Artificial intelligence (AI) is now central to economic strategy. The Singapore Economic Strategy Review has set out recommendations to position Singapore as a leader in AI solutions and innovation, backed by investment in safety, governance and enterprise adoption.
To deliver on that ambition, AI must be deployed with speed, discipline and scale.
Isolated pilots and proof-of-concept initiatives do not add meaningfully to sustained business competitiveness. What matters is the ability to translate AI into scaled, repeatable impact across the enterprise, and by extension, the broader economyLiew Nam Soon, Singapore managing partner at Ernst & Young LLP, also EY Asia East deputy regional managing partner and Asean managing partner
EY is transforming as “client zero”
EY began its AI transformation in 2017, well before generative AI became mainstream. Taking a “client zero” approach to its AI transformation, EY chose to self-disrupt at scale.
In practice, this meant developing and testing hundreds of AI use cases internally, then refining these into high-impact applications. Informed by that “client zero” experience, EY launched EY.ai, a unifying platform that brings together EY technology, leading-edge capabilities and domain knowledge across assurance, consulting, tax, strategy and transactions. These include the EY.ai Maturity Model, EY.ai Value Accelerator, Responsible AI framework, EY.ai Confidence Index and the EY.ai Academy for Industries.
Liew highlights the rich ecosystem of partners and alliances that help power EY.ai. “For example, working with Nvidia AI, we launched the EY.ai Agentic Platform, as well as a new physical AI platform and EY.ai Lab across the globe. In Singapore, the EY Agentic AI Center of Excellence is helping to develop and deploy AI agents for our clients and offers access to professional AI talent. The recent global rollout of enterprise-scale agentic AI in audit also marks a fundamental shift, where clients gain greater confidence that their audits have benefited from both advanced technologies and professional insights. For EY professionals, it means moving up the value chain for professional development.”
This self-transformation allows EY teams to assess real-world challenges before advising clients. Importantly, it also enables the EY organisation to stress-test governance and responsible AI frameworks within a complex, regulated environment.
A business transformation imperative
Increasingly, enterprises are moving to embed AI more deeply into how they operate, with leaders treating it not as a technology choice, but as a driver of better decisions, faster execution and stronger performance.
The executive focus must be on AI for business transformation. Leading organisations are going beyond experimenting with AI projects to embedding it in the operating model. Real value comes when intelligence is built into how the enterprise decides, executes and governs at scaleGaurav Modi, EY Asean and Singapore consulting leader
However, despite rising ambition and spend, many enterprises still struggle to convert AI investment into business outcomes. The challenge is rarely the technology alone. It is aligning data, operating model, talent and regulatory readiness so AI is embedded in day-to-day decisions and operationsManik Bhandari, EY Asean AI and Data leader
Without an always-on system connecting data, decisions and action, AI impact remains fragmented. Enterprise transformation will not come from isolated use cases; it requires a production-grade system that delivers intelligence with consistency, control and scale.
Industrialise intelligence with AI factories
Enterprises that build a durable advantage will be those that industrialise intelligence with a factory-style approach. That means creating systems that learn, adapt and strengthen performance over time.
EY has developed a dependable agentic AI decision engine that can be embedded across a client’s enterprise and application landscape, so intelligence flows continuously into operations, learns continuously and adapts predictively. The scenarios in the table on the left illustrate what becomes possible when AI is embedded as a continuously learning factory — one that improves decisions, strengthens resilience and compounds value.
Unlocking enterprise value
Building an AI factory takes more than technology. It requires the right operating model, a value-led roadmap and a disciplined path from idea to scaled production. EY teams support this journey by combining sector experience, delivery frameworks and solutions that help organisations industrialise intelligence with confidence.
For enterprises, the question is no longer whether to invest in AI. It is about architecting AI for sustained performance, trust and resilience, so as to create long-term enterprise value.
