TLDR: The UK government has significantly increased its spending on artificial intelligence and digital transformation, with AI-specific contracts soaring by over 1,000% since 2018. Despite this substantial investment, a new analysis by SAS and Tussell warns that poor data quality and accessibility pose a major risk, creating a “government data divide” that could hinder the nation’s AI ambitions and reduce billions in investment to mere pilot projects rather than widespread progress.
The United Kingdom government has dramatically ramped up its investment in artificial intelligence (AI) and broader digital transformation initiatives, with spending on IT and AI projects increasing by 72% since 2018. A recent analysis by data and AI leader SAS, in collaboration with public procurement specialists Tussell, reveals that AI-specific contracts have seen an even more staggering rise of over 1,000% during the same period, including a sharp 64% increase in the last year alone. This surge reflects the government’s commitment to positioning the UK as a global leader in AI innovation.
Government procurement for digital transformation projects reached an impressive £18.9 billion in 2024, a significant jump from £11 billion in 2018. The Department of Health and Social Care emerged as the highest digital investor in 2024, allocating £1.45 billion, nearly £450 million more than the next largest buyer, the Home Office, which spent £1.01 billion. Other substantial contributors to digital spending include the Department for Transport, the Department for Work and Pensions, Defra, the Metropolitan Police Service, the Department for Education, and HM Treasury.
However, despite these headline figures, experts are sounding the alarm over a critical impediment: the “government data divide.” This term describes the significant gap between the high-quality, shareable data required for successful AI implementation and the current state of government data. Dr. Iain Brown, Head of AI & Data Science at SAS Northern Europe, emphasized this concern, stating, “Our analysis shows that data quality and access remain the biggest barriers to scaling successfully – which puts the government at risk of a growing data divide.” He further elaborated on the necessity of treating data as a fundamental asset: “To deliver AI at a national scale, data must be treated as critical digital infrastructure: planned, governed and maintained with the same rigour as physical assets like transport or energy. Without it, our report suggests, billions in AI investment risk becoming a collection of pilots rather than a platform for service-wide progress that will benefit UK citizens.”
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The report underscores that while the ambition and investment are present, the practical effectiveness of these projects is being hampered by inadequate data readiness. To overcome this challenge and build trust in government AI systems, the analysis recommends careful attention to data quality, the establishment of robust sharing standards, and the secure development of digital infrastructure. Furthermore, synthetic data is highlighted as a safe and effective method to accelerate these crucial goals. Dr. Brown concluded, “As the government delivers on its AI and digital strategies, addressing the data divide will be critical to realising the UK’s vision for trusted, citizen-focused AI. Synthetic data as part of the approach gives the government a practical, safe way to accelerate that progress and ensure that public trust in the technology grows alongside public-sector innovation.”
