STENSON GLOBAL
AI is not a technology issue — it is a board-level risk and accountability problem.
AI is not a technology issue — it is a board-level risk and accountability problem.
AI Governance is a Board-Level Risk Problem
Not a technology issue — a risk ownership problem
Integrating AI into Enterprise Risk & Governance
I work with financial institutions to embed AI risk into enterprise risk governance frameworks— across ERM, the Three Lines of Defense, and board level oversight.
The AI Governance Gap
Artificial intelligence is increasingly embedded in core decision making;
across credit, fraud, operations, and customer interactions.
Governance structures have not evolved at the same pace.
AI risk does not sit neatly within a single function.
It cuts across risk, technology, data, and business lines; creating ambiguity in ownership and accountability.
The result is a structural gap:
AI capability is advancing faster than institutions are structured to govern it.
This gap requires a structured approach to integrating AI risk into enterprise governance.
The Stenson AI Governance Architecture™
A structured approach to integrating AI risk into enterprise governance frameworks.
Designed to close the gap between AI capability and institutional oversight, by embedding accountability, visibility, and lifecycle governance within existing structures.
The framework focuses on:
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Integration into Enterprise Risk Management (ERM)
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Alignment with the Three Lines of Defense
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Board-level visibility and reporting of AI risk
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Lifecycle governance — from development to deployment and monitoring
The focus is not on principles or technical controls - but on operationalizing AI governance within the structures organizations already rely on.
Engagement
Engagements are focused on clarifying AI risk ownership and embedding governance within existing institutional structures.
This typically includes:
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Board-level dialogue on AI risk and accountability
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Integration of AI into enterprise risk frameworks (ERM)
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Alignment across the Three Lines of Defense
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Design of governance models for AI lifecycle oversight
I work selectively with financial institutions and complex organizations where AI is already embedded in core decision-making — and where governance structures must evolve accordingly.
Engagements are advisory in nature and focused on structure, accountability, and implementation within existing governance frameworks — not abstract principles or isolated technical solutions.
Background & Current Work
I have served as CEO and COO across international and private-sector environments, leading governance, risk, and operational functions in complex and high-pressure contexts.
My work is informed by experience in executive leadership and an understanding of behavioral dynamics in high stakes, decision-intensive environments.
This work is currently being developed and validated with senior practitioners across ASEAN financial institutions as part of an MIT Professional Education Capstone focused on
AI governance and risk integration.