Singapore's AI maturity has rebounded, but a critical execution gap threatens to undermine record investments. While agentic AI adoption has doubled to 51% in 2026, only 10% have redesigned end-to-end workflows. This "Pacesetter" minority achieves significantly higher ROI, highlighting the difference between buying AI and building an enterprise around it—a lesson for Southeast Asia.In this PodChats for FutureCIO, Colin Tan, country manager for ServiceNow Singapore, explains to us what the most recent ServiceNow study reveals about agentic AI adoption in Singapore.Colin, welcome to PodChats for FutureCIO.1. Strategy & Ambition: In the ServiceNow study, 68% of organisations cited inadequate data accuracy, access, and management as on-going challenges. How do we modernise our data architecture to provide the clean, connected, and real-time intelligence AI agents need to act reliably at scale?2. Infrastructure & Scale: As agentic AI generates exponentially more network traffic and computational demand, is our current infrastructure resilient enough to handle this surge, or are we risking a "digital congestion collapse" that undermines performance and agility?3. Workflow Orchestration: While 51% of Singapore enterprises now use agentic AI, only 10% have redesigned end-to-end workflows. How do we shift from automating isolated tasks to orchestrating autonomous, cross-functional workflows that deliver measurable business transformation?4. Taming "Agent Sprawl": As autonomous agents proliferate across departments, they risk creating new technical debt and fragmentation. How do we architect a unified control plane to gain visibility, manage permissions, and prevent chaotic, disconnected agent deployments?5. Governance & Risk: Governance is the prerequisite for autonomous AI. How do we build a living governance framework that provides continuous oversight, embeds trust and transparency, and ensures accountability before agents operate at scale?6. Singapore’s IMDA published the world's first governance framework for agentic AI. How are Singapore enterprises keeping pace with the standard the government has set for the country?7. Measuring New Value: As AI shifts from efficiency to revenue creation and new business models, how should we evolve our metrics to accurately capture the value of AI-enabled agility, innovation, and competitive differentiation—not just cost savings?8. Lesson from Pacesetters: The ServiceNow study shows that a "Pacesetter" minority, who redesign work around AI, can achieve significantly higher ROI than those that simply layer AI onto existing processes. What can we learn from Pacesetters?

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