Key takeaways

AI is reshaping how central banks use human capital. Two scenarios illustrate possible trajectories: “AI copilots”, which augment staff, and “AI agents”, which could autonomously perform defined tasks. Copilots are already in use, while agents may emerge over the next decade. Both scenarios require upskilling, new technical roles and strong governance. Human oversight remains essential. Central banks must also attract scarce AI-related talent and foster cultures that support innovation.

Introduction

AI is expected to change job design, workflows and skill requirements in central banks. Tasks such as real-time forecasting, financial stability monitoring and transaction verification will increasingly rely on AI tools. Staff will need to interpret, validate and refine AI outputs. Workforce planning has become more complex, with 83% of central banks reporting increased difficulty. Talent shortages in AI-relevant skills, combined with fast-changing technologies, underline the need for adaptable strategies. The report focuses on the HR implications of two AI development scenarios: copilots that enhance human work, and agents that can autonomously execute tasks.

Scenario descriptions

In the first scenario, LLM-based copilots assist staff with tasks such as coding, report drafting, data analysis and internal chatbot functions. These tools extend human capability but do not replace roles. Output formats include text, code, images and audio. Staff continue to lead decision-making, while copilots reduce routine workload and improve efficiency.

In the second scenario, more autonomous AI agents could perform specific tasks with limited human involvement, such as producing real-time forecasts or verifying central bank transactions. These agents would interact directly with computers and handle dynamic data inputs. Current beta versions show mixed performance, indicating uncertainty about future capability. Despite potential role substitutions, human oversight remains necessary to ensure ethical, legal and policy alignment, and new tasks will emerge in monitoring and supervising autonomous systems.

How will AI change central bank workforces?

Both scenarios require new role profiles and continuous skill development. Roles involving repetitive tasks may diminish, while demand grows for ML engineers, data engineers, AI ethics officers and specialists in governance. Staff in economics, statistics, law, finance, IT and HR will need to use AI tools effectively and understand their limitations.

Upskilling and reskilling will be ongoing, particularly in scenario one, where staff must learn to integrate AI into daily work. Scenario two requires deeper technical competencies, including system supervision and data management. Governance frameworks covering ethics, privacy, accountability and compliance must be established in both scenarios, with more stringent ex ante requirements for autonomous agents.

AI-related human capital challenges

Nearly 90% of surveyed central banks reported increased recruitment difficulty. Hiring is particularly challenging for cybersecurity, IT, fintech, data science and AI/ML roles, largely due to competition from higher-paying private sector employers. Perceived limited career progression also deters candidates with technological expertise. Central banks may improve attractiveness by emphasising mission-driven work, access to unique datasets and opportunities for training.

Internal capability gaps are a key concern. Some experienced staff may struggle to adopt new tools quickly enough. Successful integration requires targeted training that differs by scenario: collaboration-oriented training for copilots and advanced technical training for agent-based workflows. Change management strategies should communicate the benefits of AI, address potential disruption and support team and individual development planning.

Managing capability gaps: legal and regulatory limitations and approaches

Central banks employ varied approaches to address skill shortages, including recruitment, upskilling and use of consultants. Reliance on external contractors can fill short-term gaps but may challenge continuity, culture and security. Legal constraints limit recruitment flexibility for 58% of institutions, including sourcing requirements (47%) and citizenship requirements (43%). A balanced workforce strategy combining permanent staff with targeted external support is recommended.