The In-Between Tech and Trust Podcast

WEF26: The Politics of Tech, AI Agent Systems & Models, Adoption Challenges and Tech Sovereignty (EP 17)

The In-Between Tech and Trust Podcast

Show Notes

Opening This solo episode of The In-Between Tech & Trust Podcast reflects on conversations from Davos and what they reveal about where tech, politics, and trust are heading into 2026. It’s for leaders, operators, and policy-adjacent roles who are trying to make sense of AI adoption beyond tooling. The focus is on what actually changes inside organizations, institutions, and collaborations when AI becomes infrastructure.

🎧 Episode overview Eva Simone Lihotzky unpacks four threads that kept resurfacing across discussions with tech, political, and business leaders: agentic AI systems, the politics of technology, sovereignty, and the future of collaboration and trust. Rather than reporting speeches, the episode explores tensions beneath the surface - why organizations feel urgency but struggle to act, how AI exposes institutional weaknesses instead of fixing them, and why governance, infrastructure, and responsibility are now inseparable. The episode moves between business realities and geopolitical dynamics, asking what it really means to design AI-driven organizations, who shapes the rules when tech and politics are interwoven, and how dependence on a small set of platforms reshapes power, accountability, and autonomy.

🔍 Key themes discussed Agentic AI systems and why they force a rethink of organizational design

AI adoption as a platform shift, not a tool rollout

The gap between AI urgency and practical implementation inside companies

World models vs. specialized models and why both matter

Interoperability as an unsolved infrastructure problem

Tech as both upstream and downstream of politics

Sovereignty across compute, infrastructure, data, operations, and talent

Europe’s position in an AI-driven power landscape

Why collaboration now depends on explicit commitments, not assumptions

How trust becomes harder - and more necessary - as systems scale

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