UK productivity remains a longstanding economic challenge, with policymakers consistently positioning AI as a key lever for growth and competitiveness.
Snowflake’s findings show AI investment and experimentation amongst businesses though impact so far is varied. 45% of UK organisations say AI is delivering early gains or in specific use cases, though 23% are already seeing it delivering productivity improvements at scale. Buoyed by this thought, most organisations expect AI investment to increase over the next 12 to 24 months, with just 1% planning to decrease spend. Businesses continue to back thetechnology as a strategic priority, demonstrating confidence that productivity breakthroughs will come.
The UK AI Report
Conducted by YouGov on behalf of Snowflake, the report surveyed 500 senior decision-makers including CEOs & CFOs from large UK organisations, spanning key industries including public sector, manufacturing and financial services. These industries are seen as being vital to the Government’s AI and productivity ambitions. Its 2025 AI Opportunities Action Plan aims to boost the UK economy by £47 billion annually, estimating that widespread AI adoption could increase national productivity by up to 1.5% each year.
Dr Fabian Stephany, Economist & Departmental Research Lecturer at the Oxford Internet Institute (OII), University of Oxford commented: “I am encouraged to see early evidence that AI is beginning to generate measurable productivity gains for UK firms. Since the introduction of generative AI, many observers have been asking when these gains would materialise, and the findings suggest that this moment may now be arriving. This is consistent with what research would predict: technological breakthroughs rarely translate immediately into productivity improvements, as organisations need time to adapt their workflows, governance structures and capabilities.“
From AI Promise to Productivity Reality
The data suggests that while belief in AI’s potential is strong, execution at scale is proving more complex. Findings indicate that the primary obstacles to AI-led productivity are not technological. Instead, organisations point to structural and operational barriers as factors slowing the move from pilots to enterprise-wide transformation.
Top barriers include a lack of skilled workforce, poor data quality, organisational silos and unclear leadership or strategic direction. Technology itself ranks below many of these internal challenges, cited by just 19% of respondents. Responsibility for AI governance is also often fragmented across executive, technology, data and business leaders. While executive leadership typically holds responsibility for investment, there is no clear governance owner, limiting accountability and slowing decision-making.
This suggests that many UK organisations are pursuing AI at a measured pace, building progress through smaller, targeted use cases while strengthening internal structures, with broader productivity gains likely to follow as foundations mature.
In debates about national productivity, AI is positioned as a growth engine. For business leaders, these gains will manifest themselves at both their top and bottom line with cost reduction as a clear goal. Nearly half (44%) say that cost reduction matters most as a key measure of success, while 26% say the same of revenue growth.
The Executive Confidence Gap
The research also reveals cautious confidence on AI deployments among senior leaders. Only 24% of organisations say AI initiatives are identified and prioritised using a rigorous framework aligned to business objectives. Meanwhile, 40% expect AI to take two years or more to materially improve productivity.
Around 60% say ethics and safety concerns influence their decisions to adopt and scale AI. This reflects a responsible approach to deployment, particularly in regulated and risk-sensitive sectors.
Jennifer Belissent, Principal Data Strategist, Snowflake, said: “UK organisations clearly believe in AI’s long-term potential, and continued investment runs parallel to this belief. This research shows, however, that belief alone is not enough. Productivity gains require clear ownership, strong data foundations and alignment between AI initiatives and measurable business objectives. AI has the potential to be a real driver of UK productivity and economic growth. But unlocking that potential depends on getting the fundamentals right – governance, data and clear accountability.”
A Varied Industry Picture
The research highlights clear differences in AI maturity and confidence across key UK industries, although productivity gains remain uneven.
- Financial services is more advanced on governance and strategic alignment, but regulatory and reputational concerns are slowing the move from structure to scale.
- Manufacturing shows strong belief in AI’s long-term productivity potential, yet expects slower returns due to skills gaps and integration challenges.
- Retail lags on confidence and delivery, with AI often confined to isolated use cases amid persistent data quality issues and fragmented ownership.
In the public sector, organisations are the most risk-aware and governance-led, but also anticipate longer timelines before productivity gains are realised.
- 53% cite safety & reliability of AI outputs as the top concern affecting confidence in AI.
- Two thirds (66%) say ethics and safety significantly shape adoption decisions.
- 52% say AI will not materially improve productivity for at least two years.
While this cautious approach prioritises trust and accountability, it may mean productivity gains take longer to come to fruition.
Turning Point for UK Enterprise AI
Across industries, many are still realising how best to drive AI productivity at scale and the skills needed to make this a reality. While levels of governance maturity and risk appetite differ, the journey to broader productivity gains is shared.
Dr Stephany added: “The report’s finding that skills shortages are a key barrier to adoption strongly resonates with findings from my research group (SkillScale) at the Oxford Internet Institute, University of Oxford. AI systems are only as powerful as the people who develop, maintain, apply and govern them. In SkillScale’s research, we find that workers with AI-related skills command a wage premium of around 23% in the UK, have higher chances of finding a job, and are more likely to receive additional job benefits. These patterns reflect the strong and growing demand for talent capable of working with artificial intelligence. Expanding access to AI skills and training will therefore be critical if organisations want to sustain and scale these productivity gains and ensure that the benefits of AI are broadly shared.”
Jennifer Belissent concluded: “The research paints a clear picture. The foundations for AI success in the UK are in place. Organisations are investing, experimenting and strengthening governance frameworks. However, to close the gap between ambition and measurable productivity gains, businesses need stronger alignment, clearer ownership and more robust data foundations. If AI is to play the transformative role policymakers and business leaders expect, the focus must now shift from experimentation to disciplined execution.”
Methodology
The research was conducted by YouGov on behalf of Snowflake among 500 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.
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- Data & AI
- Digital Strategy