중동 및 아프리카의 데이터센터 GPU : 시장 점유율 분석, 업계 동향과 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the Middle East and Africa data center GPU market size is projected to expand from USD 0.92 billion in 2025 and USD 1.10 billion in 2026 to USD 2.02 billion by 2031, registering a CAGR of 12.99% between 2026 and 2031.

This report is Segmented by Deployment Type (Cloud Data Centers, Enterprise, and More), GPU Type (Training GPUs, and Inference GPUs), Interconnect (PCIe-Based GPUs, High-Bandwidth Interconnect GPUs), Workload Type (AI and ML, HPC, and More), and End-User (Hyperscalers/CSPs, Enterprises, Government and Research Institutions). Market Forecasts are Provided in Terms of Value (USD).

Middle East and Africa Data Center GPU Market Trends and Insights

Accelerated Adoption of Generative AI and Large Language Models in Gulf Sovereign Initiatives

The Middle East and Africa data center GPU market is being pushed forward by sovereign AI programs that moved adoption windows from traditional multi-year cycles into much shorter deployment schedules. Saudi Arabia's HUMAIN initiative partnered with xAI in January 2026 to deploy Grok-3 inference clusters across Riyadh and Jeddah, with a target of 50,000 concurrent Arabic-language queries by Q3 2026.In the UAE, G42 operated a 200-megawatt AI campus in Masdar City that housed NVIDIA GB200 NVL72 racks designed for models with 1.8 trillion parameters, which placed the facility at a scale previously associated with U.S. hyperscalers. Morocco also moved into this pattern when the Nexus AI factory was announced with NVIDIA in November 2025, with a plan for 500 megawatts of GPU capacity by 2028 and a North African role in French and Arabic language model deployment. These projects matter because they absorb GPU supply faster than enterprise buyers that still move through quarterly budget approvals and compliance reviews. The result is a hardware mix that shifts toward training as well as inference, because localized language models require regional datasets, dialect support, and deployment under local legal and cultural frameworks.

Rapid Hyperscale Cloud Expansion Backed by Sovereign Wealth Funds

The Middle East and Africa data center GPU market is also benefiting from sovereign wealth fund capital that lets hyperscalers secure land, power, and hardware earlier than peers in many other regions. Microsoft announced a USD 15.2 billion commitment to UAE AI infrastructure with G42 in March 2025, including a 200-megawatt expansion scheduled by the end of 2026. In Qatar, the Brookfield-Qai joint venture broke ground in February 2026 on a 100-megawatt compute center in Doha under a broader USD 20 billion commitment, with projected power costs of USD 0.06 per kilowatt-hour. Amazon Web Services expanded its Bahrain region with 3 additional availability zones in January 2026 and added GPU-optimized EC2 P5 instances based on NVIDIA H200 Tensor Core GPUs. This funding model removes the financing bottlenecks that often slow large cloud projects, which is why several MEA campuses moved toward operating status far faster than the longer timelines common in global builds. It also widened the addressable base of the Middle East and Africa data center GPU market, because capacity is being prepared not only for sovereign projects but also for enterprise tenants that need local hosting and AI acceleration.

High Power And Cooling OPEX In Desert Climates

The Middle East and Africa data center GPU market faces a direct cost challenge because desert facilities can operate at power and cooling costs above USD 0.12 per kilowatt-hour, while the global hyperscale average is near USD 0.06 per kilowatt-hour. A 10-megawatt GPU cluster running at 90% utilization in Riyadh or Abu Dhabi can incur annual electricity costs of USD 9.5 million, compared with USD 4.7 million for a comparable facility in Northern Europe. Extreme heat also forces operators to over-provision chillers by 30% to 40%, which pushes cooling capital expenditure to USD 1,200 per kilowatt against USD 800 per kilowatt in more temperate locations. Liquid-cooling systems can improve efficiency, but the HPE and Khazna partnership highlighted that these designs require specialized fluids and corrosion-resistant infrastructure that raise rack-level deployment costs. Waste-gas-to-power projects can help in selected oilfield locations, but they are not a region-wide answer because site selection, permitting, and construction are tightly constrained. This cost pressure is particularly severe for inference applications where revenue per query is very small, so operators need better power contracts, alternative energy arrangements, or higher-value workloads to protect margins in the Middle East and Africa data center GPU market.

