APAC AI Decoded — What the 2026 EY Sentiment Study Means for CEOs

Analysis by Prabjeet Singh Anand. CEO, PeopleCentral. Founder, AI CEO Brief. 20 years building businesses in Singapore. This analysis draws on the EY APAC AI Sentiment Study 2026 and applies it to the Singapore context. Primary source references are listed at the end.

What EY Found

EY surveyed 1,200 C-suite executives across Australia, China, India, Japan, Singapore, and Southeast Asia between January and March 2026. The study was designed to measure AI adoption sentiment, investment intent, and confidence in AI's ability to deliver measurable returns.

The headline finding is straightforward: confidence in AI is high. 84% of respondents said they believe AI will be a major source of competitive advantage in their industry within three years.

But the more interesting finding is buried in the second layer of the data.

When EY separated respondents by whether they had already deployed AI at scale versus those still in planning or pilot stages, the confidence numbers diverged dramatically. Leaders who had deployed AI at scale were not just more confident — they were deploying faster, investing more, and reporting measurable returns. Those still planning were more cautious, less committed on investment, and more likely to cite "lack of clarity on ROI" as the reason for delay.

The confidence gap is not about personality or risk appetite. It is about evidence. Companies with deployed AI have evidence. Companies still planning do not.

The Confidence Gap

EY's data shows a bifurcation across APAC that should concern Singapore CEOs.

The gap between leaders and followers on measurable ROI is the critical number: 71% versus 18%. This is not a difference in access to technology. Every company surveyed had access to the same AI tools. The difference is that leaders deployed, tested, measured, and scaled. Followers are still waiting for more certainty before they start.

"The companies reporting the strongest AI returns in 2026 are not the ones with the best technology strategy. They are the ones who started earliest and learned fastest."

What Leaders Do Differently

EY identified five consistent behaviours in companies reporting the strongest AI returns.

1. They started with workflows, not platforms

AI leaders consistently identified a specific workflow problem first, then selected technology to solve it. AI followers consistently selected a platform first and then tried to find use cases. The direction matters — it determines whether AI is solving a real business problem or creating a new one.

2. They tested in 14 days, not six months

Leaders ran short, focused tests with clear success criteria before scaling. The average test cycle for AI leaders in EY's study was 11–17 days. Followers reported average pilot periods of 4–7 months — long enough for energy to dissipate and stakeholder support to erode.

3. The CEO was the sponsor

In 82% of AI leader companies, the CEO was personally identified as the primary AI champion. In follower companies, AI was owned by IT (41%) or an innovation team (31%). Organisational ownership matters. AI deployed without CEO sponsorship stalls at the first resistance point.

4. They communicated changes before they happened

Leaders briefed their teams on AI changes in advance, framing the change around what would be different and what would not change. Followers either deployed without communicating or communicated after deployment. The result in follower companies was predictable: resistance, workarounds, and adoption rates that failed to capture the expected time savings.

5. They documented every investment

Leading companies maintained consistent documentation of AI investments, outcomes, and methodology. This was not primarily for tax purposes — but the Singapore EIS 400% deduction is a direct consequence of the discipline these companies had already built. Documentation-first companies will capture the deduction. Others will not.

The Singapore Signal

Singapore-based respondents showed a specific pattern in EY's data worth noting for local CEOs.

Singapore respondents were more likely than the APAC average to be aware of government AI support schemes (68% vs 54% APAC average). They were also more likely to have engaged with EnterpriseSG or IMDA for AI guidance (43% vs 29% APAC average).

But awareness of support schemes did not translate to action. Singapore respondents who were aware of the EIS AI deduction but had not yet claimed it were asked why. The top three answers:

1. "Waiting for more clarity from IRAS on what qualifies" — 38%
2. "Not sure our AI spend reaches the qualifying threshold" — 29%
3. "CFO or finance team not yet briefed on the scheme" — 24%

All three of these barriers are information problems, not resource problems. The clarity is available. The qualifying threshold is S$50,000 — most SMEs with any AI investment are near or at it. And the CFO briefing takes 30 minutes.

The gap between Singapore companies aware of the 400% deduction and those capturing it is not a gap in intent. It is a gap in execution.

Three Findings That Matter Most for Singapore CEOs

Finding 1 — The window for fast-follower advantage is closing

EY's data shows the performance gap between AI leaders and followers compounded significantly between 2024 and 2026. In 2024, the measurable ROI gap was 31 percentage points (leaders 52%, followers 21%). By early 2026, that gap had grown to 53 percentage points (leaders 71%, followers 18%).

Compounding gaps are not linear. Companies that are behind now will find it harder — not easier — to close the gap in 2027. The Singapore EIS deduction window, which closes at the end of 2027, is an explicit policy mechanism to encourage action now. The government designed it to reward companies that move, not companies that wait.

Finding 2 — Small AI investments outperform large AI investments at this stage

Counter-intuitively, EY found that companies reporting the strongest early AI returns had made smaller, more targeted investments than companies reporting weak returns. The median AI investment for high-ROI APAC companies was S$45,000–S$85,000. The median for low-ROI companies was S$180,000+.

The explanation is straightforward. Large AI investments are typically platform replacements or major transformation programmes. These take months to implement, have complex change management requirements, and often fail to deliver expected returns. Small, targeted intelligent layer investments deploy in weeks, produce measurable results, and build the internal capability that makes the next investment more likely to succeed.

This directly maps to the EIS qualifying envelope. The S$50,000 cap is not a limitation — it is a signal. It is calibrated to the investment size that produces results.

Finding 3 — The workforce communication problem is underestimated

EY asked employees in companies undergoing AI deployment to rate how well they were informed about AI changes. 61% of employees in follower companies said they had received little or no advance communication about AI tools being deployed in their workflow. In leader companies, that number was 19%.

More strikingly: in follower companies, 44% of employees reported actively finding workarounds to avoid using AI tools their company had deployed. In leader companies, that number was 11%.

Adoption rates drive ROI. A company that spends S$50,000 on an AI layer that 44% of its team avoids will report poor returns. A company that spends the same amount and achieves 89% adoption will report strong returns. The difference is not the technology. It is the communication before deployment.

What This Means for You — Three Actions This Month

Action 1 — Identify which category you are in
Use the EY framework honestly. Have you deployed AI at scale in at least one workflow and measured the result? Or are you still planning? If you are in the planning stage, the data says the cost of continued delay is compounding. One decision this month to run the four-question filter across your workflows changes your trajectory.

Read also: The Intelligent Layer Framework gives you the exact four-question filter to identify your first AI workflow.

Action 2 — Brief your CFO this week
EY's data shows 24% of Singapore companies aware of the 400% deduction have not yet briefed their CFO. Send your CFO the CFO Briefing Pack today. The barrier is not the scheme — it is the 30-minute conversation that has not happened yet.

Read also: Singapore AI Tax Deduction: The CEO Checklist has the qualifying spend criteria and documentation template for the EIS 400% deduction.

Action 3 — Communicate before you deploy
The workforce communication finding is the most actionable data point in EY's study. Before any AI tool goes live in your business, your affected team should know: what is changing, why it is changing, what it means for their role specifically, and what is not changing. This is not a nice-to-have. It is the difference between a 44% workaround rate and an 11% workaround rate.