Your team. Five days. One AI PoC up and running.
The AI Design Sprint is a structured five-phase process that guides your team from "We should do something with AI" to a validated concept and running prototype - built by your own team, without external developers, without programming skills.
Five phases. One clear result.
Each phase has a defined deliverable. No shooting in the dark. Enter the sprint at the best point for you.
01. Entry option: Opportunity Mapping
0.5 – 1 day · C-Suite or upper management
With AI cards that translate AI capabilities into business language, management and senior decision-makers identify which business areas are suitable for AI. No prior technical knowledge needed. Just a look at your own business.
Result
Focus area identified — a business unit prioritized for the sprint
02. Framing Workshop: Entry option
1 day · the responsible specialist team
The team working in the chosen area analyzes its own workflows, step by step, honestly and concretely. The workflows are prioritized. We then assign AI categories: What type of AI can be usefully applied at which point? The highest-rated workflow goes directly to step 3.
Result
Prioritized workflow with AI categories as the basis for the concept
03. Entry option: Concept Development
2 days · specialist team
We go through the prioritized workflow step by step: Where does AI come in? What is the exact input, what is the output per step? What exactly does "the AI" do and where must a human intervene? The concept is not an overview it is the complete specification that makes building the POC possible in the first place.
Result
AI-Concept, Input & AI-Output defined per Workflow.
04. TechCheck
0.5 days · Facilitator + 1 team member + IT
I speak with a team member and your IT department. Here we clarify: How do we access the required data as a standalone file, without an API connection, without user accounts? For the internal POC we work with idealized data. No GDPR process, no security architecture. That comes later. Here it's only about whether the data is basically available and processable.
Result
Data situation clarified! Format and handoff path for the POC are defined.
05. Proof of Concept - AI Vibe Coded
2 days · Facilitator & your team
Your team builds the prototype itself with Codex or Claude Code and directly sees how precisely AI requirements need to be formulated. Requirements must be clearly defined. This is one of the most important insights of the sprint. This trains the team in daily use in their own workflow, with their own data.
Result
Running prototype with a real workflow and solid AI know-how in the team.
AI finds and organizes information
AI gains insights from big data and understands the past and present
AI performs simple tasks
AI makes decisions and recommendations
AI sees
AI reads
AI chats and talks
AI hears and understands speech
AI senses the environment
AI creates
AI optimizes and processes
AI forecasts
AI controls machines and robots
Other technologies
AI finds and organizes information
AI gains insights from big data and understands the past and present
AI performs simple tasks
AI makes decisions and recommendations
AI sees
AI reads
AI chats and talks
AI hears and understands speech
AI senses the environment
AI creates
AI optimizes and processes
AI forecasts
AI controls machines and robots
Other technologies
83 %
of German companies see AI as an opportunity
– – –
Bitkom Research 2025
36 %
are already actively using AI. Two years ago it was 9%
– – –
Bitkom Research 2025
~85 %
of AI projects fail due to lack of structure and strategy
– – –
kipreneur.de /
Computer Weekly 2024
Most medium-sized companies face the same challenges when it comes to getting started with AI.
Does this sound familiar:
-
"We've paid external consultants and nothing to show for it."
Commissioning, presentation, done. No functioning result. -
"Our IT says the use case can't be implemented."
Without a structured feasibility check, much remains unclear. -
"AI is for corporations, not for us."
This belief costs competitive advantages. The AI Design Sprint is specially developed for mid-market teams with no prior AI experience. -
"We don't know where to start."
Lots of ideas, no prioritization. In the end, nothing happens. -
"AI projects at our company always take years."
Without a clear framework, every initiative is delayed until it stalls.
85% of AI projects rarely fail because of the technology.
They fail because the wrong problem is solved, users are not involved and assumptions about data remain unchecked. The AI Design Sprint is built to avoid exactly these three mistakes in 5 days, before a single euro is spent on development.
– – –
kipreneur.de / Computer Weekly DE, 2024
What is the AI Design Sprint?
A structured AI Design Sprint is the fastest, lowest-risk path from AI idea to validated prototype.
