New report calls for strategic rethink in Government AI adoption

A new briefing published by the Ada Lovelace Institute, titled 'Learn Fast and Build Things: Lessons from Six Years of Studying AI in the Public Sector,' provides an in-depth analysis of the challenges and opportunities associated with artificial intelligence in government.

The report, authored by Anna Studman, Imogen Parker, and Elliot Jones, distils key lessons from over 30 research studies examining AI usage in sectors such as healthcare, education, and social care, as well as broader cross-government applications.

One of the core findings is the necessity for clear and shared terminology around AI technologies. The authors state: "Lack of clear terminology about ‘AI’ is inhibiting learning and effective use. Shared definitions for AI are needed for effective communication, evaluation and to make strategic decisions."

The briefing highlights the pivotal role data quality plays in AI effectiveness: "AI systems rely on data, which is never neutral, often partial, and can encode existing societal inequalities." It advises public sector organisations to critically assess their data sources, ensuring they are comprehensive and accurately represent diverse groups to prevent amplifying biases.

Transparency and governance are also highlighted as crucial factors for successful AI deployment. According to the authors, the public sector's current understanding of AI implementation is "severely lacking," undermining accountability and internal knowledge sharing. The briefing notes, "There remains a persistent, systemic deficit in understanding where and how AI and data-driven systems are used in the public sector."

The report critiques existing public procurement practices, describing them as "not fit for purpose" in the context of AI, highlighting the risk of vendor lock-in and knowledge asymmetries. It calls for structured procurement guidance to enhance fairness and transparency, thus fostering trust and delivering genuine public value.

Further, the briefing emphasises the importance of a sociotechnical approach, stating, "AI systems are not deployed in a vacuum... The success and acceptance of AI tools depend on their interaction with existing social systems, values and trust." This suggests that evaluating AI interventions must extend beyond technical metrics to consider broader societal impacts.

Public acceptance is another essential theme. The briefing states, "Moving out of step with public comfort can undermine the ability for the public sector to effectively use AI." Historical experiences, such as controversies around NHS data sharing initiatives, underline the need to earn and maintain public trust through transparent and ethical AI use.

Finally, the Institute urges government leaders to embrace AI as a tool for reimagining public services rather than merely automating existing processes: "Public sector leaders should see the rollout of AI as an opportunity to reimagine the state, rather than focusing solely on immediate efficiency gains or automating the status quo."

The full report can be downloaded here.