A new SAS report with research insights by IDC uncovers what’s powering the organisations 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.
According to 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. Fewer than one in 20 trustworthy AI “laggard” organisations reported the same.
“When AI works, it’s incredibly impactful,” says 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.”
Chris Marshall, vice-president at IDC, adds: “As AI becomes more autonomous, organisations face a new challenge: maintaining confidence in systems people don’t fully understand. Our findings show that stronger oversight, explainability, accountability, and data foundations are becoming prerequisites for scaling AI successfully.”
South Africa’s country findings show one of the strongest year-on-year improvements in AI trustworthiness. The local Trustworthiness Index rose 23.9 points to 67.9 in 2026, while the trust gap narrowed from 35.6 points to 8.1. All five trustworthiness dimensions now sit above their respective global benchmarks. On returns, 39% of South African organisations expect strong or high ROI per dollar invested in AI, with a further 35,6% expecting moderate returns.
“South Africa has made real progress in building the governance foundation needed for AI, particularly in banking and among larger listed organisations,” says Joy Naidoo, country leader of SAS South Africa. “The challenge is spreading that discipline more widely. For organisations moving AI into production, the quality of the data and the way systems are governed have to keep pace with adoption.”
The report’s findings span three themes:
#1 AI that can’t explain itself is a major business liability
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. 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.
Key global findings include:
- 97,2% of users globally override AI-generated recommendations in at least some cases.
- The number one reason employees decided to override AI, regardless of whether its output was considered correct, was when the AI could not provide an explanation behind its decision.
- Trust falls from 76% for generative AI to 66% for agentic AI, highlighting growing concerns as AI systems gain more autonomy.
South Africa shows a different override pattern. Inadequate context was the leading local reason for overriding AI recommendations at 35,1%, while 21,1% cited unsafe or inappropriate outputs. The country findings point to a need for better context and stronger guardrails around AI used in production.
#2 Trustworthy AI practices drive business success
The report exposes a widening ROI divide between organisations that prioritise trustworthy AI practices and those that do not. The findings suggest organisations gaining the most value from AI are not necessarily deploying different technologies, but instead managing AI differently.
Key global findings include:
- Organisations investing in trustworthy AI measures are 15 times more likely to report strong or high ROI on their AI projects (62% vs. 4%).
- Organisations with the strongest trustworthy AI practices realise 1.85 times greater gains across 13 different business outcomes, including revenue growth, cost savings and customer experience.
- 85% of these AI leaders with trustworthy practices are increasing their investment in this area by more than 10% this year, actively widening the performance gap.
#3 Too many organisations are losing time and money to weak data foundations
Most organisations are deploying AI on severely underdeveloped or outdated data and data infrastructure. Without a strong data foundation to support crucial transparency and explainability, organisations struggle to govern AI effectively and realise value.
Key global findings include:
- Only 17,5% of enterprises have a fully optimised data infrastructure mature enough for the demands of agentic AI, which negatively impacts performance.
- Organisations with an optimised data foundation are four times more likely to expect strong ROI from AI projects – and six times more likely to mandate the data quality and explainability controls necessary to build trust.
Locally, Data Quality & Governance has become the leading reliability priority, rising from 16,2% in 2025 to 71,2% in 2026. The improvement is substantial, although the country analysis shows that capability remains uneven, with leading banks and JSE-listed organisations ahead of much of the mid-market.
“That unevenness affects how readily organisations can scale AI,” says Naidoo. “The strongest local organisations have already put much of the groundwork in place. Across the wider market, good data practice and governance need to become part of everyday delivery so that promising AI projects have a stronger foundation when they move beyond the pilot stage.”
Take a deeper dive
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 highlights industry use cases and findings that demonstrate how leaders in each of these industries around the globe are approaching AI.
South African country insights compare a 2025 baseline of 50 organisations surveyed in June 2025 with 59 organisations surveyed in April 2026. These country insights are supplementary to the global report.
Key global findings 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.
- 41% 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.
- 23% of life sciences organisations have scaled AI company-wide – the highest of any industry.