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Making AI Work for Britain: From Strategies to Practice

By (author) Alan Brown

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normal price: R 717.95

Price: R 645.95

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| book description |

The UK has made progress in digital transformation by consolidating demand and diversifying supply for digital government. For AI, it has inverted the formula. This will make achieving the UK's goals for AI impossible. This book explains why - and what to do about it. Ministers have committed to making Britain an AI superpower and have identified GBP45 billion in potential productivity savings from digital transformation. But this book argues that without fundamental institutional reform, these ambitions will fail. In 2014 Professor Brown co-authored Digitizing Government with Jerry Fishenden and Mark Thompson. That book challenged the UK to move beyond ""digital as websites"", and it helped to provided important input to both the Government Digital Service and the Government as a Platform reforms. Where those institutional reforms were followed, they worked; where they were not, the government's own data now shows the consequences. According to the UK government's own ""State of Digital Government Review"" (January 2025), only 9% of the country's major technology programmes are rated as being on track for successful delivery. Technology programmes are 60% more likely to be rated ""Red"" than non-technology projects, and only 8% of public sector AI projects show measurable benefits. Professor Brown argues that rather than being technology failures, these are institutional failures in governance, procurement, skills and accountability. ""More capable AI does not fix less capable institutions,"" he writes. ""Strategy documents don't transform countries. Institutions do."" The book proposes five concrete reforms: a statutory AI Coordination Authority modelled on the OBR; outcome-based procurement using the Procurement Act 2023, with mandatory exit provisions; sovereign data infrastructure treated as strategic national investment; a three-level skills pipeline from awareness through professional capability to system leadership; and community impact assessments for every high-stakes public AI deployment.