of UK Government Digital Service (GDS) is expanding its AI accelerator program after its first year as departments look to build internal AI and machine learning capabilities rather than relying on external support.
This initiative reflects a broader shift to practical, role-based AI skills development across public sector organizations.
Since its launch in March 2025, 49 civil servants have completed the program. The program focuses on upskilling existing personnel into technical roles such as data science and machine learning engineering.
The latest cohort brought together 25 participants from 17 public sector organizations, with projects spanning chatbots, large-scale language models, search extension generation, and machine learning systems.
The program is structured around hands-on learning, with participants developing and presenting practical AI solutions rather than focusing solely on theory.
One participant described the experience as “one of the most rewarding learning experiences I’ve had since joining the civil service.”
This approach addresses the growing demand for applied AI skills, especially in environments where teams are required to design, test, and deploy systems within operational constraints.
Departments move toward ownership of AI capabilities
In response to strong demand, GDS is now introducing self-funded sectoral cohorts, which will allow individual organizations to run a customized version of the program to suit their priorities.
The Northern Ireland Statistics and Research Agency (NISRA) is the first to pilot this model, which includes a pathway from data analyst to data scientist.
This move suggests that departments are seeking more control over how AI skills are developed, especially as use cases become more specific to operational needs.
The AI Accelerator includes multiple promotion routes, covering not only the transition from data analyst to data scientist, but also the path for engineers to transition into AI-focused roles.
The program focuses on learning-by-doing and embedding skills within teams, as well as the leadership and organizational support roles that enable AI adoption.
As demand increases, the move to flexible, department-driven cohorts illustrates how public sector AI capabilities are evolving from centralized programs to a more decentralized model where teams build and apply skills directly within their own environments.
