Southeast Asian organizations scored above the global benchmark across all five dimensions of a SAS trustworthy-AI index in 2026, but the same regional study found that reported returns and regular AI audits weakened even as adoption accelerated.
The findings come from SAS’s second annual Data and AI Impact Report, which incorporates research from IDC. The global study surveyed 2,699 decision-makers across 28 countries. Its Southeast Asia results are a sample-weighted composite of Singapore, Malaysia and Thailand, based on 122 respondents in 2026, compared with 120 in 2025.
Trustworthiness scores rise across the regional sample
SAS said Southeast Asia’s Trustworthiness Index rose from 57.7 in 2025 to 66.5 in 2026. The gap between perceived trust and measured trustworthiness narrowed from 14.6 points to 6.6 points.
The region improved across each of the study’s five dimensions. Data quality and governance reached 66.7, model governance and oversight 64.2, explainability and fairness 63.7, responsible AI policy 71.2, and audit and accountability 70.5.
SAS said Southeast Asia was the only market grouping in the study to outperform the global benchmark across all five dimensions. Because the regional sample covers Singapore, Malaysia and Thailand rather than every ASEAN economy, the result should be read as a three-market composite rather than a measure of the entire region.
AI maturity is rising faster than infrastructure
The report found a widening gap between AI ambition and infrastructure readiness. Advanced AI maturity in the Southeast Asian sample rose by 20.5 points, while infrastructure maturity increased by 4.1 points.
Spending intentions are still rising. Around 65.6 percent of respondents planned a small increase in AI spending over the next 12 months, while 14.8 percent planned a large increase.
That creates pressure on organizations to strengthen the data, compute and governance systems underneath more autonomous AI. TNGlobal has previously reported how organizations in the region are trying to balance AI adoption with explainability and the ability to prove how AI decisions are made.
Higher trust scores have not yet produced higher returns
The regional Impact Index remained almost flat, slipping from 58.3 to 58.0. The share of organizations reporting strong or high return on AI investment fell from 36.7 percent to 28.7 percent.
The study also found that employees were still overriding AI recommendations when systems could not provide enough context. Insufficient explanation was cited by 37.8 percent of respondents, while 37 percent pointed to a lack of situational context.
Deepak Ramanathan, vice president of Customer Advisory at SAS, said the next challenge for organizations in Southeast Asia is converting stronger trustworthiness into measurable business results while maintaining explainability and control as autonomous systems expand.
Audit frequency falls despite governance gains
One of the report’s more cautionary findings concerns verification. Although the Audit & Accountability score rose by 11.3 points to 70.5, the proportion of organizations conducting regular AI audits or impact assessments fell from 47.3 percent to 21.3 percent.
That decline suggests formal governance frameworks may be improving faster than recurring operational checks. As organizations deploy more agentic systems, the difference could become more important because autonomous workflows can make decisions or take actions with less direct human intervention.
Chris Marshall, vice president at IDC, said stronger oversight, explainability, accountability and data foundations are becoming prerequisites for scaling AI successfully.
The study covers banking, insurance, life sciences and the public sector. Its regional findings offer a useful snapshot of Singapore, Malaysia and Thailand, but the relatively small Southeast Asian sample means year-on-year shifts should be interpreted with care.
MBSB sees data center demand to drive Malaysia’s power capacity upcycle