AI Discovery Lab

From AI Hype to a Reliable Proof of AI

AI is everywhere – yet in many companies, its concrete value in day-to-day work remains unclear. Leaders and teams recognize the potential, but often do not know where to start. Between tool hype, security concerns, limited experience, and unclear business potential, uncertainty arises: Which AI use cases are truly relevant? Which ideas are worth pursuing? And how can value be made tangible before larger investments are triggered? The challenge: AI opportunities are often discussed, but too rarely tested systematically. As a result, opportunities remain undiscovered, early success stories fail to materialize, and the organization remains stuck in observer mode.

Duration
6- 12 weeks
Format
Project
Target audience
CDO, Head of Innovation

Solution Approach

What if your leaders and teams could not only understand AI, but actually experience it, test it, and translate it into measurable insights? That is exactly what our AI Discovery Lab enables: a focused experimentation space in which AI ideas are systematically identified, tested, and evaluated. Together with selected leaders and employees, we develop concrete AI hypotheses and test them quickly and pragmatically – using prototypes, prompts, workflows, or vibe-coding approaches. The goal is not another AI training session, but reliable evidence: Which AI use cases create real business value? Which ideas should be pursued further? The result is a tangible Proof of AI – concrete evidence that AI can create value in your specific business context.

Benefits

  • Systematically identify AI opportunities within your own area of responsibility and translate them into concrete hypotheses
  • Reduce uncertainty and risk by testing AI ideas quickly, pragmatically, and with limited effort
  • Activate leaders and teams through hands-on success experiences and foster an exploratory AI mindset
  • Make business impact visible by systematically documenting results, learnings, and value
  • Create a reliable basis for decision-making regarding potential scaling, investments, or further enablement initiatives

Approach

  1. Kick-off & Goal Definition: Together, we define the focus of the AI Discovery Lab, select relevant areas and topics, and determine which company or business unit goals should be addressed through AI.
  2. Discover & Hypothesize: Leaders and teams explore AI opportunities in their work environment. Using Opportunity Cards, challenges, user groups, benefits, and critical assumptions are made visible. The result is a set of prioritized AI hypotheses with clear business relevance.
  3. Experiment & Build: Selected hypotheses are translated into simple experiments. Participants test AI-supported solution approaches, develop initial prototypes, prompts, or workflows, and collect evidence in day-to-day work.
  4. Learn & Share: Results are documented using Learning Cards. Insights, surprises, and impact patterns are shared, discussed, and made reusable for others.
  5. Validate & Scale: Successful approaches are assessed in terms of value, acceptance, feasibility, and scaling potential. This results in an Evidence Board with validated AI use cases and concrete next steps.
  6. Management Workshop: In a final workshop, we present the key findings, learnings, and use cases. Together, we assess which approaches should be pursued further, scaled, or integrated into a broader AI enablement initiative.

Deliverables

  • Prioritized AI Opportunity Cards with concrete challenges, hypotheses, target groups, value propositions, and critical assumptions
  • AI Experiment Cards with clearly defined tests, success criteria, effort estimates, and validation logic
  • Documented Learning Cards with results, observations, surprises, and recommendations
  • Initial AI prototypes, prompts, workflows, or solution approaches for real-world use cases from day-to-day work
  • Evidence Board with validated AI use cases, business impact, maturity level, and scaling potential
  • Management Presentation with the key insights, quick wins, decision options, and next steps
  • Concrete Roadmap for the further development of AI use cases, enablement formats, or scaling initiatives

Speak with our experts!

Let’s work together to identify where the greatest potential lies and which measures will deliver the greatest added value for you.

Tim Schüning
Director Digital Business Consulting
Contact us!
Frequently Asked Questions

Do you have questions? We have the answers.

How does the AI Discovery Lab differ from traditional AI training?

Training transfers knowledge. The Discovery Lab produces results. Your leaders and teams do not test AI in a training environment, but on real challenges from their day-to-day work. The outcome is validated use cases with documented business impact – not just trained employees.

Do participants need technical AI knowledge?

No. The Lab is designed so that participants without a technical background can formulate, test, and evaluate AI hypotheses. We use pragmatic formats such as prompts, no-code tools, and vibe-coding approaches that do not require programming skills.

What types of experiments are conducted in the Lab?

They range from simple prompt tests and workflow prototypes to functional mini-applications built through vibe coding. The decisive factor is not technical depth, but whether the hypothesis can be validated: Does this AI approach deliver measurable value in the specific context?

What happens if an experiment fails?

Then that is a valuable result. A failed experiment can prevent an expensive wrong investment. Every learning is documented on a Learning Card – including the reasons why it did not work. This allows your organization to build AI capabilities systematically.

How do we make sure the results do not get lost after the Lab?

Each validated use case is documented in the Evidence Board with its value, maturity level, and scaling potential. In the final management workshop, we jointly define concrete next steps. If desired, we also support the transition of successful approaches into implementation.