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How business leaders are turning AI ambition into operational reality
Last week we had the honor of welcoming industry leaders and researchers to Rewire LIVE 2025 in Frankfurt — for a day of practical insights on scaling data and AI, from vision to value at scale. With a packed agenda of keynotes, case studies, and mastermind sessions, the event zeroed in on one of the toughest challenges in enterprise AI today: how to bridge the last mile — turning promising pilots into production-grade, scalable, and trusted AI systems.
We know the answer but not the question
Rewire partner Christoph Sporleder thus opened the day by challenging common strategic pitfalls in AI adoption. Whether taking an exploratory, foundational, or holistic approach, many organizations struggle to operationalize at scale due to mismatched expectations, over-engineering, or governance complexities. His conclusion on breaking it down, balancing the transformation dimensions and going the full mile towards scale were picked up in the the powerful keynote of Simone Menne, Lufthansa’s former first female CFO. She reminded us that the real challenge of AI isn’t finding answers — it’s asking the right questions. Drawing from The Hitchhiker’s Guide to the Galaxy and her experience in leadership, Simone Menne spoke to the cultural and psychological hurdles that slow AI adoption. To overcome this we need to confront fear, foster curiosity, and prioritize education, governance, and collaboration across sectors to close the gap between potential and execution.
Dr. Peter Bärnreuther from Munich Re walked us through the rapidly growing domain of AI risks, from legal liabilities and IP issues to model drift and data bias. With over 200 AI-related lawsuits already filed globally, the urgency for transparent, testable, and auditable AI systems is mounting, and Munich Re is leading the way in also providing insurance products for AI. Nikhil Srinidhi, Partner at Rewire, illustrated the growing chasm between AI ambition and data readiness. In his talk, “Mind the Data Gap,” he highlighted the widening divide caused by poor data quality, fragmented ownership, and an expanding AI vendor landscape. His takeaway: scaling GenAI means scaling data maturity — and doing it across architecture, culture, and capability. Shannon Kehoe of QuantPi went on to emphasize that trust in AI starts with predictability and transparency. She introduced a model-agnostic platform that tests AI solutions across dimensions and presents results clearly for diverse stakeholders — from data scientists to regulators. Loïc Tilman of Elia Group shared what it takes to scale AI within a critical infrastructure operator. From evolving legacy systems to upskilling teams and ensuring sovereignty in the IT infrastructure, his talk made it clear: even in high-stakes environments, digital, data and AI transformation isn’t a luxury — it’s a necessity.
AI masterminds: defining real solutions to real challenges
The event also included interactive sessions, where Lu Yu of Novo Nordisk, Dr. Pierre Fischer of Roche and Dr. Martin Paschmann of Douglas shared real-world case studies. Participants dissected challenges ranging from siloed systems to frontline adoption. Solutions focused on data culture, internal champions, and aligning science with business needs. In one mastermind session, participants unpacked how to define the value of data products — from use-case fit and quality to cloud cost savings, time-to-insight, and user satisfaction. A key insight: value must be seen through multiple lenses — technical, financial, and strategic — and agreed upon by data, finance, and business stakeholders.
Panel discussion: scaling AI responsibly
The day concluded with a rich panel featuring Eberhard Schnebel (Goethe University Frankfurt / Commerzbank), Dr. Stefan Rose (University of Cologne), and Paola Daniore (EPFL Lausanne), moderated by Damien Deighan, Editor of the Data and AI magazine. Topics included the privacy paradox between academia and industry; the social psychology of AI interaction in teams; Trust-building through transparency and governance; The ethical design of emotionally resonant AI systems. Their message: AI adoption is about more than models. It’s about culture, behavior, and values — and how we ensure they evolve together.
Final thoughts
Rewire LIVE 2025 reinforced a shared truth: next to data and technology, AI is a leadership challenge. The ideas, stories, and solutions shared in Frankfurt revealed a deep appetite for actionable, scalable, and human-centered approaches to Data & AI.
We’re grateful to all speakers, participants, and partners who made the day a success. Let’s keep building — together.
Want to learn more about upcoming Rewire events? Visit the Rewire events page here.
