Middle East Artificial Intelligence In Healthcare Market Size, Share And Trends Analysis Report By Component (Hardware, Services, Software Solutions), By Application, By End Use, By Technology (ML, NLP), By Country, And Segment Forecasts, 2025 - 2033
Description
Middle East AI In Healthcare Market Trends
The Middle East artificial intelligence in healthcare market size was valued at USD 435.63 million in 2024 and is projected to reach USD 8390.91 million by 2033, growing at a CAGR of 36.99% from 2025 to 2033. Rapid expansion of digital health infrastructure, growing adoption of telemedicine and remote care, and increasing government investments, coupled with national artificial intelligence (AI) strategies, are factors contributing to market growth.
Healthcare systems across the Middle East are undergoing rapid digitalization, harnessing AI integration. Initiatives such as Abu Dhabi’s Malaffi platform, which connects all regional hospitals and clinics via a secure health information exchange, enhance real-time, seamless data sharing. This infrastructure enables AI algorithms to leverage comprehensive, high-quality patient data, significantly improving diagnostic precision, risk stratification, and personalized treatment planning.
In addition, countries such as the UAE and Qatar are investing heavily in smart hospitals, where AI solutions are being embedded into patient care models. The UAE’s National Strategy for Artificial Intelligence 2031 and Saudi Vision 2030 prioritize AI integration in healthcare to increase access, efficiency, and quality of care. Investment in AI research centers, talent development like the Mohamed bin Zayed University of Artificial Intelligence, and collaborations with leading U.S. healthcare institutions foster innovation.
Similarly, in April 2025, Abu Dhabi announced it would launch a pioneering AI and healthcare Innovation Hub through a strategic partnership between Abu Dhabi Health Data Services (ADHDS), SRI International (a Silicon Valley-based R&D leader), and VantageBridge Partners (Abu Dhabi private equity). Thus, the expansion of robust digital health ecosystems enables AI adoption at scale, supporting more efficient healthcare delivery.
Moreover, the rapid adoption of telehealth platforms drives market growth further. For instance, SEHA Virtual Hospital is a flagship example of AI-enabled, hub-and-spoke virtual care that augments specialist throughput. In February 2025, Aster DM Healthcare launched myAster, its flagship digital health platform, in Saudi Arabia at LEAP 2025, expanding from its success in the UAE. The AI-powered app integrates telemedicine, online pharmacies, appointment management, chronic disease monitoring, and health record access.
Furthermore, the regional focus on developing biotechnology hubs and precision medicine accelerates demand for AI-powered research, drug discovery, and personalized therapeutics, driving sustained market expansion. For instance, in April 2025, the Institute for Healthier Living Abu Dhabi (IHLAD) and Singleron Biotechnologies launched AD-Omics, a joint venture to advance precision medicine in the Middle East using AI-driven single-cell multi-omics technologies. Thus, the demand for precision medicine and data-driven tailored treatments underscores the accelerated adoption of AI-driven medical devices in this region.
Middle East Artificial Intelligence In Healthcare Market Report Segmentation
This report forecasts revenue growth at the regional and country-level and provides an analysis of industry trends in each of the sub segments from 2021 to 2033. For this study, Grand View Research, Inc. has segmented the Middle East Artificial Intelligence (AI) in healthcare market report based on component, application, technology, end use, and country:
The Middle East artificial intelligence in healthcare market size was valued at USD 435.63 million in 2024 and is projected to reach USD 8390.91 million by 2033, growing at a CAGR of 36.99% from 2025 to 2033. Rapid expansion of digital health infrastructure, growing adoption of telemedicine and remote care, and increasing government investments, coupled with national artificial intelligence (AI) strategies, are factors contributing to market growth.
