Snowflake’s latest research highlights increasing focus on artificial intelligence (AI) among UK businesses. Despite significant investment, the move toward widespread productivity improvements remains at an early stage. The research, conducted with YouGov, surveyed 500 senior decision-makers across key sectors and examines AI’s role in supporting economic growth.
Many businesses report optimism around AI’s potential, with 23% already seeing productivity improvements at scale and 45% identifying early or use-case-specific benefits. However, organisations also report a range of barriers to broader adoption. These include a lack of skilled workforce, poor data quality, and organisational silos. Technology itself is ranked lower as a constraint, cited by 19% of respondents.
While executive leadership often leads AI initiatives, governance is frequently distributed across functions, which can slow implementation. Only 24% of organisations report using a structured framework to prioritise AI initiatives aligned with business objectives. This suggests that challenges related to structure and alignment are a significant factor in scaling AI, alongside investment levels.
Sector differences are also evident. Financial services shows more developed AI governance but faces regulatory constraints. Manufacturing anticipates slower productivity gains due to skills shortages and integration challenges. Retail reports lower confidence, with AI often applied in isolated use cases alongside ongoing data quality issues.
In the public sector, organisations are taking a more risk-aware approach. Over half cite reliability of AI outputs as a key concern, and ethics plays a significant role in decisions around adoption and scaling. Many organisations expect productivity gains to take two years or more to materialise.
The findings indicate that while AI adoption is increasing, the timeline for measurable productivity improvements varies across organisations and sectors. Commonly cited priorities for improving outcomes include stronger data foundations, clearer ownership of AI initiatives, and enhanced skills and training.
Dr Fabian Stephany highlights AI skills shortages as an important factor influencing adoption and outcomes, noting that individuals with AI-related competencies can experience additional employment benefits.
