AI maturity in United Kingdom organisations

Artificial intelligence (AI) is transforming industries by unlocking new possibilities in innovation, operational efficiency, and decision-making. From enhancing customer experiences to optimising processes, AI is becoming an essential component for organisations aiming to maintain competitiveness in a digital-first economy. The UK’s unique regulatory landscape and market dynamics further shape how AI is implemented, offering both challenges and opportunities for businesses. Understanding these barriers will help UK businesses move strategically with AI, enabling them to increase their AI maturity.

Findings are based on research conducted by Iron Mountain alongside independent market research specialist Vanson Bourne. Data in this report is based on 200 IT and data decision-makers in the UK, who have knowledge or involvement in their AI strategy. You can read the global report here.

Three key takeaways:

• The UK is less AI mature than the global average, with only 7% of those in the UK among the most mature
• Despite the limited AI maturity, the UK is focusing on moving towards advanced AI technologies in the next two years, including retrieval augmented generation (RAG) and generative AI
• There’s currently a limited focus on integrating unstructured data with AI in the UK, with fewer than the global average feeling data from unstructured sources is important to the success of their organisation’s AI strategy (49% vs an average of 56%) 

The UK’s perspective on AI

There are a couple of social-economic reasons organisations in the UK may be lagging in AI maturity, but regulations such as GDPR and the EU AI Act play into this. In fact, the EU AI Act is a regulatory framework created specifically to ensure safe and ethical development and deployment of AI systems by categorizing AI applications by risk levels and imposing stricter requirements on those ‘high-risk’. These acts are causing organisations to become more cautious about trying new technologies such as AI, to avoid breaking any regulations and being fined.

However, regulations and frameworks can’t explain why the UK is so far behind other European countries. Looking at the organisations that are most mature, the UK includes only 25%, while both Germany and France have at least 50% more (38% in Germany, 43% in France). This begs the question, outside of regulations, what else is holding the UK back from AI adoption and maturity?

The divergence in technology priorities among UK organisations may stem from foundational infrastructure insufficiencies rather than regulatory barriers. Unlike the global trend, UK businesses have differing opinions on what could help accelerate the adoption of AI initiatives and maximise value. They place less emphasis on increasing automated data governance and compliance reporting tasks (29% vs. 43% globally) or having robust AI-focused security protocols in place (25% vs. 39% globally). Instead, their priorities lie in scaling IT capabilities to handle large data volumes (46%), providing a clear vision for AI initiatives (44%), allocating more resources to AI expertise and project development (38%), and identifying and addressing sustainability challenges in AI integration (38%).

In fact, UK organisations are primarily using AI to reduce costs (57%) and enhance decision-making (50%). What’s more, they have much less focus on improving customer experience (47%) or innovation of new products (42%) than the global trend (58% and 57% respectively).

By focusing less on automation and security protocols and more on scalability, expertise, and sustainability, UK organisations may inadvertently be slowing their path to AI maturity. Bridging this gap will require aligning strategic priorities with global best practices while addressing the UK’s unique technological and cultural factors. Without this alignment, the UK risks falling further behind its European counterparts in realising AI’s full potential.

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