UAE Ranks Second Globally in 5G AI Workload Capacity, Ookla Finds
Ookla report: UAE ranks second globally in 5G AI workload capacity, behind Singapore. 2025 data from 22 markets highlights the country’s network readiness.
The UAE has secured the second spot worldwide for 5G AI workload capacity, underscoring the maturity of its mobile infrastructure for artificial intelligence applications. The ranking, published by Ookla and based on measurements collected during 2025, places the UAE behind only Singapore in the speed and reliability of 5G for handling AI processing demands. This result signals growing network readiness for latency-sensitive and compute-intensive AI services across public and private sectors.
Ookla report places UAE second worldwide
The Ookla study evaluated how well 5G networks in major markets can support the compute and data flows required by AI workloads. The UAE’s performance reflects both high-throughput connections and consistent latency characteristics that are important for real-time AI use cases. Ookla’s analysis compared 22 countries, and the UAE finished directly after Singapore in the overall ranking.
The report drew on network measurements taken through 2025 to model the capacity of 5G links to sustain AI-driven tasks. Those measurements considered factors such as peak throughput, sustained speeds under load, and latency variability. By aggregating these metrics, Ookla produced a comparative index intended to reflect practical readiness for deploying AI services over mobile networks.
How the ranking was measured
Ookla’s methodology focuses on end-to-end performance metrics rather than theoretical peak speeds from equipment vendors. Tests included repeated throughput samples, upload and download stability checks, and latency logging under different traffic conditions. These real-world measurements provide a clearer picture of how a network will behave when AI models are run at the edge or when large datasets are transferred to cloud inference services.
The 22 markets sampled in the analysis span Asia, Europe, the Americas and the Middle East, allowing for a broad comparative view. Singapore and the UAE emerged at the top due to a combination of dense 5G coverage, modern radio access networks, and robust backhaul and core network configurations. Other markets in the study ranged from established European networks to fast-growing deployments in Southeast Asia and Latin America.
Technical factors behind the high score
Key drivers for the UAE’s ranking include widespread 5G deployment, investments in fiber backhaul, and improvements in core network architecture. Low latency and steady throughput are particularly important for AI workloads that require rapid model inference or federated learning across distributed nodes. The UAE’s network operators have accelerated upgrades to support higher traffic volumes and lower jitter, which improves AI workload reliability.
Edge computing capacity and distributed datacenter presence also contributed to the strong showing. Deploying compute resources closer to mobile users reduces the round-trip time for AI processing, enabling applications such as augmented reality, computer vision, and industrial automation to function with tighter real-time constraints. These infrastructure elements, coupled with ongoing spectrum management, help explain the UAE’s performance.
Impact on industries and AI deployment
A high 5G AI workload capacity directly benefits sectors that rely on low-latency, high-throughput connectivity. Healthcare systems can run image analysis and remote diagnostics with faster turnaround times, while financial services can leverage real-time risk analytics and fraud detection over mobile networks. Smart city initiatives, including traffic management and public safety systems, stand to gain from more responsive AI-enabled services.
Enterprises exploring mobile-first AI applications are likely to view the UAE as a favorable environment for pilots and rollouts. Faster, more reliable 5G links mean developers can move AI processing to the edge or use hybrid edge-cloud models with reduced delay and improved user experience. This capability may accelerate innovation in sectors from logistics and retail to energy and transport.
Regional comparison and global peers
While the UAE ranked second, Singapore retained the top position for 5G readiness to support AI workloads. Several Nordic and Asian markets also placed strongly, reflecting long-standing investments in next-generation mobile infrastructures. The report highlights a growing divide between markets with deep fiber and core upgrades and those still expanding basic 5G coverage.
Within the Middle East and North Africa region, the UAE’s standing underscores a competitive advantage that could attract international AI developers and technology investments. The country’s performance contrasts with other markets where 5G adoption is progressing but where backhaul or core upgrades remain incomplete, limiting effective support for high-demand AI tasks.
Next steps for UAE’s 5G and AI ecosystem
Maintaining and improving this ranking will require continued investment in spectrum allocation, densification of radio sites, and expansion of edge compute footprints. Policymakers and operators will need to coordinate on regulatory frameworks that support secure, scalable AI services over mobile networks. Strengthening partnerships between telecom providers and cloud or AI vendors can also drive innovative deployments that fully utilize the country’s 5G capabilities.
Operators and enterprises should prioritize use cases that demonstrate clear public benefit and commercial viability, leveraging the UAE’s strong network base to scale effectively. Ongoing measurement and transparency will be important as well; regular performance assessments can help identify bottlenecks and guide targeted infrastructure upgrades.
The Ookla finding provides a measurable signal that the UAE is well-positioned to support next-generation AI services over 5G, but sustaining that advantage will depend on continued technical upgrades and collaborative policy action.