Fast AI adoption is not enough; Singapore must care about redesigning work

29 April 2026 – Singapore has emerged as one of the fastest adopters of artificial intelligence (AI) in the world, with more than 60 per cent of the population using generative AI in some form. Enterprise uptake of agentic AI is also progressing ahead of the Asia-Pacific average, according to a recent International Data Corporation (IDC) study commissioned by Microsoft*.

But rapid adoption does not automatically translate into sustained business impact. The real differentiator is execution in terms of whether organisations can turn AI usage into measurable returns.

For two decades of my career, I have seen Microsoft evolve as a customer, partner and competitor, while technology has consistently pushed the boundaries of what businesses can achieve.

What feels different about this moment is not how widely AI is being used, but how unevenly its value is being realised due to an underestimation of the structural change it will take. Now, in my new role at the company, I have a front-row seat to the next boundary of AI transformation and the organisations that are on the right track.

A question I posed to a room full of Singapore’s leaders at the recent Wee Cho Yaw Business Forum was: If your best people had 20 per cent more time every week, what would you want them to do with it?

We are beginning to see the real prize of the AI revolution if the answer is: More customer engagement. More mentoring. More thinking. More craft. More care for team members.

In a world where we have intelligence on tap, where computation is abundant and analysis is instant, care becomes the most expensive commodity on Earth. Those who lead with both intelligence and care – our uniquely human edge – will manage through this change and define the AI era.

Seasoned leaders know that real transformation takes a deep understanding of human behaviour and an investment in change management, not just bolting on new tech to old tasks.

We’re seeing this challenge in the data. In Singapore and across Asia-Pacific, only 13 per cent of organisations qualify as “frontier firms” – companies that have embedded AI into core operations and are capturing consistently higher returns – compared with 31 per cent in North America. According to IDC, this gap is less about ambition than execution maturity. North American firms have moved faster to redesign end-to-end workflows, integrate AI across multiple business functions, and put operating models, data foundations and governance in place. In much of Asia-Pacific, adoption has outpaced organisational readiness, leaving a visible gap between usage and impact, and many organisations stuck between pilots and production.

Singapore’s own adoption patterns reflect this. While the study found enterprise uptake of agentic AI at 37 per cent is broadly in line with global peers (36 per cent), deployment remains uneven across functions and sectors. Planned investment is concentrated in finance and accounting, human resources and customer service. These are strong starting points, but only part of where enterprise value is created.

Frontier firms stand out not because they use AI more often, but because they embed it more deeply and broadly, across at least seven functions. They move beyond standalone tools into shared workflows that connect data, systems and decisions across the enterprise. Just as importantly, AI becomes part of how work is measured and governed – not an add-on for employees to use.

The contrast is stark at the sector level. In Singapore, according to IDC, manufacturing shows the lowest intent to deploy agentic AI in the near term, with only 7.5 per cent planning to use it in the next two years. This is despite manufacturing accounting for 13 per cent of global agent usage, with deployments in factories, supply chains and energy operations. To help address this gap, Microsoft is working with the Agency for Science, Technology and Research (A*STAR) to explore agentic AI solutions in manufacturing, as part of a key initiative under Singapore’s National AI Strategy 2.0.

Across the region, the lag is driven less by intent than readiness. Competitive pressure to adopt is rising even as models, security controls and operating frameworks continue to evolve. Without reliable infrastructure, AI-ready skills, clear accountability and strong data foundations, deployment can accelerate faster than an organisation’s ability to absorb it. AI may remain concentrated in support functions rather than the operational core where durable returns are often realised.

Singapore is better positioned than much of the region to meet this moment, combining speed with institutional trust, regulatory clarity and a strong compliance culture. But that advantage is only real if leaders make deliberate choices: which workflows to redesign end-to-end, how to measure outcomes beyond usage, and how to extend adoption from early-moving functions into the operational core.

The next 12 months will be pivotal. If the “frontier gap” is fundamentally an execution gap, Singapore has an opportunity to lead in trusted execution by deploying AI at scale while maintaining accountability and governance, and by investing in those fundamentally human capabilities of judgment, leadership and care.

_{^{*IDC InfoBrief: sponsored by Microsoft, What Every Company Can Learn From Frontier firms Leading the AI Revolution, IDC # US53838325, November 2025}}

_{^{This op-ed was originally published in The Business Times.}}