In 5 phases, your team goes from idea to running prototype, without external developers, without programming knowledge. Whoever builds the prototype understands it. And those who understand it can champion it internally.
Book a free discovery call
Most workshops end with a presentation. This one ends with running code.
Your team uses AI coding tools like Claude Code to build the prototype themselves – without programming knowledge, without an external agency. This fundamentally changes the dynamics in your company:
-
Stakeholders see real results
A demo convinces in 10 minutes what a presentation takes months to achieve. Budget approvals happen faster. -
Your team becomes an internal champion
Whoever builds something themselves believes in it and carries it forward. The knowledge stays in the company not with the consultant who leaves after the project. -
AI expertise as a lasting value
Your team learns to use AI tools productively. This is not a side effect of the sprint it is a standalone business value.
What you walk away with
Concrete, immediately usable result. No presentations without substance. No concept gathering dust in a drawer.
Duration: ~7 working days.
From the first idea to a working prototype. In a few weeks instead of months.
Prioritized use case list
At least 4-8 identified AI use cases, evaluated by potential, effort and strategic relevance.
Technically validated concept
Each use case was checked with your IT for data availability, and possible system integration and security were discussed.
Working AI prototype
Built by the team, for the team, with modern AI tools. No external developer, no dependency. The result belongs to you. The knowledge stays in the company.
Hands-on AI expertise
Your team has learned to apply AI tools and can put that knowledge to use directly in day-to-day business, explore new use cases and develop them.
Implementation roadmap
A concrete roadmap with next steps so the sprint doesn't end at the prototype stage but creates real impact.
Who is the AI Design Sprint made for?
The Sprint is a versatile solution, built for exactly one type of company.
- Mid-market company with 50–5,000 employees
- You want to use AI, but don't know where yet
- Your technical contact person or internal IT is super busy already
- You are looking for a structured, low-risk AI entry point
- You don't want a permanent dependency on external consultants
Is this expensive?
Well, see for your self ...
Source: Bitkom, Microsoft, HR Report; consultingcosts according to industry benchmarks DE 2024/25
| Tasks | External Consulting | Hire AI Developer | Buy AI Software | AI Design Sprint |
|---|---|---|---|---|
| Time to first insight | 3–12 months | 6-18 months | Immediately, needs configuration | 2–5 days |
| Cost to validate | 50K€–500K€+ | 80K€–120K/pa | License + configuration costs | 25-35k€ |
| Result | Powerpoint | Depending on candidate | With limitations | PoC with running code, implementation plan |
| Prior technical knowledge needed | No | High (evaluate candidates) | Medium | No |
| Risk of building the wrong thing | High | High | Medium | Low, fast iteration possible |
| Knowledge stays in the company | No | Depends on the employee | Fast, but generic | Stays 100% |
FAQ: your questions answered
What company size is the sprint suitable for?
The sprint is ideal for mid-market companies with 50 to 5000 employees. More important than size is that you have an open mind and you are willing to change things.
Do we need prior technical knowledge?
No. The sprint team doesn't need any programming background. We work with modern AI tools that can be used without coding experience. However, we do need a technical contact person at your company for the TechCheck and PoC data provisioning.
How is this different from traditional management consulting?
Traditional consulting delivers a presentation at the end. The AI Design Sprint delivers a working prototype built by your team with tangible AI know-how and an implementation roadmap for the next step.
What happens if a use case is not technically feasible?
That's exactly why the TechCheck exists in phase 4, directly before building. If a use case isn't feasible, we switch to the next best one from the prioritised long list. So you don't waste time on projects that would fail anyway.
Do we work remotely or on site?
We highly recommend an in-person event for steps 1–3 and 5, as group work benefits from personal contact. Phase 4 (TechCheck) can be conducted remotely.
What happens after the sprint?
At the end of the sprint you have a coded prototype and an implementation roadmap. You decide what happens next. Many teams move straight on to another use case, while we help find external service providers to handle production grade implementation of the first use case. Your own IT team is often already at capacity.