Other drivers and restraints analyzed in the detailed report include:

1. Hardware Innovation Cycle Toward High-Bandwidth Memory and Multi-Chip Module GPUs
2. Sovereign GPU Allocation Agreements Skewing Supply in Favor of MEA Projects
3. Semiconductor Export Restrictions Limiting High-End GPU Supply to Some African Countries

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Cloud data centers held 57.39% of deployment-type revenue in 2025, which gave them the largest share of the Middle East and Africa data center GPU market size within this segment set. That position reflected hyperscaler strength in training workloads, centralized compute, and batch analytics across major Gulf campuses. Edge data centers are still expected to grow faster through 2026-2031 because field operations and urban service nodes are prioritizing local processing for response-sensitive use cases. Saudi Aramco deployed 12 edge GPU pods across the Ghawar and Safaniya oilfields in Q1 2026, and each pod contained 64 NVIDIA L40S inference GPUs for real-time seismic processing and drill-bit optimization. That example shows why edge deployments are becoming more practical in energy operations, where waiting for a centralized cloud response can reduce the value of the analysis. The Middle East and Africa data center GPU market is therefore widening beyond centralized campuses and into distributed environments that support industrial inference close to assets.

Enterprise and private data centers remained the second-largest deployment type because regulated industries still prefer direct control over data placement and compute resources. The UAE Central Bank issued guidance in August 2025 that required domestic banks to process customer transaction data within national borders, which pushed institutions such as Emirates NBD and First Abu Dhabi Bank toward private GPU systems. This type of regulatory push supports on-premise deployment even when cloud offerings are technically available. Edge sites also face higher per-rack capital costs, because rugged enclosures, redundant power, and remote connectivity requirements make these systems more complex to install. Even so, operators continue to fund them where real-time decision making in oil and gas fields, smart-city nodes, and transport corridors produces a clear operational return. That balance between centralized scale and local responsiveness is likely to keep all 3 deployment types relevant as the Middle East and Africa data center GPU market continues to expand.

Inference GPUs held 59.86% of GPU-type revenue in 2025, which made them the leading product category in the Middle East and Africa data center GPU market. Their growth profile also remains the strongest through 2031 because lower inference costs changed the economics of deploying chatbots, voice systems, recommendation engines, and localized language services at commercial scale. The decline in per-token inference costs from USD 0.02 in early 2024 to USD 0.0008 by late 2025 was a major reason why real-time Arabic language applications became more viable across public and private deployments. G42 allocated 70% of its 200-megawatt Masdar City capacity to inference workloads in 2025, which shows that demand is now centered on serving users rather than only training frontier models. This demand pattern is especially visible in government portals, translation services, customer support, and enterprise AI tools, where scale depends on transaction cost, not only raw compute capability. The Middle East and Africa data center GPU market is therefore moving from a build-first phase into a serve-at-scale phase for many deployments.

Training GPUs remain essential even though they represent a smaller unit base, because sovereign AI programs still need local models trained on regional legal, medical, and language datasets. NVIDIA stated that H200 pricing sat well above inference-oriented L40S configurations, which keeps training systems concentrated in state-backed campuses and hyperscaler labs rather than broad enterprise rollouts. Saudi Arabia's HUMAIN initiative used 10,000-plus H200 GPUs in a Riyadh facility that went live in January 2026 for Arabic legal and medical language models. This split between training and inference is important because it means revenue growth does not depend on one workload alone. Inference expands unit demand across more users and locations, while training supports a smaller number of very large projects with higher selling prices. That combination gives the Middle East and Africa data center GPU market both breadth and depth across the GPU-type mix.

Complete Report Scope:

• By Deployment Type
  • Cloud Data Centers
  • Enterprise / Private Data Centers
  • Edge Data Centers
• By GPU Type
  • Training GPUs
  • Inference GPUs
• By Interconnect
  • PCIe-Based GPUs
  • High-Bandwidth Interconnect GPUs
• By Workload Type
  • Artificial Intelligence and Machine Learning
  • High-Performance Computing (non-AI scientific computing)
  • Data Analytics (database acceleration, query processing)
  • Graphics and Visualization (VDI, rendering, digital twins)
• By End-User
  • Hyperscalers / Cloud Service Providers
  • Enterprises
  • Government and Research Institutions
• By Geography
  • Middle East
    • Saudi Arabia
    • United Arab Emirates
    • Qatar
    • Rest of Middle East
  • Africa
    • South Africa
    • Nigeria
    • Egypt
    • Rest of Africa

List of Companies Covered in this Report:

