AI Transformation (and/or Disruption) and Implementation Experiences: Views from Management, Board and GRC Professionals
Dr Jenny Tan25 Nov 2025 · 1 min read · First published by SheLeadsTech Singapore
Drawing on conversations with executives, directors and governance, risk and compliance (GRC) professionals, this article maps the very different ways each group experiences AI transformation — and why those differences so often turn promising initiatives into stalled ones.
Management tends to see opportunity and competitive pressure; boards see reputational, regulatory and ethical exposure; GRC teams see immature controls and unclear accountability. Jenny argues that none of these views is wrong, and that successful implementation depends on building a shared language and a shared risk appetite before scaling any use case.
The piece closes with practical lessons from real implementations: begin with well-bounded use cases, embed security and governance by design, make model ownership explicit, and create feedback loops that connect AI performance back to business KPIs and to the board's oversight agenda.
Key takeaways
- Align management, board and GRC on a shared AI risk appetite before scaling.
- Governance by design beats governance by retrofit.
- Explicit model ownership and feedback loops keep AI accountable over time.
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