AI GUIDE FOR BOARDS IN SINGAPORE
Section VI: Operationalisation
Step 5: Monitor adoption and performance
Boards should monitor whether AI investments are producing measurable business value and progressing beyond experiments. Tracking the health of AI integration requires a set of key performance indicators that go beyond traditional technology metrics. Management reporting may include: • AI performance dashboard: Metrics may track estimated value realised, adoption rates, model performance and dri , operational e ciency gains and
percentage of projects progressing from pilot to production. • Shadow AI risks: Boards should understand the extent of unauthorised use of public AI tools within the organisation. Unchecked, “shadow AI” may introduce risks relating to data leakage and intellectual property risks.
Reference Chapter 5: Measuring AI Value
Step 6: Enable talent and cultural transformation
AI adoption is fundamentally an organisational change initiative rather than about technology deployment. Boards should oversee how management is preparing the workforce to operate eectively alongside AI systems. Key considerations include: • Workforce upskilling: Organisations should invest in AI literacy, skills development, training and leadership programmes to support broader adoption and reduce asymmetry across the organisation. • Job redesign: Boards should monitor how AI is fundamentally changing workforce roles, and ensure a just transition for
employees whose primary tasks are being automated. A Guide to Job Redesign in the Age of AI by IMDA and Personal Data Protection Commission is a useful resource. • Board capability: Boards should maintain su cient AI literacy to discharge their responsibilities through director education programmes, external expert brie ngs and reverse mentorship sessions where technical leads may brief the board on emerging trends and risks.
Reference Chapter 8: Responsible AI and Building Trust Chapter 11: Talent and Technology
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