1. NVIDIA Corporation
2. Advanced Micro Devices, Inc.
3. Intel Corporation
4. Amazon Web Services, Inc.
5. Microsoft Corporation
6. Google LLC
7. Huawei Technologies Co., Ltd.
8. Dell Technologies Inc.
9. Hewlett Packard Enterprise Company
10. Super Micro Computer, Inc.
11. Cisco Systems, Inc.
12. Arista Networks, Inc.
13. Broadcom Inc.
14. Marvell Technology, Inc.
15. Khazna Data Centers LLC
16. Center3 (stc Data Center Company)
17. G42 Cloud Computing LLC
18. Africa Data Centres (Cassava Technologies)
19. Equinix, Inc.
20. Digital Realty Trust, Inc.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Accelerated Adoption of Generative AI and Large Language Models in Gulf Sovereign Initiatives
  • 4.2.2 Rapid Hyperscale Cloud Expansion Backed by Sovereign Wealth Funds
  • 4.2.3 Hardware Innovation Cycle Toward High-Bandwidth Memory and Multi-Chip Module GPUs
  • 4.2.4 Sovereign GPU Allocation Agreements Skewing Supply in Favor of MEA Projects
  • 4.2.5 Deployment of Waste-Gas-to-Power Data Centers in Middle East Oilfields
  • 4.2.6 Preferential Liquid-Cooling Infrastructure Grants in Desert Campuses
• 4.3 Market Restraints
  • 4.3.1 High Power and Cooling OPEX in Desert Climates
  • 4.3.2 Semiconductor Export Restrictions Limiting High-End GPU Supply to Some African Countries
  • 4.3.3 Chronic DAC/AOC Fiber Lead-Time Bottlenecks for Large MEA GPU Clusters
  • 4.3.4 Scarcity of Local AI Infrastructure Talent Driving Deployment Delays
• 4.4 Industry Value Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Impact of Macroeconomic Factors on the Market
• 4.8 Porter's Five Forces Analysis
  • 4.8.1 Threat of New Entrants
  • 4.8.2 Bargaining Power of Suppliers
  • 4.8.3 Bargaining Power of Buyers
  • 4.8.4 Threat of Substitutes
  • 4.8.5 Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Deployment Type
  • 5.1.1 Cloud Data Centers
  • 5.1.2 Enterprise / Private Data Centers
  • 5.1.3 Edge Data Centers
• 5.2 By GPU Type
  • 5.2.1 Training GPUs
  • 5.2.2 Inference GPUs
• 5.3 By Interconnect
  • 5.3.1 PCIe-Based GPUs
  • 5.3.2 High-Bandwidth Interconnect GPUs
• 5.4 By Workload Type
  • 5.4.1 Artificial Intelligence and Machine Learning
  • 5.4.2 High-Performance Computing (non-AI scientific computing)
  • 5.4.3 Data Analytics (database acceleration, query processing)
  • 5.4.4 Graphics and Visualization (VDI, rendering, digital twins)
• 5.5 By End-User
  • 5.5.1 Hyperscalers / Cloud Service Providers
  • 5.5.2 Enterprises
  • 5.5.3 Government and Research Institutions
• 5.6 By Geography
  • 5.6.1 Middle East
    • 5.6.1.1 Saudi Arabia
    • 5.6.1.2 United Arab Emirates
    • 5.6.1.3 Qatar
    • 5.6.1.4 Rest of Middle East
  • 5.6.2 Africa
    • 5.6.2.1 South Africa
    • 5.6.2.2 Nigeria
    • 5.6.2.3 Egypt
    • 5.6.2.4 Rest of Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
  • 6.4.1 NVIDIA Corporation
  • 6.4.2 Advanced Micro Devices, Inc.
  • 6.4.3 Intel Corporation
  • 6.4.4 Amazon Web Services, Inc.
  • 6.4.5 Microsoft Corporation
  • 6.4.6 Google LLC
  • 6.4.7 Huawei Technologies Co., Ltd.
  • 6.4.8 Dell Technologies Inc.
  • 6.4.9 Hewlett Packard Enterprise Company
  • 6.4.10 Super Micro Computer, Inc.
  • 6.4.11 Cisco Systems, Inc.
  • 6.4.12 Arista Networks, Inc.
  • 6.4.13 Broadcom Inc.
  • 6.4.14 Marvell Technology, Inc.
  • 6.4.15 Khazna Data Centers LLC
  • 6.4.16 Center3 (stc Data Center Company)
  • 6.4.17 G42 Cloud Computing LLC
  • 6.4.18 Africa Data Centres (Cassava Technologies)
  • 6.4.19 Equinix, Inc.
  • 6.4.20 Digital Realty Trust, Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment