Singapore's Big AI Push Falls Short on Data Activation, PwC Report Finds
Source: CDOTrends
Singapore organisations are leading the world in AI risk-taking, with 67% willing to invest aggressively compared to 41% globally, but a new PwC report reveals a critical gap: only 43% are generating new value from their data. The finding points to a widespread failure to activate the data that AI systems depend on.
Singapore is moving faster into artificial intelligence than most of the world, but a significant gap is emerging between adoption and results. According to a PwC report cited by Boomi CTO David Irecki in a CDOTrends analysis, 67% of Singapore-based organisations are willing to take risks on AI, compared to 41% globally, and 63% are already using AI to inform key financial and workforce decisions. Yet only 43% say they are generating new value through data, significantly behind the 63% among leading AI-adopting organisations worldwide.
The disconnect, Irecki argues, lies in data activation. AI creates real business value only when it is embedded into everyday workflows and supported by trusted, accessible data. But most enterprise data in Singapore remains fragmented across CRM platforms, billing systems, customer support tools and finance databases — each holding a different version of the same story. Without a unified view, AI agents can recommend the wrong product, overlook service issues, or create disjointed customer experiences. In a pilot phase, teams can manually catch these issues. In a live environment, the inconsistencies scale quickly and noticeably.
PwC's research found that organisations that redesign workflows around integrated, trusted data are seeing up to 7.2 times greater revenue and efficiency gains. Yet only just over a third of organisations in Singapore have redesigned their workflows to fully incorporate AI, compared to more than half of AI leaders globally. The implication is clear: ambition and investment alone are not enough. Without a foundation of connected, contextualised and governed data, even the most advanced AI tools will struggle to deliver consistent value.
Singapore has the government backing, the digitally mature economy and the ecosystem to lead in AI. But the next phase of competition will not be about who has the most tools or the fastest pilots. It will be about who can break down data silos, improve data quality, and create a shared foundation that AI systems can rely on. The winners, Irecki says, will be the organisations that understand that AI is only as powerful as the data behind it.
Why it matters for Singapore: For a city-state that has staked its economic future on becoming a global AI hub, the gap between adoption and value creation is a warning signal. The government has poured resources into AI infrastructure, talent development and industry partnerships. But the PwC data suggests that enterprise readiness — specifically data readiness — is not keeping pace. Closing this gap could unlock significant economic value and cement Singapore's position as a genuine AI leader rather than just an early adopter.