The latest from SAS for you;
UK organisations are moving from isolated AI experimentation to enterprise-wide deployment faster than anywhere else in the world, but the payoff hasn’t followed. A new SAS report developed with research insights from IDC finds that the future success of AI in the UK will depend on converting trust and oversight into measurable business outcomes.
The second edition of the Data and AI Impact Report: The New Economics of Trust surveyed 2,699 decision-makers across 28 countries.
The share of UK organisations describing their AI approach as integrated or transformative more than doubled, from 29% to 60% in a year, the fastest such transition recorded for any country in the study, while those whose AI strategy takes a short-term view fell from 40% to 7.1%. Three-quarters of UK organisations (75.3%) now plan to increase AI investment over the next 12 months as they look to continue momentum.
Trust foundations rose alongside adoption. The UK’s Trustworthiness Index, a measure of the governance, data and oversight practices that prove AI reliability, climbed from 58.2 to 60.5. But its AI Impact Index, a measure of realised business value, reached just 51.7, 8.8 points behind.
The UK’s Trustworthiness Index gained 2.3 points year-on-year, slower growth than Germany (+8.1), Italy (+7.6) or the United States (+8.4) recorded over the same period, while the global average rose by 11.6 points overall, from 49.7 to 61.3. The result is that the global average now sits fractionally ahead of the UK’s own score, at 61.3 versus 60.5.
But it isn’t all catch-up. The UK’s Trust Gap, the distance between what people believe AI can do and what governance can actually demonstrate, narrowed to 7.2 points, tighter than the US (7.3), Spain (9.2), Germany (10.4), France (13.1) and Italy (14.1). That doesn’t mean UK governance is the most developed of these markets as the UK’s own Trustworthiness Index remains below the global average. However, it means UK organisations’ confidence in their AI is now the most closely matched to what their governance can actually deliver.
And while the UK’s own payoff is still catching up, it’s moving in the right direction: the UK’s Impact Index rose 3.5 points this year, while Spain’s fell 7.9 points and France’s fell 6.1 points over the same period, despite both markets also strengthening their governance.
Commenting on the findings, Dr Iain Brown, Global Head of AI and Data Science at SAS, said:
“UK organisations are moving faster than any other market we studied, replacing isolated AI experimentation with enterprise-wide deployment. It shows real intent.
“Right now, organisations can show they’re moving fast on adoption, but that speed isn’t yet converting into business results. The fix starts with the data underneath the AI: until that foundation is strong enough to support real explainability, the UK’s trust score will keep outpacing what AI can actually deliver.”
Data quality: A binding constraint
Data Quality & Governance is the UK’s weakest dimension, scoring 56.5, the lowest of any of the major markets compared in this study, behind Italy (57.1), Germany (57.4), France (58.1), Spain (60.3) and the United States (65.8), and 3 points below the global benchmark of 59.5.
Awareness of the problem isn’t the issue however; the share of UK organisations naming data quality a critical factor for AI reliability jumped from roughly 20% to 69.3%, the most cited factor in this year’s results.
Globally, only 17.5% of organisations have reached a fully “optimised” data infrastructure; 53.9% of UK organisations now sit at managed or optimised level, slightly ahead of the 52% global figure, but progress on full optimisation has been slow everywhere.
Explainability: The widest gap to the global benchmark
Explainability & Fairness scored 57.1 against a global benchmark of 60.4, the UK’s widest shortfall against the benchmark of any dimension, at 3.3 points and behind Germany (60.6), Spain (63.0), France (58.2) and the United States (68.2), though narrowly ahead of Italy (57.0).
This isn’t a problem unique to the UK: globally, “lack of explanation” is the single most common reason people override AI recommendations (34.5% of respondents), and Explainability & Fairness improved less than any other trust dimension worldwide over the past year.
“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.”
Impact trailing trust: Governance without outcomes
The UK’s AI Impact Index reached 51.7 in 2026, still 8.8 points behind its Trustworthiness Index. Globally, organisations with trustworthy AI practices are 15 times more likely to report strong or high ROI than those without (62% vs. 4%) – but it doesn’t guarantee that the impact will match if issues like data quality and explainability aren’t resolved.
Funding is not the obstacle
A commitment to invest is there. The share of UK organisations expecting only limited change in AI investment fell from 34.5% to 18.7% this year. What’s missing is the scale of returns to match. Organisations need to address issues around data quality, explainability and governance for this investment to deliver returns. If those shortcomings aren’t addressed and gaps persist in 2027, boards may begin to question where future AI investments should go.
Read the Data and AI Impact Report: The New Economics of Trust here.
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