Dubai adopts AI-powered Workforce Productivity Measurement System across 32 government entities

The initiative connects workforce resources, financial resources and government service outputs to support more efficient operations, resource allocation and future government planning.

Dubai has adopted a unified Workforce Productivity Measurement System across 32 government entities as part of its efforts to strengthen data-driven government operations and improve institutional performance.

The system, developed over five years by the Dubai Government Human Resources Department (DGHR), uses machine learning, advanced artificial intelligence and large-scale data analysis to measure workforce productivity and provide government entities with more accurate insights for planning and decision-making.

The Workforce Productivity Measurement System was formally adopted as a unified government-wide system under Executive Council Resolution No. (67) of 2025.

According to DGHR, implementation has progressively expanded to 32 government entities, creating a common framework for measuring workforce productivity and analysing the relationship between human resources, financial resources and government service outputs.

The system is designed to help government entities regularly monitor productivity indicators, assess resource utilisation and identify opportunities to improve institutional performance.

AI-powered productivity measurement across Dubai government

The Workforce Productivity Measurement System uses advanced analytical tools and digital platforms powered by machine learning and artificial intelligence.

These capabilities allow government entities to process and analyse millions of data points and develop a broader understanding of workforce productivity.

Rather than relying on individual performance indicators, the system connects different categories of government data to examine how resources contribute to outputs and outcomes.

This approach is intended to provide officials with a more comprehensive view of institutional efficiency.

The system can also support the regular monitoring of productivity indicators, allowing government entities to identify trends and assess changes in performance over time.

By using data and advanced analytics, authorities can develop more accurate insights to support planning, policy development and operational decisions.

Dubai’s productivity system developed over five years

Development of the Workforce Productivity Measurement System began in 2020 with a pilot phase involving a limited number of government entities.

The pilot provided the foundation for developing a unified methodology that could eventually be implemented across the Government of Dubai.

As the project progressed, the Workforce Productivity Measurement Steering Committee was established under Resolution No. (7) of 2023.

The committee contributed to the development of the productivity measurement methodology and helped strengthen government entities’ readiness for implementation.

The project was subsequently expanded to additional government entities.

Following Executive Council Resolution No. (67) of 2025, the Workforce Productivity Measurement System was adopted as a unified government-wide system.

The steering committee completed its assigned responsibilities after the adoption of the system and concluded its work.

The five-year development process reflects Dubai’s approach to testing and developing government technology before scaling it across the wider public sector.

System analyses millions of data points

One of the key features of the system is its integrated knowledge base, which has been developed through the analysis of millions of data points.

The data provides the foundation for a unified government methodology for measuring productivity.

The system brings together information related to human resources, financial resources and government service outputs.

This enables government entities to examine how resources are being utilised and how they contribute to the delivery of government services.

The use of artificial intelligence and machine learning provides additional analytical capabilities, allowing large volumes of information to be processed and interpreted more efficiently.

The resulting insights are intended to support more accurate and forward-looking decision-making.

Dubai targets more efficient resource allocation

Improving resource allocation is one of the main objectives of the Workforce Productivity Measurement System.

Government entities require significant human and financial resources to deliver public services. Understanding the relationship between these resources and the outputs they generate can help authorities identify opportunities for greater efficiency.

The system provides a common framework for analysing this relationship.

Government entities can use productivity indicators to assess performance and support decisions about the allocation and utilisation of resources.

This is expected to strengthen planning efficiency while supporting the optimal use of government resources.

The system can also provide information that helps policymakers understand where additional resources may be required and where existing resources could potentially be deployed more effectively.

Data-driven decision-making becomes a central focus

The adoption of the system forms part of Dubai’s broader efforts to build a government driven by data and advanced analytics.

The unified methodology enables government entities to use consistent approaches when measuring workforce productivity.

This can improve the comparability and reliability of productivity information across government entities.

The integrated knowledge base also provides a foundation for government planning and policy development.

By analysing historical and current data, officials can gain insights into institutional performance and use those insights to support future decisions.

The system is therefore designed to move productivity measurement beyond traditional reporting and towards a more data-driven model of government management.

Focus on institutional performance and service quality

The Workforce Productivity Measurement System is not limited to measuring the number of employees or the amount of resources used by government entities.

Its broader objective is to understand the relationship between resources, outputs and outcomes.

This approach allows government entities to examine productivity in the context of overall institutional performance.

Improved productivity analysis can help identify operational inefficiencies and opportunities to enhance government processes.

The system is also expected to support improvements in the quality of government services by providing more accurate information for planning and performance management.

The resulting analysis can be used to inform policy development and operational improvements across government entities.

DGHR highlights strategic importance

Abdullah Ali Bin Zayed Al Falasi, Director General of the Dubai Government Human Resources Department, said the adoption of the Workforce Productivity Measurement System across the Government of Dubai represents a strategic milestone.

He said the system reflects Dubai’s vision of building a government driven by data and advanced analytics.

According to Al Falasi, the system supports policy development, enhances performance efficiency and enables government entities to make more accurate, proactive and impactful decisions.

He also said the system’s impact extends beyond measuring productivity.

The unified methodology is intended to strengthen resource allocation, improve the quality of government services and support sustainable institutional performance.

The initiative is aligned with Dubai’s objective of developing a more agile, efficient and future-ready government.

Supporting proactive government planning

The use of artificial intelligence and machine learning gives the system a forward-looking dimension.

Government entities can monitor productivity indicators and analyse relationships between resources and outputs on a regular basis.

This can provide decision-makers with information that supports both current operational management and longer-term planning.

The availability of large-scale government data also creates opportunities for identifying patterns and trends that may not be visible through conventional reporting.

By incorporating these insights into planning and policy development, Dubai aims to strengthen the accuracy and effectiveness of government decisions.

Dubai expands its data-driven government model

The implementation of the Workforce Productivity Measurement System across 32 government entities represents a significant expansion of Dubai’s use of advanced analytics in public-sector management.

The initiative began with a limited pilot in 2020 and has developed over five years into a unified government-wide framework.

Its adoption under Executive Council Resolution No. (67) of 2025 establishes a common approach to workforce productivity measurement across participating government entities.

The system combines millions of data points with artificial intelligence, machine learning and analytical tools to provide insights into the relationship between government resources and service outputs.

For Dubai, the broader objective is to create a government that can use data more effectively to allocate resources, improve institutional performance and support better public services.

As implementation continues, the Workforce Productivity Measurement System is positioned to become an important component of Dubai’s wider data-driven government strategy, supporting more efficient operations and more accurate, proactive and future-focused decision-making.