SAS: Southeast Asia leads in trustworthy AI investments

Source: SAS landing page.

A new SAS report* with research insights by IDC has uncovered what’s powering the organisations winning the race to profit from their AI investments: embracing trustworthy AI measures. Southeast Asia has emerged as the strongest-performing region in trustworthy AI, exceeding global benchmarks across all five dimensions of trustworthiness while rapidly increasing adoption of more autonomous AI systems.

Trustworthy AI is defined as AI designed to be reliable, fair, secure, up to regulatory standards, and able to clearly show how it arrived at a decision. Users and decision-makers at all levels within an organisation must be able to hold an AI system to a predetermined chain of accountability for incorrect or missing AI output. Any AI system must also be governed and proven to be in compliance with clear rules.  

The 2nd annual Data and AI Impact Report: The New Economics of Trust has found that organisations investing in trustworthy AI measures are 15x more likely to report strong or high return on investment (ROI). 

Southeast Asia's Trustworthiness Index rose 8.8 points to 66.5 in 2026, while its Trust Gap narrowed from 14.6 points to 6.6 points. The region was the only market in the study to outperform the global benchmark across all five dimensions of trustworthy AI, putting Southeast Asian organisations in a strong position to capture the business benefits associated with more trustworthy AI. 

A trust gap is defined as the difference between what people believe AI can be trusted to do, and what AI can demonstrably prove it can do reliably and safely—creating both risks and opportunities for organisations. 

However, the findings highlight a critical next phase for the region: ensuring that infrastructure, ongoing oversight and measurable business impact keep pace with its AI ambitions. 

“When AI works, it’s incredibly impactful,” said Bryan Harris, CTO at SAS. 

“However, it is well documented that state-of-the-art agents can have error rates that exceed 25% on complex tasks** – which is unacceptable in high-stakes decision-making. In order to achieve accuracy and repeatability, organisations must embed domain expertise into agentic workflows, while keeping people at the centre of governance and oversight. Organisations that do this successfully will close the trust gap and gain a competitive advantage in the market with AI.” 

“Organisations in Southeast Asia that invest in building genuine AI capability will be better positioned to earn trust and lead in an AI-driven market,” said Deepak Ramanathan, VP, Customer Advisory at SAS. 

“The region’s next challenge is turning its gains in trustworthiness into measurable impact. Explainability becomes increasingly important as autonomous AI expands; through advanced analytics, we understand how AI is being utilised throughout organisations, where potential risk areas exist, and what policy says regarding deployment, to allow leaders to progress more quickly while maintaining control of what is being deployed,” he added. 

“As AI becomes more autonomous, organisations face a new challenge: maintaining confidence in systems people don't fully understand,” said Chris Marshall, VP at IDC. 

“Our findings show that stronger oversight, explainability, accountability and data foundations are becoming prerequisites for scaling AI successfully.” 

Researchers found that at many organisations, employees are increasingly hesitant to rely on systems that may or may not be able to offer correct output or explain how AI arrived at a final decision. As AI gains autonomy, this liability grows, making explainability crucial for success. 

The report also explored a major hurdle to success in AI adoption: when employees' lack of trust in AI decisions leads them to override and make manual corrections. In Southeast Asia, the leading reasons for overriding an AI recommendation were insufficient explanation (37.8%) and lack of situational context (37%). This only perpetuates the AI trustworthiness deficit, and can cost organisations time, productivity and profitability. 

When AI decision-making is only as good as the data it’s based on, building a strong data foundation becomes pivotal for organisations looking to reduce override rates, SAS said. 

The region's Trustworthiness Index increased from 57.7 in 2025 to 66.5 in 2026, while perceived trust remained broadly stable at 73.1. This means the narrowing Trust Gap was driven primarily by stronger capabilities rather than lower expectations. 

All dimensions improved: 

- Data quality & governance: 66.7, up 10.7 points 

- Model governance & oversight: 64.2, up 14 points 

- Explainability & fairness: 63.7, up 6.5 points 

- Responsible AI policy: 71.2, up 9.8 points 

- Audit & accountability: 70.5, up 11.3 points  

Despite rapid progress in trustworthiness and AI maturity, the region's infrastructure is progressing at a slower pace. AI ambitions are outpacing infrastructure readiness, with advanced AI maturity rising 20.5 points versus 4.1 points for infrastructure maturity. This potential infrastructure gap is particularly significant as organisations move toward agentic AI, SAS noted. 

Meanwhile, investment intentions are rising, with 65.6% planning a small increase in AI spending over the next 12 months and 14.8% planning a large increase. 

Stronger trust has yet to translate into stronger ROI, according to the report. Southeast Asia's Trustworthiness Index improved significantly, but its Impact Index remained almost flat, falling slightly from 58.3 to 58.0. The share of organisations reporting strong or high ROI also fell from 36.7% to 28.7%, suggesting that investments in trustworthy AI have yet to translate consistently into measurable business returns. 

This underscores the growing global recognition that trustworthiness is not simply a governance consideration, but a critical enabler of AI adoption, performance and business value, SAS said. 

The region's governance gains also come with a warning. While its Audit & Accountability score increased 11.3 points to 70.5, the proportion of organisations conducting regular AI audits or impact assessments fell from 47.3% to 21.3%. As AI becomes more autonomous, organisations will need to pair governance frameworks with regular verification to ensure that AI systems continue to operate as intended, SAS recommended. 

Report highlights include: 

- Banking leaders are going beyond compliance, treating robust AI governance as a competitive advantage and operational necessity - 85% of AI leader banks have established governance frameworks, compared to just 29% of laggards. 

- Forty-one percent of public sector leaders are increasing trustworthy AI investment by more than 20% in the year ahead, which is as fast as the most ambitious organisations across any industry. 

- About a quarter (23%) of life sciences organisations have scaled AI company-wide – the highest of any industry. 

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Get the report at sas.com/ai-impact

*The findings are based on a global survey of 2,699 decision-makers with knowledge of or influence over their company's data and AI initiatives. The survey was conducted across 28 countries and four focus industries: banking, insurance, life sciences and the public sector. The report also highlights industry use cases and findings that demonstrate how leaders in each of these industries around the globe are approaching AI.  

Southeast Asia is reported as a sample-weighted composite of Singapore, Malaysia and Thailand, based on 120 respondents in 2025 and 122 in 2026.  

Within the study, organisations were scored out of 100 against five dimensions of trustworthy AI. The report’s trustworthy AI leaders were organisations with an average total score of 80 or higher. 

**Stanford HAI, 2026 AI Index Report; independent AI agent benchmark evaluations.