Healthcare systems across the Middle East are undergoing rapid digitalization, harnessing AI integration. Initiatives such as Abu Dhabi’s Malaffi platform, which connects all regional hospitals and clinics via a secure health information exchange, enhance real-time, seamless data sharing. This infrastructure enables AI algorithms to leverage comprehensive, high-quality patient data, significantly improving diagnostic precision, risk stratification, and personalized treatment planning.
In addition, countries such as the UAE and Qatar are investing heavily in smart hospitals, where AI solutions are being embedded into patient care models. The UAE’s National Strategy for Artificial Intelligence 2031 and Saudi Vision 2030 prioritize AI integration in healthcare to increase access, efficiency, and quality of care. Investment in AI research centers, talent development like the Mohamed bin Zayed University of Artificial Intelligence, and collaborations with leading U.S. healthcare institutions foster innovation.
Similarly, in April 2025, Abu Dhabi announced it would launch a pioneering AI and healthcare Innovation Hub through a strategic partnership between Abu Dhabi Health Data Services (ADHDS), SRI International (a Silicon Valley-based R&D leader), and VantageBridge Partners (Abu Dhabi private equity). Thus, the expansion of robust digital health ecosystems enables AI adoption at scale, supporting more efficient healthcare delivery.
Moreover, the rapid adoption of telehealth platforms drives market growth further. For instance, SEHA Virtual Hospital is a flagship example of AI-enabled, hub-and-spoke virtual care that augments specialist throughput. In February 2025, Aster DM Healthcare launched myAster, its flagship digital health platform, in Saudi Arabia at LEAP 2025, expanding from its success in the UAE. The AI-powered app integrates telemedicine, online pharmacies, appointment management, chronic disease monitoring, and health record access.
Furthermore, the regional focus on developing biotechnology hubs and precision medicine accelerates demand for AI-powered research, drug discovery, and personalized therapeutics, driving sustained market expansion. For instance, in April 2025, the Institute for Healthier Living Abu Dhabi (IHLAD) and Singleron Biotechnologies launched AD-Omics, a joint venture to advance precision medicine in the Middle East using AI-driven single-cell multi-omics technologies. Thus, the demand for precision medicine and data-driven tailored treatments underscores the accelerated adoption of AI-driven medical devices in this region.
Middle East Artificial Intelligence In Healthcare Market Report Segmentation
This report forecasts revenue growth at the regional and country-level and provides an analysis of industry trends in each of the sub segments from 2021 to 2033. For this study, Grand View Research, Inc. has segmented the Middle East Artificial Intelligence (AI) in healthcare market report based on component, application, technology, end use, and country:
- Component Outlook (Revenue, USD Million, 2021 - 2033)
- Hardware
- Processor
- MPU (memory protection unit)
- FPGA (Field-programmable gate array)
- GPU (Graphics processing unit)
- ASIC (Application-specific integrated circuit)
- Memory
- Network
- Adapter
- Interconnect
- Switch
- Software Solutions
- AI platform
- Application Program Interface (API)
- Machine Learning Framework
- AI Solutions
- On premise
- Cloud based
- Services
- Deployment & Integration
- Support & Maintenance
- Others (Consulting, Compliance management etc.)
- Application Outlook (Revenue, USD Million, 2021 - 2033)
- Robot Assisted Surgery
- Virtual Assistants
- Administrative Workflow Assistants
- Connected Medical devices
- Medical Imaging & Diagnostics
- Clinical Trials
- Fraud Detection
- Cybersecurity
- Dosage Error Reduction
- Precision medicine
- Drug discovery & development
- Lifestyle management & remote patient monitoring
- Wearables
- Others (Patient engagement, etc.)
