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Event Q&A
Enterprise AI Success Depends on Trust Governance and Clear Accountability
As organizations move from AI experimentation to enterprise-wide deployment, governance, accountability, and trust are becoming critical success factors. In this Q&A, Wei Ma shares insights on scaling AI responsibly, highlighting the importance of secure architectures, clearly defined ownership, continuous monitoring, and system-level governance. The discussion explores how organizations can move beyond pilots and build the foundations needed for sustainable enterprise AI adoption.
Nov 03, 2026
Wei Ma, Managing Director, Head of Risk Modelling Centre of Excellence, SMBC
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
- Examines
the governance and security challenges that emerge when scaling AI beyond pilot
programs.
- Explores
how organizations can define ownership across business, technology, risk, and
compliance teams.
- Discusses
the benefits of reusable AI platforms and governance frameworks.
- Highlights the shift from model-centric governance to system-level oversight.
- Explores
the growing importance of continuous assurance, explainability, and
traceability.
- Shares practical advice for organizations looking to scale AI adoption successfully.
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