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🎙️ with Dr. Marc Roman Franke, Partner & Associate Director AI and digital transformation at BCG
💬 Opening
Eva Simone Lihotzky speaks with Marc Roman Franke, Partner & Associate Director AI and digital transformation at BCG, about how trust is built - or lost - during AI transformation inside large organizations. The conversation is for leaders, product owners, and transformation teams trying to move beyond pilots and into real operating change. It focuses on why execution, governance, and organizational choices determine whether AI creates value or stalls.
🎤 Episode overview
Drawing on large-scale research and implementation experience, the episode examines why only a small share of companies see meaningful returns from AI. Franke argues that the main constraints are not models or tools, but leadership alignment, operating models, and how trust is earned through delivery. The discussion moves from the limits of “AI-ready” programs to what it means to become “AI-first,” including the rise of agentic AI, unmanaged security risks, and why postponing Responsible AI eventually blocks scale.
🎯 Key themes discussed
Trust as a practical outcome of reliable execution and visible value, not long-term promises
Why most AI value depends on people, organization, and leadership rather than algorithms
What separates the small minority of companies that capture real AI value from the rest
The difference between experimenting with AI and redesigning the business around it
How agentic AI changes accountability, decision rights, and human–AI collaboration
Governance as an enabler of adoption and safety, not a compliance afterthought
Security and third-party risks that grow as AI scales
When Responsible AI can be delayed—and why it becomes a blocker later
🤝🏻 Referenced during the conversation:
BCG, MIT, SAP S/4HANA, GDPR, and Steve Jobs.
By Eva Simone Lihotzky🎙️ with Dr. Marc Roman Franke, Partner & Associate Director AI and digital transformation at BCG
💬 Opening
Eva Simone Lihotzky speaks with Marc Roman Franke, Partner & Associate Director AI and digital transformation at BCG, about how trust is built - or lost - during AI transformation inside large organizations. The conversation is for leaders, product owners, and transformation teams trying to move beyond pilots and into real operating change. It focuses on why execution, governance, and organizational choices determine whether AI creates value or stalls.
🎤 Episode overview
Drawing on large-scale research and implementation experience, the episode examines why only a small share of companies see meaningful returns from AI. Franke argues that the main constraints are not models or tools, but leadership alignment, operating models, and how trust is earned through delivery. The discussion moves from the limits of “AI-ready” programs to what it means to become “AI-first,” including the rise of agentic AI, unmanaged security risks, and why postponing Responsible AI eventually blocks scale.
🎯 Key themes discussed
Trust as a practical outcome of reliable execution and visible value, not long-term promises
Why most AI value depends on people, organization, and leadership rather than algorithms
What separates the small minority of companies that capture real AI value from the rest
The difference between experimenting with AI and redesigning the business around it
How agentic AI changes accountability, decision rights, and human–AI collaboration
Governance as an enabler of adoption and safety, not a compliance afterthought
Security and third-party risks that grow as AI scales
When Responsible AI can be delayed—and why it becomes a blocker later
🤝🏻 Referenced during the conversation:
BCG, MIT, SAP S/4HANA, GDPR, and Steve Jobs.