- Technology Outlook (Revenue, USD Million, 2021 - 2033)
- Machine Learning
- Deep learning
- Supervised
- Unsupervised
- Others (Reinforcement learning, Semi supervised)
- Natural Language Processing
- Smart Assistance
- OCR (Optical Character Recognition)
- Auto Coding
- Text analytics
- Speech analytics
- Classification and categorization
- Context-Aware Computing'
- Computer Vision
- End Use Outlook (Revenue, USD Million, 2021 - 2033)
- Healthcare providers (hospitals, outpatient facilities, and others)
- Healthcare payers
- Healthcare companies (Pharmaceutical, Biotechnology, Medical Devices)
- Patients
- Others
- Country Outlook (Revenue, USD Million, 2021 - 2033)
- Middle East
- Saudi Arabia
- UAE
- Kuwait
- Qatar
- Oman
Table of Contents
120 Pages
- Chapter 1. Methodology and Scope
- 1.1. Market Segmentation & Scope
- 1.2. Segment Definitions
- 1.2.1. Component Segment
- 1.2.2. Application Segment
- 1.2.3. Technology Segment
- 1.2.4. End Use Segment
- 1.3. Research Methodology
- 1.4. Information Procurement
- 1.4.1. Purchased database
- 1.4.2. GVR’s internal database
- 1.4.3. Secondary sources
- 1.4.4. Primary research
- 1.4.5. Details of primary research
- 1.5. Information or Data Analysis
- 1.5.1. Data analysis models
- 1.6. Market Formulation & Data Validation
- 1.7. Model Details
- 1.7.1. Commodity flow analysis (Model 1)
- 1.7.2. Approach 1: Commodity flow approach
- 1.7.3. Volume price analysis (Model 2)
- 1.7.4. Approach 2: Volume price analysis
- 1.8. List of Secondary Sources
- 1.9. List of Primary Sources
- 1.10. Objectives
- Chapter 2. Executive Summary
- 2.1. Market Outlook
- 2.2. Segment Outlook
- 2.3. Competitive Insights
- Chapter 3. Middle East Artificial Intelligence (AI) in Healthcare Market Variables, Trends & Scope
- 3.1. Market Lineage Outlook
- 3.1.1. Parent market outlook
- 3.1.2. Related/ancillary market outlook
- 3.2. Market Dynamics
- 3.2.1. Market driver analysis
- 3.2.2. Market restraint analysis
- 3.2.3. Market opportunity analysis
- 3.2.4. Market challenges analysis
- 3.3. AI in Healthcare Market Analysis Tools
- 3.3.1. Industry Analysis - Porter’s
- 3.3.1.1. Supplier power
- 3.3.1.2. Buyer power
- 3.3.1.3. Substitution threat
- 3.3.1.4. Threat of new entrant
- 3.3.1.5. Competitive rivalry
- 3.3.2. PESTEL Analysis
- 3.3.2.1. Political landscape
- 3.3.2.2. Technological landscape
- 3.3.2.3. Economic landscape
- 3.3.2.4. Environmental Landscape
- 3.3.2.5. Legal Landscape
- 3.3.2.6. Social Landscape
- Chapter 4. Middle East Artificial Intelligence (AI) in Healthcare Market: Component Estimates & Trend Analysis
- 4.1. Middle East AI in Healthcare Market: Component Movement Analysis
- 4.2. Middle East AI in Healthcare Market Size & Trend Analysis, by Component, 2021 to 2033 (USD Million)
- 4.2.1. Software Solutions
- 4.2.1.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.1.1.1. AI platform
- 4.2.1.1.1.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.1.1.1.2. Application Program Interface (API)
- 4.2.1.1.1.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.1.1.1.3. Machine Learning Framework
- 4.2.1.1.1.3.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.1.1.2. AI Solutions
- 4.2.1.1.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.1.1.2.2. On premise
- 4.2.1.1.2.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.1.1.2.3. Cloud based
- 4.2.1.1.2.3.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.2. Hardware
- 4.2.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.2.1.1. Processor
- 4.2.2.1.1.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.2.1.1.2. MPU (memory protection unit)
- 4.2.2.1.1.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.2.1.1.3. FPGA (Field-programmable gate array)
- 4.2.2.1.1.3.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.2.1.1.4. GPU (Graphics processing unit)
- 4.2.2.1.1.4.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.2.1.1.5. ASIC (Application-specific integrated circuit)
- 4.2.2.1.1.5.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.2.1.2. Memory
- 4.2.2.1.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.2.1.3. Network
- 4.2.2.1.3.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.2.1.3.2. Adapter
- 4.2.2.1.3.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.2.1.3.3. Interconnect
- 4.2.2.1.3.3.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.2.1.3.4. Switch
- 4.2.2.1.3.4.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.3. Services
- 4.2.3.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.3.1.1. Deployment & Integration
- 4.2.3.1.1.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.3.1.2. Support & Maintenance
- 4.2.3.1.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.3.1.3. Others (Consulting, Compliance management etc.)
