AI Guide For Boards in Singapore

AI GUIDE FOR BOARDS IN SINGAPORE

Section II: Strategy and Value Creation

4.3 Resource Allocation

• Productivity projects: Workforce productivity tools may show returns relatively quickly. Examples include: workforce co-pilots, knowledge assistants and administrative automation tools. • Transformation initiatives: Workow redesign, system integration and AI- enabled product development oen require more sustained investment before their full return on investment becomes visible. Organisational readiness is oen a determining factor in whether AI investment translates into measurable value.

Resource allocation for AI initiatives should extend beyond soware procurement to include the organisational capabilities required to support long-term transformation. Boards should treat AI investment as a strategic capability portfolio rather than a collection of isolated technology projects, and pay attention to the Core Pillars of AI Investment .

is includes investment in: • People and skills. • Data infrastructure. • Systems integration. • Governance. • Organisational readiness.

Boards should assess transformation initiatives with a longer-term strategic lens, rather than short-term return metrics alone.

Budgeting decisions should reect the fact that dierent AI initiatives create value over dierent time horizons:

Core Pillars of AI Investment

Eective AI integration generally requires coordinated resource allocation and investment across several critical pillars: • Talent strategy: Organisations need more than just technical specialists. ey require leaders, operational sta and frontline teams who can identify use cases, redesign workows, evaluate outputs and adopt new ways of working. • Data and knowledge infrastructure: High-value use cases depend on AI access to trusted and well-governed organisation data. AI systems are more eective when they can securely access relevant internal documents, systems and institutional knowledge. • Connected systems: AI creates greater value when integrated into existing enterprise systems and workows, including: email, calendars, customer relationship management systems, collaboration tools and operational platforms. • Organisational readiness: AI maturity depends not only on technology deployment, but also on: sta training, adoption levels, governance structures and cross- functional coordination.

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