How to invest in AI to scale enterprise value

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 impacts across the enterprise, and by extension, the broader economy.

Transforming as “client zero”

The global EY organization began its AI transformation in 2017, well before generative AI became mainstream. Taking a “client zero” approach to its AI transformation, the organization 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, the EY organization 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. 

A rich ecosystem of partners and alliances helps power EY.ai. For example, working with Nvidia AI, the EY organization 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 helps develop and deploy AI agents for clients and offers access to professional AI talent. The recent EY 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 organization 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 a driver of better decisions, faster execution and stronger performance. 

The executive focus must be on AI for business transformation. Leading organizations are going beyond experimenting with AI projects to embed it in the operating model. Real value comes when intelligence is built into how the enterprise decides, executes and governs at scale. 

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, the operating model, talent and regulatory readiness so that AI is embedded in day-to-day decisions and operations. 

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.