- 4.2.3.1.3.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.4. Distributed Denial of Service (DDoS) Mitigation
- 4.2.4.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.5. Security Information and Event Management
- 4.2.5.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.6. Intrusion Detection System (IDS)/Intrusion Prevention System (IPS)
- 4.2.6.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 4.2.7. Others
- 4.2.7.1. Market estimates and forecast 2021 to 2033 (USD Million)
- Chapter 5. Middle East Artificial Intelligence (AI) in Healthcare Market: Application Estimates & Trend Analysis
- 5.1. Middle East AI in Healthcare Market: Application Movement Analysis
- 5.2. Middle East AI in Healthcare Market Size & Trend Analyses, by Application, 2021 to 2033 (USD Million)
- 5.2.1. Robot Assisted Surgery
- 5.2.1.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.2. Virtual Assistants
- 5.2.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.3. Administrative Workflow Assistants
- 5.2.3.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.4. Connected Medical Devices
- 5.2.4.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.5. Medical Imagining & Diagnosis
- 5.2.5.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.6. Clinical Trials
- 5.2.6.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.7. Fraud Detection
- 5.2.7.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.8. Cybersecurity
- 5.2.8.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.9. Dosage Error Reduction
- 5.2.9.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.10. Precision medicine
- 5.2.10.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.11. Drug discovery & development
- 5.2.11.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.12. Lifestyle management & remote patient monitoring
- 5.2.12.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.13. Wearables
- 5.2.13.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 5.2.14. Others
- 5.2.14.1. Market estimates and forecast 2021 to 2033 (USD Million)
- Chapter 6. Middle East Artificial Intelligence (AI) in Healthcare Market: Technology Estimates & Trend Analysis
- 6.1. Middle East AI in Healthcare Market: Technology Movement Analysis
- 6.2. Middle East AI in Healthcare Market Size & Trend Analyses, by Technology, 2021 to 2033 (USD Million)
- 6.2.1. Machine Learning
- 6.2.1.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.1.1.1. Deep learning
- 6.2.1.1.1.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.1.1.2. Supervised
- 6.2.1.1.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.1.1.3. Unsupervised
- 6.2.1.1.3.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.1.1.4. Others (Reinforcement learning, Semi supervised)
- 6.2.1.1.4.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.2. NLP
- 6.2.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.2.1.1. Smart Assistance
- 6.2.2.1.1.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.2.1.2. OCR (Optical Character Recognition)
- 6.2.2.1.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.2.1.3. Auto Coding
- 6.2.2.1.3.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.2.1.4. Text analytics
- 6.2.2.1.4.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.2.1.5. Speech analytics
- 6.2.2.1.5.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.2.1.6. Classification and categorization
- 6.2.2.1.6.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.3. Computer Vision
