What happened
Emirates 24|7 reports that Dubai Police deployed 36 robotic process automation robots across administrative and operational functions after completing 104 technology projects over the past year. The force also reviewed an AI platform, a smart assistant used in Smart Police Stations, and reported service-continuity rates above 99.9%.
Emirates 24|7 reports that Dubai Police completed 104 strategic and operational technology projects during the past year. The report says the work was reviewed by Lieutenant General Abdulla Khalifa Al Marri during an annual inspection of the General Department of Artificial Intelligence.
According to the outlet, 36 robotic process automation robots were deployed across administrative and operational functions. Dubai Police said the robots accelerate procedures, increase productivity and reduce routine workloads, allowing personnel to focus on more specialized responsibilities.
The report also describes an AI transformation plan covering policing, administrative and operational activities. It says the Dubai Police AI platform supports data analysis, process automation and AI-powered tools for employees and customers, while a smart assistant operates in Smart Police Stations to support round-the-clock services.
Emirates 24|7 reports that Dubai Police recorded 99.97% public-service continuity and 99.92% system continuity during the year. These figures, the number of robots and the description of their impact are reported claims from Dubai Police relayed by the outlet and were not independently confirmed in the supplied material.
Source details: emirates247.com ↗
Why it matters
The report describes a concrete public-sector deployment in which AI-enabled automation is being integrated into policing, administrative work and public services. If sustained, such systems could reduce repetitive workloads and speed service delivery, but the article does not establish how much human work has been replaced, whether performance improved against a baseline, or how the systems are governed in high-stakes policing contexts.
The deployment is notable because it places AI-related automation inside a large public-service and policing organization rather than limiting it to a pilot or research setting. Administrative automation may reduce repetitive processing and help staff concentrate on tasks requiring human judgment.
The practical significance depends on where automation is used. Process automation for back-office work carries different risks from AI tools used to prioritize cases, interpret data or interact with the public. The source does not specify whether any of the 36 robots make or recommend consequential policing decisions.
The report provides operational metrics, but it does not provide a baseline, methodology or independent audit for the continuity figures. It also does not quantify productivity gains, response-time changes, cost savings or error reductions, so the scale of the claimed benefits remains unclear.
What to watch next
Key unknowns include the robots’ vendors, underlying systems, specific tasks, deployment costs, access controls, error rates and oversight arrangements. Further reporting should establish whether the reported continuity figures were independently audited and whether the smart assistant or other AI tools affect decisions involving residents, complaints, investigations or frontline policing.
Future disclosures should identify the tasks assigned to each robotic process automation system, the technologies and vendors involved, and whether the systems are rule-based automation, generative AI, or a combination of tools.
Oversight will be important if the AI platform or smart assistant handles personal data, public complaints, investigative information or decisions affecting residents. The supplied report does not describe data-protection measures, human review requirements, testing, incident reporting or appeal mechanisms.
It is also unknown whether the systems are available outside Dubai Police, what they cost, how many personnel use them, or whether the reported continuity rates continued after deployment. Independent evidence would help distinguish reliable operational improvement from institutional self-reporting.