AI House Davos 2026

"Building Global Trust in AI" is a 50-minute moderated roundtable that surfaces the gap between high-level governance expectations (robustness, fairness, resilience, explainability) and the technical evidence required to operationalize trust at scale.

Organized by

Date

January 20 2026

Location

AI House Davos (Davos Platz)

Access the Replay of the Roundtable

From principles to evidence-based AI Governance

As AI shifts toward more autonomous, interconnected systems, the risk surface expands, and generic, principle-based approaches don’t scale without operational, evidence-based governance. This session centers on what “trust by evidence” looks like in practice: reproducible evaluations, auditable artifacts, and assurance mechanisms that support real adoption and ROI.

Speakers

Prof. Andreas Krause (Moderator)

Full Professor ETH Zurich, Director ETH AI Center, Co-founder LatticeFlow AI

Prof. Yoshua Bengio

Turing Award Laureate, Founder and Scientific Director
at Mila – Quebec AI Institute

Dr. Sean Kask

Chief AI Strategy Officer
at SAP

Dr. Sina Wulfmeyer

CDO
Unique

Vanessa Candela

Chief Legal & Trust Officer
Celonis

Jonathan Zanger

CTO
Check Point Software

Sunir Kapoor

Chairman, Kibo Ventures & Partner
Atlantic Bridge

Sam Ramadori

Co-President
LawZero

Dr. Petar Tsankov

CEO and Co-Founder
at LatticeFlow AI

Denise Wong

Assistant Chief Executive - Data Protection and Innovation Group
IMDA

Karen O’Regan

Managing Director
Accenture

What the session covers

Where lack of trust concretely slows AI adoption.
Why do regulations reference technical properties but break down in implementation.
Minimum viable evidence to deploy and scale AI with confidence.
Reproducible and auditable assessments (system-level vs model-only).
Continuous assurance for agentic AI: testing behavior, not just outputs.

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