Recommendation 19

HM Government Accepted

4. PAC conclusion: DSIT has no systematic mechanism for bringing together learning from pilots and there are few examples of successful at–scale adoption across government. 4a. PAC recommendation: To learn from AI pilots and support the scaling of the most promising use cases DSIT should: • set up a mechanism for systematically gathering and disseminating intelligence on pilots and their evaluation; and 4.1 The government agrees with the Committee’s recommendation. Target implementation date: May 2026 4.2 DSIT is establishing a number of workstreams to create a structured process for gathering and sharing insights from AI pilots (branded as the Prime Minister’s AI Exemplars), including those built by the Incubator for AI (i.AI). Across a variety of AI use cases and public services, these workstreams will collect insights from pilots of both commercial and DSIT own- build AI tooling, conducting rigorous evaluation to identify the conditions and common patterns that enable successful scaling. 4.3 Led by the Public Sector AI Adoption programme, these learnings will be synthesised into patterns for implementation, including best practice guides and case studies to help service teams build the government’s collective capacity to maximise the potential of AI for better outcomes and avoid duplication. Bringing a systematic approach to evaluating AI’s impact on delivering better public services for citizens, and productivity. 4b. PAC recommendation: • set out how it will identify common and scalable AI products and support their development and roll–out at scale. 4.4 The government agrees with the Committee’s recommendation. Target implementation date: May 2026 4.5 DSIT is well positioned, in terms of both its remit and its specialist capabilities, to enable more successful scaling within departments and across organisational boundaries, ultimately realising better outcomes for government and for citizens from these technology investments. 4.6 A proposal is currently being developed in the Public Sector AI Adoption programme with the aim to build maturity and capability within government as a whole to be able to effectively scale AI initiatives past pilot stage. This work would include creating the resources and capability to: • Assess maturity and capability across government departments and synthesise into a government-wide picture, in order to validate understanding of blockers & prioritise work to resolve them. • Effectively identify core components best suited to scale and roll out to a wider audience. • Catalogue and create (or advocate for) targeted interventions to resolve common bureaucratic blockers to timely scaling, to include: procurement frameworks and skillsets; information governance processes; Digital, Data and Technology (DDaT) recruitment and funding. • Guidance agreed with HM Treasury to evaluate impact consistently and rigorously - enabling departments to reliably access funding. 4.7 The first part of this proposal will be to decide scope, secure funding, and build a minimal viable product of cross-cutting technical components to be built and maintained by the digital centre of government.