Address by SMS Tan Kiat How at NVIDIA AI Day Singapore

We are living through an extraordinary period in technology.

AI models are becoming more capable at remarkable speed. At the same time, companies are investing billions of dollars in GPUs, data centres, networks, energy and the infrastructure needed to support the next generation of AI.

NVIDIA has been at the centre of this build-out. At the same time, I think the next phase raises a different question: Can we turn all this AI capacity into AI value?

The first bottlenecks were technological: Can we build the models, chips and computing infrastructure needed to make advanced AI possible?

Increasingly, another bottleneck is emerging – commercialisation. Technology companies need sustained enterprise demand to support continued investment in AI infrastructure. Enterprises and the government, in turn, need to see meaningful returns before they deploy AI at scale.

The next constraint on AI growth may not be what AI can do. It may be about how quickly organisations can turn what AI can do into economic value.

There is a simple distinction that I find useful.

But capacity is not the same as capability.

And capability is not yet competitive advantage.

To create value, AI has to work with data systems, domain expertise, people and business processes. That means enterprises have to change too.

The question is no longer simply: “Where can we use AI?” A better question is: “What should we redesign, now that AI exists?”

There is a progression here: from tools, to tasks, to workflows, to jobs, and eventually to the organisation itself. The biggest gains may come not from making an individual task 20 per cent faster, but from rethinking how an entire process works when people and AI can divide the work differently.