AI GUIDE FOR BOARDS IN SINGAPORE
Section II: Strategy and Value Creation
Chapter 5: Measuring AI Value
Boards play a critical role in ensuring that AI delivers measurable and sustainable value beyond experimentation. E ective oversight requires directors to establish clear expectations regarding performance measurement, accountability and business outcomes. Unlike traditional technology investments, AI initiatives o en evolve iteratively, with
Boards should therefore ensure that AI measurement frameworks are dynamic, business-oriented and aligned with enterprise strategy. value emerging progressively as adoption scales, workows are redesigned, and organisational capabilities mature.
5.1 Establishing AI-Specific Performance Metrics
Boards should ensure that AI initiatives are measured in a structured, consistent manner, aligned to business objectives and stages of maturity. Measurement frameworks should be designed to enable directors to assess whether AI initiatives are progressing from experimentation to tangible value creation. AI metrics should not be con ned to technical performance alone. Eective oversight requires visibility into:
• Business impact. • Operational eectiveness. • User adoption. • Risk exposure. • Organisational readiness.
5.1.1 Measuring AI value across stages of maturity
Boards should recognise that AI initiatives evolve through Stages of Maturity in the AI Lifecycle .
Stages of Maturity in the AI Lifecycle
Stage
Primary focus
Example metrics
Pilot (Proof-of- concept) Scaled adoption
Feasibility and technical validation
Accuracy, reliability, task completion rates, error rates, human review burden User adoption, repeat usage, turnaround time, time saved, workow integration, output quality Revenue contribution, customer satisfaction, throughput improvement, margin enhancement, cost-to-serve reduction
Business integration and operational usage Business impact and strategic outcomes
Enterprise transformation
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