- 53% of UK organisations surveyed say regulation and governance accelerate and enable more confident AI adoption
- Despite better use of data also being seen as central to AI success (45%), data quality is called out as the top barrier to productivity (31%).
- Responsibility for internal AI governance is fragmented across leadership teams, slowing AI adoption and value realisation
Snowflake, the AI Data Cloud company, today announced new findings from its UK research revealing how trusted data and strong governance are becoming key accelerators of AI adoption across organisations. However, while regulation and governance are giving businesses greater confidence to deploy AI responsibly, challenges around data quality and accountability are preventing many from scaling its impact.
In a survey of 500 senior decision-makers in large UK organisations, conducted by YouGov on behalf of Snowflake, more than half (53%) of respondents report that regulation and governance are actually advancing AI adoption and enabling its more confident and stable use. At the same time, 40% cite regulatory, legal or reputational risk as an important consideration when adopting and scaling AI, highlighting the importance of trust in shaping how organisations deploy and scale the technology.
While governance is increasingly seen as a positive foundation for AI adoption, organisations are still encountering practical barriers that impede progress. Data quality is cited as the biggest challenge to improving organisational productivity (31%), with organisational silos and poor collaboration coming in close behind (17%). This is despite respondents stating that better use and integration of data is essential to unlocking AI’s potential (45%). These findings reinforce that the growth and success from AI can only be achieved by having a strong and robust foundational data strategy.
Data and Ownership Gaps Limit Progress
A broader tension underpins these findings. Organisations recognise that while strong data foundations and clear accountability are key for AI success, many have yet to embed these consistently across the business. This gap between understanding and execution could slow progress, as fragmented ownership and inconsistent approaches delay the transition from experimentation to sustained impact and long-term value.
The research also highlights a cautious, but increasingly confident approach to AI adoption. Over 60% of organisations say ethics and safety concerns influence their decisions to adopt and scale AI, reflecting the growing importance of responsible deployment. This reflects the UK’s wider ambition to accelerate AI adoption in a way that supports growth, productivity and better public services, while maintaining trust, transparency and accountability. This balance is particularly evident in the public sector, where governance and assurance can extend timelines for impact, but are essential to building confidence in long-term transformation.
Dr Jennifer Belissent, Principal Data Strategist, Snowflake, said: “UK organisations are building the right foundations for AI success, with governance and trust frameworks increasingly seen as enablers rather than barriers. However, to turn that progress into real outcomes, organisations need to address the fundamentals. Strong data foundations, clear ownership and alignment between AI initiatives and business objectives will be critical to scaling impact. The opportunity is clear, but realising value will depend on execution.”
Challenges in Scaling Impact
The research findings show that internal responsibility for AI governance is often divided across executive, technology and data leaders, with no clear owner, slowing decision-making and making it harder to scale initiatives. This builds on Snowflake research from earlier in 2026, which showed that while UK organisations are investing heavily in AI, most are still in the early stages of realising productivity gains at scale. 23% have successfully achieved productivity improvements across many use cases, while 45% report early or modest gains.
This reinforces a consistent pattern: the potential for AI is clear, however leaders must address the obstacles so it can be deployed in a way that delivers sustained, organisation-wide impact. Many organisations are taking a measured approach, building confidence through smaller use cases while strengthening internal foundations such as governance, data and skills. With that experimentation – the experience it brings and the opportunity it provides to build that foundation – companies will close the gap between ambition and delivery.
Dr Fabian Stephany, Economist & Departmental Research Lecturer at the Oxford Internet Institute (OII), University of Oxford commented:“It is encouraging to see that UK business leaders have such a positive mindset towards AI adoption. Snowflake’s research findings suggest that technology itself is no longer the main barrier. Instead, policy and governance can be powerful levers for helping firms scale AI. This includes encouraging a shift in mindset within firms, so that employees are explicitly supported and encouraged to experiment with AI in their day-to-day work.”
Stephany continued: “Many companies remain hesitant because they lack secure infrastructure or overestimate the cost of putting it in place. Here, government support, policy initiatives and partnerships with larger technology firms can help to bridge this gap. The same is true for upskilling – governments, education providers and tech companies can work together to offer short courses, in-house training and microcredentials that give workers credible signals of their AI skills.”
Methodology
The research was conducted by YouGov on behalf of Snowflake. Results are based on information obtained from 500 respondents who are senior decision-makers from large UK organisations with 250 or more employees across manufacturing, financial services, retail, the public sector and other industries. Fieldwork was conducted in January 2026.
Learn more at snowflake.com
