A new SAS report with research insights by IDC uncovers what’s powering the global organisations that are winning the race to profit from their AI investments: embracing trustworthy AI measures. Organisations applying trustworthy AI practices were 15 times more likely to report strong return on investment (ROI) from their AI projects.
As identified in the second annual Data and AI Impact Report: The New Economics of Trust, organisations with the strongest governance, data quality and auditability practices – a comparatively small market segment – consistently outperformed peers, reporting at least double the ROI from AI deployments. In comparison, fewer than one in 20 trustworthy AI ‘laggard’ organisations reported the same.
“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.”
“As AI becomes more autonomous, organisations face a new challenge: maintaining confidence in systems people don't fully understand,” said Chris Marshall, Vice President at IDC. “Our findings show that stronger oversight, explainability, accountability and data foundations are becoming prerequisites for scaling AI successfully.”
What is significant is that the report has found trustworthiness in the Oceania region continues to lag behind global benchmarks, despite the trustworthiness index rising by 3.3 points to 59.5 from 2025, and positive movement across all five dimensions of trustworthiness.
With the 2025 Impact score reflecting early optimism about what AI would deliver, the 2026 score offers a more grounded answer, raising considerations around what the next 12 months should look like to improve Oceania’s capabilities.
“While more and more organisations in the Oceania region are adopting ‘Integrated’ or ‘Transformative’ AI programs, rising from 38% to 48.7%, we have observed that the sector’s underlying trust in AI hasn’t kept pace with the market’s ambitions”, said Craig Jennings, Regional Vice President & Managing Director, Asia Pacific at SAS.
“As a result, organisations haven’t been able to sink their teeth into AI, creating a tight, credible trust gap between Oceania. While markets like Australia have faced regulatory considerations and others continue to navigate workforce skills or decisioning challenges, there is a strong opportunity to build AI value across the region. However, its near-term trajectory will depend on whether the market treats 2026 as a floor to build from or a correction to wait out”.
The report’s findings span three core themes:
Close the infrastructure gap behind the impact decline
None of the most advanced large language models used by organisations in Oceania are hosted locally. As a result, organisations routinely stream sensitive data overseas for processing, creating a structural constraint for growth and a sovereignty gap.
The region’s declining Impact Index (-13 points) suggests governance improvements alone will not unlock the next wave of value. For now, scaling these local verification and grounding architectures is the most effective action available, but closing the gap depends on infrastructure investment that no single organisation can make on its own.
A unified approach to tackling AI overrides will drive value
The report 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. 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.
The reasons behind an AI override are already visible in the data, and addressing them is fully within an organisation's control. Addressing factual accuracy, bias detection, and explainability together will reduce the override rate and drive value in AI-driven decisioning.
Building an organisation with the management skills to deploy trustworthy AI
There is a widening ROI divide between organisations that prioritise trustworthy AI practices and those that do not. Global organisations investing in trustworthy AI measures are 15 times more likely to report strong or high ROI on their AI projects (62% vs. 4%).
The findings for Oceania suggest organisations that invest in their workforce, prioritise building expertise, and clearly understand when, how, and why to use AI are gaining the most value. Investing in training alongside technology will help Oceania organisations close this emerging gap.
