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AI-driven incentives and rewards framework


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Added by:   OECD analyst
Added on:   06 Oct 2026
Updated by:   OECD analyst
Updated on:   06 Oct 2026

The Ministry of the Interior introduced an AI-enabled initiative to support a permanent system of incentives and rewards for public employees, based on key performance indicators (KPIs). The initiative uses AI-supported digital tools to help link individual and organisational performance with measurable results, while decisions remain under human oversight. It was developed to strengthen performance-based rewards and promote fairness, transparency and motivation across public administration.

Name in original language

Εφαρμογή πάγιας διαδικασίας κινήτρων και ανταμοιβών των υπαλλήλων, μέσω Κρίσιμων Δεικτών Απόδοσης (KPIs) με την αξιοποίηση ΤΝ

Initiative overview

This initiative was launched to support the implementation of a permanent, performance-based system of incentives and rewards for public employees grounded in measurable results. It builds on the performance management framework introduced by Law 4940/2022, which established goal-setting, performance evaluation and the systematic use of KPIs across public administration.

While this framework generated structured performance data, an additional step was required to translate performance outcomes into fair, transparent and consistent incentive mechanisms. The initiative addresses this need by supporting the structured use of KPIs as the basis for incentives and rewards, reinforcing the link between organisational objectives, individual contribution and measurable outcomes.

Its objectives include improving objectivity and consistency in reward allocation, strengthening motivation and accountability, and enhancing trust in performance-based rewards. The framework operates across different types of public entities while preserving managerial responsibility and ensuring that all incentive-related decisions remain under human oversight. It functions not only as a remuneration mechanism but also as a management instrument supporting a performance-oriented organisational culture.

Artificial Intelligence is used strictly as a decision-support tool to analyse performance data, identify trends and provide structured insights to managers. AI does not automate decisions on incentives or rewards; rather, it supports informed judgement by facilitating consistent interpretation of KPIs and performance results. This approach is aligned with the Ministry’s broader strategy for the responsible and human-centric use of AI and builds on earlier AI-supported initiatives in goal-setting and performance evaluation.

Implementation is supported through the development of a dedicated digital solution following a competitive procurement process, designed to integrate with existing HRM and performance management systems. This integration supports scalability, interoperability and consistent application of KPI and reward criteria across public administration.

Governance arrangements, common definitions and guidance mechanisms are incorporated to ensure uniform implementation and reduce fragmentation. The project is financed by the Recovery and Resilience Facility, reflecting its strategic role in modernising performance management practices.

Over time, the initiative is expected to become a core component of the public-sector performance management architecture. It builds directly on the first implementation cycle of the goal-setting and evaluation framework and represents the next step in linking performance measurement with incentives and rewards. Continuous refinement based on performance data and implementation feedback supports a more results-oriented, transparent and motivating administrative culture.

Other relevant details

Results, outcomes and impacts: The initiative is under implementation. Initial outcomes include the establishment of a structured digital framework linking incentives and rewards with KPIs, alongside common performance indicators and governance rules supporting consistency across public entities. Progress is monitored through implementation milestones, system-development deliverables, validation of KPI definitions and reward criteria, and managerial oversight mechanisms. Expected outcomes include improved objectivity and transparency in reward allocation, stronger alignment between performance results and motivation, and more consistent application of performance-based incentives across public administration. Challenges and lessons learned: The Ministry of the Interior identified challenges in designing and implementing a performance-based incentive and reward system across a diverse public administration. Key risks included defining KPIs that are meaningful, comparable and fair across organisational contexts, ensuring acceptance by managers and employees, and safeguarding transparency and legal compliance when using AI-supported tools. These challenges are addressed through governance arrangements, common KPI definitions, and human-in-the-loop design, ensuring that all incentive-related decisions remain under managerial responsibility and are aligned with data-protection and AI-related legal requirements. AI use is limited to decision-support functions, analysing performance data without automating outcomes. Early experience highlights the importance of institutional ownership, stakeholder engagement and clear communication. Conditions for success include reliable data, user training, legal safeguards and continuous refinement.

About the policy initiative


Category:

  • AI policy initiatives, programmes and projects

Initiative type:

  • AI use cases/projects in the public sector

Status:

  • Active

Start Year:

  • 2023

OECD AI Principles:

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Other relevant urls:

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