Public administrations across OECD countries are major employers, yet many are under strain from staff shortages, heavy workloads and fiscal constraints. At the same time, they are responsible for large volumes of administrative and support tasks such as document processing, claims management and citizen information services. Artificial intelligence offers significant potential to support and accelerate these functions, improve service quality and free up staff capacity for more complex and value-adding work. However, limited skills and internal capabilities remain one of the most significant barriers to effective AI adoption in the public sector, making workforce preparedness as critical as the technology itself.
This policy brief examines how AI adoption is reshaping the public sector workforce and outlines strategies that public leaders can use to strengthen AI capabilities within their institutions. Drawing on OECD analysis and examples from across member countries, it highlights how governments are approaching AI in ways that prioritise trust, transparency, accountability and human oversight, while cautiously expanding use cases where the technology demonstrably adds value. Evidence from early adopters shows that AI can substantially reduce administrative burdens, particularly in rule-based processes, while concerns about widespread job displacement in the public sector remain largely speculative at this stage.
The growing use of generative AI tools by public servants has intensified the need for clear governance, training and internal guidance. While many officials already rely on open-access tools to support daily work, unregulated use can create risks related to data protection and compliance. In response, more advanced public organisations are investing in staff training, developing internal AI tools and setting clear rules for responsible use. At the same time, governments face evolving skills needs, with shortages in advanced digital and data expertise alongside a broader requirement for AI literacy among the general workforce. Complementary skills such as critical thinking, problem-solving, collaboration and change management are becoming increasingly important as AI reshapes work processes.
Building sustainable AI capability requires deliberate choices about outsourcing, recruitment and training. While external providers can support specific tasks, developing in-house expertise helps ensure accountability, reduces dependency on vendors and aligns AI systems with institutional priorities. Many governments are also strengthening capabilities through strategic collaborations with start-ups, research institutions and universities, creating ecosystems for experimentation and innovation rather than relying solely on traditional procurement models. Targeted talent programmes and improved career pathways are being used to attract scarce digital professionals, while internal cultures that encourage experimentation, learning and cross-disciplinary collaboration are helping organisations adapt to technological change.
Training plays a central role in preparing the public workforce for AI. Public administrations increasingly offer foundational AI training for all staff, strategic training for leaders and more specialised programmes for digital and data professionals. These initiatives aim to ensure responsible use, compliance with emerging regulations and the effective integration of AI into public services. While resource constraints shape the scale and depth of training, evidence suggests that context-specific, trainer-led and practice-oriented learning is most effective. Over time, the impact of AI training is strengthened when it is embedded within a broader organisational environment that supports continuous learning, innovation and evidence-based evaluation of outcomes.
