Is data maturity a key foundation for AI-ready public services?

The Government Digital Service (GDS) and The National Archives have joined together to explore how public sector legal data can be prepared for artificial intelligence

The GDS and The National Archives show a growing consensus that successful AI adoption depends not only on technology, but on the quality, governance and management of data.

The project, which concluded its discovery phase in April 2026, examined whether legal information held by The National Archives, including legislation and case law, could be effectively used in AI systems.

Following encouraging results, the GDS and The National Archives project is now moving into an Alpha phase to test practical approaches and explore how data maturity can reduce the risks associated with AI.

Why data maturity matters

Data maturity refers to an organisation’s ability to manage, understand and govern its data effectively. It looks at data quality, leadership, governance processes, staff skills and organisational culture.

While AI tools often attract attention for their capabilities, experts increasingly recognise that the reliability of AI outputs depends heavily on the data they are trained on or connected to.

Poorly managed or poorly understood data can undermine the most advanced AI systems.

The projects decided that AI readiness should begin with an assessment of data maturity, ensuring organisations have strong foundations before introducing new technologies.

One of the most significant findings was that The National Archives’ legal data is already close to being AI-ready. Researchers found that the organisation benefits from high-quality data, strong leadership, robust governance frameworks, and specialist expertise.

This combination means that both the information itself and the systems surrounding it meet the standards required for responsible AI use.

The findings reinforce the idea that data quality alone is not enough. Organisations must also have the right people, processes and culture in place to support the effective use of AI technologies.

Keeping up with rapid technological change

The The GDS and The National Archives project also highlighted the challenge of operating in a fast-moving AI landscape. Major technology companies and governments around the world are investing heavily in AI development, making it difficult for public sector organisations to predict which solutions will remain relevant over time.

Rather than immediately building new AI services, the partnership focused on understanding long-term opportunities that are less likely to become outdated as technology evolves.

This approach helped identify areas where government can provide unique value, particularly in developing standards and methods for assessing the reliability of AI-generated information.

A key opportunity identified during the discovery phase is the need for stronger tools and frameworks to evaluate AI outputs.

As AI systems become more widely used in public services, ensuring that their responses are accurate, trustworthy and consistent will become more important. The The GDS and The National Archives project suggests that the government is well positioned to lead efforts to create validation standards rather than competing directly with private-sector AI developers.

The discovery also showed the benefits of cross-government collaboration. To explore the use of Model Context Protocol (MCP), an open-source standard that connects AI systems with external data sources and tools, GDS partnered with the Department for Business and Trade and the Ministry of Justice.

With the project now entering its next phase, the lessons learned are expected to influence future government guidance on preparing public sector data for AI. GDS also plans to launch an updated data maturity service, building on its original 2023 framework, providing a model that could be applied across government departments and public bodies.