IMAGE: IDC APAC
This time each year, scores of companies will flood our inboxes with technology trend predictions. While I’m waiting for the day an actual AI tool autonomously emails me its own predictions, I’ll fall back on what IDC has shared.
The research firm unveiled its top technology predictions for 2026–2030 for APAC, highlighting the region’s transition from the AI pivot to the agentic future. It forecasts that by 2030, 50 per cent of new economic value generated by digital businesses in APAC will come from organisations investing in and scaling their AI capabilities today, as enterprises embed autonomy, data intelligence and responsible governance into strategy to deliver measurable business impact.
Sandra Ng, senior vice president, IDC APAC, said: “2026 marks the dawn of the agentic era. Enterprises across the region are moving beyond experimentation and pilot projects to a future where AI acts with intent, autonomy and accountability. In this new phase, leadership clarity and responsible scaling are critical.”
The SAP Value of AI Report, which surveyed 1,600 business leaders of various sizes across eight countries, might proffer a different assessment in Singapore’s context.
Today, only 6 per cent of businesses are fully prepared to deploy and scale AI agents, while the majority (52 per cent) say they are partially prepared. In the next two years, Singaporean businesses expect return on investment from agentic AI of 8 per cent, below the global average of 10 per cent.
“Agentic AI represents the next frontier of business transformation,” said Eileen Chua, managing director, SAP Singapore. “It has the potential to multiply productivity and innovation, but its success depends on the same fundamentals – data quality, integration and people readiness. The organisations that invest in these areas now will be best positioned to capture value as AI continues to evolve.”
This is the catalyst for Far East Organization, a Singapore private property developer. It uses SAP Business AI as part of its broader digital transformation agenda to advance its leasing operations. The company has automated end-to-end lease management, from contract generation to analytics, to improve data accuracy, reduce manual inputs and provide real-time insights into portfolio performance. It now track trends in rental, occupancy rates and lease durations, giving property managers actionable insights to respond faster to market changes while making better decisions that strengthen portfolio and operational management.
“What previously took days can now be completed in minutes, giving our teams the time and insight to focus on customers and business growth,” said Ng Yee Pern, CTO, Far East Organization.
Agreeing, Kirsten Hinze, senior director, digital experience, Gold Coast Health, Australia, said: “Healthcare systems often struggle with limited resources due to the rising demand for services, an aging population and the increasing complexity of patient care. By automating repetitive administrative tasks using AI, our health service can ‘connect the unconnectable’ to increase operational efficiency and better allocate resources, ultimately improving patient outcomes.”
Gold Coast Health is a UIPath customer using AI to optimise both clinical and administrative workflows as part of its broader digital transformation strategy.
Are we buying real AI benefit, or into the AI Hype?
As companies pour billions into AI, whether to get ahead or simply keep pace, the stock market remains skittish, haunted by the threat of an AI bubble. The anxiety isn’t just limited to institutional investors looking for a quick exit. Industry heavyweights are sounding alarms too.
In a BBC interview, Alphabet CEO Sundar Pichai didn’t mince words, warning that if the AI bubble were to burst, no business would emerge unscathed. Pichai acknowledged the unmistakable whiff of “irrationality” fuelling the current AI boom, pointing to the sky-high valuations and frenzied spending on AI tech firms in recent months. The upshot? Caution is warranted, even as the AI arms race shows no signs of slowing down.
However, Qlik CEO Mike Capone offered a dose of realism. The current surge in AI, he argued, is more than hype – call it an investment cycle, not a speculative gold rush. Yes, there are frothy pockets, and market corrections loom on the horizon, but the bedrock of today’s AI landscape is cold, hard infrastructure and genuine demand.
“People keep asking whether AI is a bubble. I do not think that is the right single question. What I see globally is an investment cycle with pockets of speculation on top, not a pure rerun of 1999,” Capone said. “The facts matter here. The companies driving most of the spend today actually have earnings, cash flow and customers asking for capacity. Central banks and market analysts point out that valuations are high, but they are still anchored in real profits and very real capital expenditure on data centres, networks and power. That looks more like an industrial build-out than a meme stock frenzy.”
Take Groq, the AI inference upstart making moves in APAC. Its debut AI infrastructure in Equinix’s Sydney data centre isn’t just another pin on the map, it’s a calculated expansion that makes high-speed, affordable AI inference a reality for businesses, from creative juggernauts like Canva to public sector agencies. These aren’t moonshot experiments. They are AI solutions engineered to deliver, whether it’s turbocharging customer experiences or making employees more productive.
Still, Capone is quick to flag the warning signs. “Whenever you combine high valuations, concentration in a small group of names, and some circular deals between chipmakers, cloud providers and model companies, you should expect corrections … [some] projects will not clear the bar and that is exactly how cycles sort themselves out.”
So, what’s next for the executive suite?
The path ahead is less about chasing the AI hype cycle and more about sober assessment. Even as some companies post tangible wins, SAP’s research throws cold water on the notion that AI is a guaranteed game-changer.
70 per cent of Singaporean leaders aren’t convinced their AI bets are paying off: proof that today’s buzz doesn’t ensure tomorrow’s dominance. The real constraint? Organisational readiness. SAP found 76 per cent of Singapore firms haven’t rolled out robust AI training, yet 68 per cent admit that shadow AI is already sneaking in the back door.
The data dilemma is just as stark: 58 per cent of local companies don’t trust their ability to integrate and share data across teams, a mission-critical foundation for enterprise-grade AI. That trust deficit is especially acute in legal (80 per cent), finance (73 per cent), HR (66 per cent), the CEO’s office (64 per cent) and procurement (55 per cent).
The playbook, says IDC, is clear: C-suite leaders need to laser focus on use cases that move the needle.
By 2026, nearly half of all AI-driven digital initiatives in APAC will stumble on ROI targets, hobbled by fuzzy value and rocky data foundations. Looking further ahead, by 2027, half of Asia’s top 1,000 CIOs will be under orders to craft AI value playbooks: manuals for measuring the business impact of these algorithms.
And IDC predicts that by 2029, over half of top CEOs lacking a clear AI strategy could find themselves out of a job, as regional IT spending soars towards US$1.123 trillion in 2026.
