Firms and agencies have to reorganise data, rebuild systems, redesign processes and jobs, and retrain people
BUDGET 2026 places artificial intelligence (AI) at the centre of Singapore’s economic strategy. Prime Minister Lawrence Wong’s framing is clear: Singapore must harness AI as a strategic advantage in a more uncertain and competitive world, and we must do so responsibly, safely and in a way that benefits are shared widely.
To execute that strategy effectively, two capabilities will matter enormously: disciplined design, and speed of innovation.
This year’s Budget is explicit that Singapore’s edge does not lie in building the largest frontier models. It lies in deploying AI effectively, responsibly and at speed. That is a demanding direction because deployment at scale is not a technology purchase. It is organisational change.
Firms and agencies have to reorganise data, rebuild systems, redesign processes and jobs, and retrain people. If those changes do not happen, AI stays trapped in pilots and isolated experiments.
The national AI Missions reflect this ambition. Advanced manufacturing, connectivity, finance and healthcare are structural pillars of Singapore’s economy. These are also sectors where productivity gains can compound through supply chains and public systems.
PM Wong’s point is straightforward: the AI missions must be anchored in clear objectives and tangible outcomes. The government will align research and development, regulation and investment promotion so agencies pull in the same direction.
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A National AI Council chaired by PM Wong signalled that the intention is coordination and execution, not scattered experimentation.
But execution is hard for a reason. AI does not deliver value simply because it exists. It delivers value when the surrounding system changes.
A bank can automate parts of loan processing, but if approval remains layered and manual, time saved at the front end is lost downstream.
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A hospital can deploy predictive analytics, but if clinical workflows remain untouched, better insights do not reliably translate into better outcomes. A factory can install sensors and real-time monitoring, but if maintenance routines remain designed for periodic inspection, responsiveness does not improve much.
These are not failures of AI. They are failures to redesign work.
This is what I mean by design. It is not about aesthetics. It is about how decisions are made, how responsibilities are allocated, how risks are managed, and how humans and AI interact.
Done well, design makes AI part of daily operations. Done poorly, AI becomes a technical overlay that never shifts productivity at scale.
Speed matters because AI capabilities evolve quickly and organisations have limited time to convert early adoption into lasting advantage.
The Budget itself makes this point in a different way. It notes that end-to-end transformation is demanding, even for major global companies, and that those who succeed will gain a decisive competitive advantage. In other words, a slow transformation risks becoming a perpetual transformation, always catching up to the next cycle of tools and models.
That is why the enterprise measures in the Budget matter. The Champions of AI programme is positioned to support firms that want comprehensive transformation, including workforce training.
For the broader base of enterprises, especially SMEs, the expansion of the Enterprise Innovation Scheme to include qualifying AI expenditures, and the strengthening and widening of AI-enabled solutions under the Productivity Solutions Grant, are aimed at helping firms move from interest to real adoption.
The examples in the Budget are helpful because they ground the idea that AI adoption is not abstract. It is operational.
But the Budget is also clear that workers must be brought along, not left behind. Anxiety about job disruption is real, and Singapore’s approach is to press ahead with AI while putting strong support in place for transitions, reskilling and progression.
The focus on AI literacy across institutes of higher learning, and on helping working adults build practical AI capabilities, points to a deeper truth: sustained advantage requires sustained capability.
This is where education and training become strategic. At the Singapore University of Technology and Design, we have been reorganising our own approach around this reality through our Design·AI direction.
Design·AI is not simply about producing more coders or more model builders. It is about developing people who can combine deep technological and scientific foundations with design thinking and human-centred judgment. AI has to function inside real organisations, with real constraints, real accountability and real people.
We are putting in place new pathways that integrate computational and disciplinary depth with design thinking and human-centred systems education.
Students do not encounter AI as an abstract subject. They work on real industry problems where the challenge is not only to build a model, but also to redesign the workflow around it.
They grapple early with governance, responsibility and trust, because those are often what determine whether adoption succeeds.
Just as importantly, we train for speed of innovation. Students are expected to move from concept to prototype and from prototype to deployment within compressed cycles.
They learn to test assumptions early, iterate responsibly and act under uncertainty while maintaining rigour. Speed, as we teach it, is disciplined execution. It is the ability to translate insight into working reality before the window closes.
PM Wong is right that fear cannot guide Singapore’s response to AI. Discipline must guide it: discipline in design, so that AI changes how work is actually done; discipline in execution, so that transformation happens fast enough to create advantage; and discipline in capability-building, so that benefits are broad-based and workers can progress rather than be displaced.
In the coming years, Singapore’s AI strategy will be judged in practical terms: whether productivity rises materially in advanced manufacturing, connectivity, finance and healthcare; whether enterprises beyond a small frontier of leaders can adopt AI meaningfully; and whether Singaporeans are equipped to use AI well and progress.
The advantage will not belong to those who adopt AI first, but to those who redesign fastest, learn fastest and scale fastest.
If we get design and speed of innovation right, Singapore will not merely adopt AI responsibly. We will help define how a nation competes, builds and prospers in the age of AI.
The writer is provost and chief academic and innovation officer at the Singapore University of Technology and Design
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