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AI STRATEGIC WORKFORCE PLANNING


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Added by:   OECD analyst
Added on:   17 Jul 2026
Updated by:   OECD analyst
Updated on:   17 Jul 2026

The Ministry of the Interior is developing a digital workforce planning tool that supports decision-making based on big data and predictive technologies. The tool analyses demographic trends, retirements, skills and operational needs to produce 5–10 year staffing scenarios. It helps policymakers anticipate future needs, identify skill gaps, compare hiring and reskilling options, and better align staff with organisational goals.

Name in original language

Στρατηγικό εργαλείο προγραμματισμού ανθρώπινου δυναμικού βασισμένου σε τεχνικές τεχνητής νοημοσύνης

Initiative overview

The strategic workforce planning initiative aims to strengthen evidence‑based human resource management across public administration. It responds to long‑standing difficulties in anticipating staffing needs, managing demographic change, addressing skills mismatches and aligning workforce capacity with organisational priorities. By drawing on increasingly available HR, performance and administrative data, the initiative supports a shift from reactive staffing decisions toward forward‑looking workforce planning.

The initiative treats workforce planning as a strategic management function rather than an administrative task. It supports policymakers and managers in planning both the quantity and quality of the public‑sector workforce by identifying current and future staffing gaps, analysing skills requirements and assessing the impact of technological, demographic and economic change on roles and competencies. This approach strengthens alignment between organisational objectives and available skills over the medium to long term. To enable this, a dedicated digital workforce‑planning platform has been developed. The platform integrates demographic information, retirement trends, skills profiles and operational needs, and generates alternative staffing scenarios over a five‑ to ten‑year horizon. Users can compare different policy options, such as accelerated recruitment, internal mobility or targeted reskilling, making the platform a practical simulation tool for evidence‑based workforce‑strategy discussions.

Artificial intelligence and predictive analytics are used strictly as decision‑support tools. They analyse large datasets to identify patterns and forecast potential skills shortages, supporting structured assessment of hiring, mobility and reskilling options. All strategic and operational decisions remain under human responsibility. The initiative is aligned with broader HR digitalisation and performance‑management reforms, ensuring consistency with goal‑setting, evaluation and incentive frameworks. The platform has been developed and piloted in nine public entities, allowing real‑world testing of data integration, scenario generation and usability. Progress has been assessed through validation of data inputs, evaluation of scenario outputs and qualitative feedback from participating policymakers and managers. These pilots provided practical insights and supported refinement before wider deployment.

Other relevant details

Several challenges shaped implementation. Workforce planning requires integrating demographic, staffing, skills and operational data, which varies in quality and interoperability across public entities. Defining common role and skills classifications and supporting acceptance of data‑driven planning among managers also required attention. These challenges were addressed through data standardisation, governance arrangements and a human‑in‑the‑loop design. Pilot deployment helped identify practical issues early and adjust methods before scaling. Key lessons highlight the importance of reliable data, stakeholder engagement and clear communication. The initiative is now in its finalisation phase, preparing for productive operation. Over time, it is expected to scale across public administration, enabling earlier identification of staffing gaps, more evidence‑based hiring and reskilling decisions, improved workforce allocation and reduced long‑term costs. By supporting better role matching, it is also expected to contribute to higher employee satisfaction and more effective public‑sector performance. The development of the digital workforce‑planning platform has been financed through the Recovery and Resilience Facility.

About the policy initiative