing the problem from one function to another.
Does everybody need to join all four days?
No. The Sprint is designed to use people’s time where their expertise matters most.
Days 1 & 2 · Discover & Design
The full Sprint team works together to understand the workflow, challenge assumptions and design the new human + AI solution.
Day 3 · Build
A smaller build team takes over. Typically the Business or Workflow Owner works with the AI, Data and Tech experts to create the prototype.
Day 4 · Test
Testing can be led by one or two team members with real users. Other Sprint team members can join where useful.
Day 4 · Decide
The full team comes back together to review the evidence, align on what was learned and decide whether to scale, iterate or stop.
Four focused days, without requiring the whole team for four full days.
Frequently asked questions
What is the difference between an AI Opportunity Workshop and an AI Solution Sprint?
The AI Opportunity Workshop helps you decide where AI can make the biggest difference. The AI Solution Sprint goes deeper into one selected opportunity or workflow: redesign the work, prototype the human + AI solution, test it and decide whether it deserves further investment.
Do we need our own AI developers to run the Sprint?
You need enough technical expertise to challenge feasibility and create a believable prototype. That expertise can come from your own organisation or be brought into the Sprint. The Sprint is not a replacement for production engineering.
Is the prototype production ready?
Usually not. Its purpose is to create realistic evidence quickly, not to bypass architecture, security, integration and production-quality engineering. A successful Sprint gives the implementation team a much stronger starting point.
How long does an AI Solution Sprint take?
The core Sprint is four focused days, supported by preparation beforehand and a short follow-up to capture decisions and next steps.
What happens after the Sprint?
You make an explicit decision: scale, iterate or stop. If the evidence is strong, internal IT, Data & Tech or an implementation partner can take the validated concept into production delivery with much richer context.
your facilitator
Jens Broetzmann is the founder of CONTINNO and has more than 25 years of experience helping organisations and teams turn change into practical progress. He combines systems thinking, Agile, Lean, Design Thinking and behavioural change principles to create approaches that fit the context rather than forcing a methodology.
bring one AI challenge.
Ready to redesign how work gets done with AI?
You don’t need a finished specification or AI concept. Bring one promising AI opportunity, an important workflow worth improving, or simply something that isn’t working as well as you’d like.
Let’s get to know each other and talk about what you’d like to achieve.
In 30 minutes, we’ll explore what’s going on, what’s getting in the way and what could help you move forward.
No preparation needed. And we can talk in English, Dutch or German.
+ 31 – 6 53432423
jens.broetzmann@continno.com
‘s-Hertogenbosch, the Netherlands
Understand your situation
We look at what you want to improve.
Explore options
We explore what could make a difference.
Leave with clarity
You leave with a clearer view of what to do next.