Post by Gerd Winandi-Martin

Last week, I had the opportunity to spend two inspiring days in Berlin as part of my CAS AI Game Changer journey. 📍 𝐃𝐚𝐲 𝟏: 𝐌𝐨𝐭𝐢𝐨𝐧𝐋𝐚𝐛 & 𝐕𝐞𝐧𝐭𝐮𝐫𝐞 𝐂𝐚𝐟é 𝐁𝐞𝐫𝐥𝐢𝐧 We kicked things off at MotionLab.Berlin, where we met a range of startups working on bold, real-world innovations. What stood out most was the energy: people building, testing, failing, and iterating fast. Later at Venture Café Berlin, the exchange with founders and innovators reinforced one key idea for me: innovation doesn’t happen in isolation - it thrives in communities. 📍 𝐃𝐚𝐲 𝟐: 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩 “𝐅𝐫𝐨𝐦 𝐈𝐝𝐞𝐚 𝐭𝐨 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞: 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐢𝐧𝐠 𝐀𝐈 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬” The second day at Merantix AI Campus took a deeper, more structured dive into how AI projects actually get implemented. During the workshop, we didn’t just talk about AI, we worked through a hands-on case, built a structured approach, and even calculated implementation costs. A particularly valuable takeaway was a simple but powerful framework (see image 👇) to holistically evaluate AI initiatives before kickoff. It includes: ➡️ Value Proposition – What real problem are we solving? Is there tangible business value? ➡️ Performance Indicators – How do we measure success? ➡️ Organization – Do we have the right people, skills, and setup? ➡️ Data & Technology – Is the data available, and is the tech stack ready? ➡️ Operational Implications – What changes in processes, roles, and workflows? ➡️ AI Life Cycle – How do we ensure continuous improvement after launch? 💡 My key learnings: AI success is less about the algorithm and more about clarity, structure, and execution. Many ideas fail not because they’re bad, but because feasibility isn’t properly assessed upfront. Thinking in end-to-end processes (not just prototypes) is crucial. Cost transparency early on helps avoid “innovation theater” and drives real decisions. A big thank you to Paulina Weiss and Alina Govoni for facilitating such a hands-on and insightful workshop! I’m taking away not just inspiration, but also practical tools I can apply immediately. Curious: How do you currently evaluate whether an AI idea is worth pursuing? Maria Anselmi Jelena Brdar Manuel Eicher Alexander Fürer Oscar Lopez Tejido Faizal N. Hayal Oezkan Andreea Schiopu Sandra Siehler Dr. Andreas Tschuor David Vuckovic Patrick Meyer Executive Education Universität Zürich