Abu dhabi: The Ministry of Human Resources and Emiratisation (MoHRE) has announced the successful completion of approximately 13 million transactions through automation and artificial intelligence (AI) technologies, without human intervention, from the beginning of the year until December 10, 2025.
According to Emirates News Agency, the smart transactions encompassed a wide range of the Ministry's services, marking a significant milestone that underscores its steady progress in integrating AI technologies across all operations. This initiative is part of Phase Two of the Zero Government Bureaucracy (ZGB) programme, aiming to support digital service transformation, enhance the UAE labour market's competitiveness, and contribute to the 'We the UAE 2031' vision.
The Ministry is committed to a sustainable approach in service development by optimally utilising AI solutions, leveraging its robust digital infrastructure, and enhancing workforce skills to manage smart automation efficiently. This is further bolstered by electronic integration with government partners, ensuring ease of business and meeting customer demands for fast, seamless, round-the-clock services.
In a related development, the Ministry revealed the outcomes of its AI-powered system for allocating work permit quotas to establishments. This system supports business growth by streamlining transactions and proactively allocating quotas based on the unique needs and operational status of each establishment, thereby effectively meeting their workforce demands.
The upgraded system reflects the Ministry's ongoing commitment to deploying advanced digital and AI solutions across all operations to achieve operational excellence. It facilitates data-driven decision-making and addresses potential challenges such as time constraints, human error, and ineffective data utilisation.
Between the beginning of the year and October, the system granted around 900,000 quotas to establishments and processed over 11 million transactions through automation and AI. The enhancements have reduced human effort by 56%, automating procedures for approximately 175,000 requests out of 310,000 between February and October. Additionally, the time required for reviewing and approving additional quota requests that do not require human intervention has been reduced by up to 99%, from 10 days to just one second. This improvement significantly enhances the accuracy of outcomes delivered by automation projects.
The system automatically grants initial quotas to establishments, using AI to verify their eligibility and approve quota requests according to their needs. For additional quotas, predictive models are deployed to anticipate requirements and automatically approve some requests. If the AI determines that the quotas are insufficient, the matter is referred to the relevant committee for further review.
The system's self-learning capabilities allow it to continuously improve its decision-making process. By analysing new data and reviewing the operational patterns of establishments, it refines its expectations and determines needs more accurately. Over time, this enhances the quality and precision of the system's outputs.