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Event Q&A
Building Trustworthy AI: Why Data Governance is the Foundation of AI Governance
Sebastian Nordgren explores how data and AI governance are increasingly converging, and why organisations must integrate AI risk into existing governance frameworks. He discusses data provenance, accountability, and preparing for the challenges of autonomous AI, while highlighting trust and transparency as emerging competitive advantages.
Oct 01, 2026
Sebastian Nordgren, Former Global Head of Privacy & AI Governance, Director, MUFG Bank
Tags:
AI and Technology (including Fintech)
The views and opinions expressed in this content are those of the thought leader as an individual and are not attributed to CeFPro or any other organization
- Data governance must evolve beyond structured data to encompass unstructured and AI-driven environments.
- Successful AI governance builds on existing privacy, cybersecurity, and risk management frameworks.
- Data provenance, traceability, and accountability are essential throughout the AI lifecycle.
- Agentic AI requires enhanced oversight, access controls, monitoring, and kill-switch capabilities.
- Future competitive advantage will depend on trusted, well-governed AI as much as technological advancement.
- Governance investment should be viewed as a business enabler rather than a compliance expense.
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