DSIT has no systematic mechanism for bringing together learning from pilots and there are few examples of successful at–scale adoption across government. At the time of the NAO report (March 2024), levels of AI use in government were low, but 70% of surveyed government bodies were piloting or planning AI tools. Examples of pilot activity include use of AI to analyse digital images to identify and classify objects, use of natural language processing to summarise or draft text, and use of AI to assess trends and patterns and monitor live data. More recently i.AI has developed a suite of tools to support civil servants with tasks including minute taking and analysis of consultation responses. However, there is so far little evidence of successful adoption at scale. To grasp the opportunities of AI, government must learn from these pilots, identify the most promising examples, and where appropriate, help drive adoption at scale so the whole of the public sector can take advantage. However, there is no systematic mechanism for bringing together the learning from all the pilot activity across government and disseminating it. We welcome the recent publication of the Evaluation Taskforce’s guidance for evaluating the impact of AI tools, and DSIT’s commitment to piloting an AI Knowledge Hub to bring together good practice and learning in one place. However, without concerted effort and leadership from DSIT, government risks duplication of effort and cost from siloed pilot activity. recommendation To learn from AI pilots and support the scaling of the most promising use cases DSIT should: a. set up a mechanism for systematically gathering and disseminating intelligence on pilots and their evaluation b. Set out how it will identify common and scalable AI products and support their development and roll–out at scale 6