- 6.2.3.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 6.2.4. Context-aware computing
- 6.2.4.1. Market estimates and forecast 2021 to 2033 (USD Million)
- Chapter 7. Middle East Artificial Intelligence (AI) in Healthcare Market: End Use Estimates & Trend Analysis
- 7.1. Middle East AI in Healthcare Market: End Use Movement Analysis
- 7.2. Middle East AI in Healthcare Market Size & Trend Analyses, By End Use, 2021 to 2033 (USD Million)
- 7.2.1. Healthcare providers (hospitals, outpatient facilities, and others)
- 7.2.1.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 7.2.2. Healthcare payers
- 7.2.2.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 7.2.3. Healthcare Companies
- 7.2.3.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 7.2.4. Patients
- 7.2.4.1. Market estimates and forecast 2021 to 2033 (USD Million)
- 7.2.5. Others
- 7.2.5.1. Market estimates and forecast 2021 to 2033 (USD Million)
- Chapter 8. Middle East Artificial Intelligence (AI) in Healthcare Market: Regional Estimates & Trend Analysis by Component, Applications, Technology & End Use
- 8.1. Middle East Regional Market Snapshot
- 8.2. Market Size & Forecasts Trend Analysis, 2021 to 2033
- 8.3. Middle East
- 8.3.1. Market estimates and forecasts 2021 to 2033 (USD Million)
- 8.3.2. Saudi Arabia
- 8.3.2.1. Saudi Arabia market estimates and forecast, 2021 - 2033 (USD Million)
- 8.3.3. UAE
- 8.3.3.1. UAE market estimates and forecast, 2021 - 2033 (USD Million)
- 8.3.4. Kuwait
- 8.3.4.1. UAE market estimates and forecast, 2021 - 2033 (USD Million)
- 8.3.5. Qatar
- 8.3.5.1. Qatar market estimates and forecast, 2021 - 2033 (USD Million)
- 8.3.6. Oman
- 8.3.6.1. Oman market estimates and forecast, 2021 - 2033 (USD Million)
- Chapter 9. Competitive Landscape
- 9.1. Recent Developments & Impact Analysis, By Key Market Participants
- 9.2. Company/Competition Categorization
- 9.3. Competitive Landscape
- 9.3.1. Microsoft
- 9.3.1.1. Company overview
- 9.3.1.2. Financial performance
- 9.3.1.3. Product benchmarking
- 9.3.1.4. Strategic initiatives
- 9.3.2. IBM
- 9.3.2.1. Company overview
- 9.3.2.2. Financial performance
- 9.3.2.3. Product benchmarking
- 9.3.2.4. Strategic initiatives
- 9.3.3. NVIDIA Corporation
- 9.3.3.1. Company overview
- 9.3.3.2. Financial performance
- 9.3.3.3. Product benchmarking
- 9.3.3.4. Strategic initiatives
- 9.3.4. Intel Corporation
- 9.3.4.1. Company overview
- 9.3.4.2. Financial performance
- 9.3.4.3. Product benchmarking
- 9.3.4.4. Strategic initiatives
- 9.3.5. GE Healthcare
- 9.3.5.1. Company overview
- 9.3.5.2. Financial performance
- 9.3.5.3. Product benchmarking
- 9.3.5.4. Strategic initiatives
- 9.3.6. Medtronic
- 9.3.6.1. Company overview
- 9.3.6.2. Financial performance
- 9.3.6.3. Product benchmarking
- 9.3.6.4. Strategic initiatives
- 9.3.7. Oracle
- 9.3.7.1. Company overview
- 9.3.7.2. Financial performance
- 9.3.7.3. Product benchmarking
- 9.3.7.4. Strategic initiatives
- 9.3.8. Google
- 9.3.8.1. Company overview
- 9.3.8.2. Financial performance
- 9.3.8.3. Product benchmarking
- 9.3.8.4. Strategic initiatives
- 9.3.9. IQVIA
- 9.3.9.1. Company overview
- 9.3.9.2. Financial performance
- 9.3.9.3. Product benchmarking
- 9.3.9.4. Strategic initiatives
- 9.3.10. Siemens Healthineers AG
- 9.3.10.1. Company overview
- 9.3.10.2. Financial performance
- 9.3.10.3. Product benchmarking
- 9.3.10.4. Strategic initiatives
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