
Region:Middle East
Author(s):Yogita Sahu
Product Code:KROD2364
October 2024
82

The market is segmented into various factors like application, deployment type, and region.
By Application: The market is segmented by application into healthcare, finance, and smart cities. The healthcare segment dominated the market share, driven by the rapid adoption of AI-powered diagnostic and treatment tools. The rise in demand for personalized healthcare solutions, especially in telemedicine and robotic surgery, has been a key factor for its dominance.

By Deployment Type: The market is segmented by deployment type into cloud-based, on-premise, and hybrid. Cloud-based deployment dominated the market with the flexibility and scalability it offers. Many organizations, especially in healthcare and finance, have shifted towards cloud-based AI solutions due to lower operational costs and easy integration with existing IT infrastructure.

By Region: The market is segmented by region into North, South, East, and West. The central region, led due to its role as the administrative and financial capital of the country, as well as its leadership in smart city and AI innovation initiatives.
|
Company Name |
Establishment Year |
Headquarters |
|
IBM |
1911 |
Armonk, NY, USA |
|
Microsoft |
1975 |
Redmond, WA, USA |
|
|
1998 |
Mountain View, CA |
|
STC |
1998 |
Riyadh, Saudi Arabia |
|
SDAIA |
2019 |
Riyadh, Saudi Arabia |
The KSA AI market is expected to experience growth over the next five years, with increased AI adoption in smart city development, healthcare, and financial services, supported by ongoing government investments and strategic initiatives.
|
By Application |
Healthcare Smart Cities Finance |
|
By Deployment Type |
Cloud-Based On-Premise Hybrid |
|
By Region |
North East West South |
1.1. Definition and Scope
1.2. Market Taxonomy (AI Solutions, Deployment Models, Applications, Verticals)
1.3. Market Growth Rate (Market Penetration, Government Initiatives, AI Ecosystem)
1.4. Market Segmentation Overview (Key Market Sectors and Sub-Sectors)
2.1. Historical Market Size
2.2. Year-on-Year Growth Analysis (Financial, Operational Metrics)
2.3. Key Market Milestones (Adoption Rate, Government Support)
2.4. Macroeconomic Indicators Impacting Market Size (GDP Growth, Non-Oil Economy)
3.1. Growth Drivers
3.1.1. Government Digital Transformation Initiatives
3.1.2. AI Adoption in Healthcare and Energy
3.1.3. Private Sector Investments in AI
3.1.4. AI in Financial Services and Smart Cities
3.2. Restraints
3.2.1. High Cost of AI Implementation for SMEs
3.2.2. Data Privacy and Security Concerns
3.2.3. Regulatory and Ethical Challenges in AI Use
3.2.4. Talent Shortage in AI Specialization
3.3. Opportunities
3.3.1. AI in Smart City Projects (Neom, The Line)
3.3.2. AI Applications in Autonomous Vehicles and IoT
3.3.3. Expansion into Emerging Industries (Agriculture, Retail)
3.3.4. AI Startups and Entrepreneurial Ecosystem Development
3.4. Key Trends
3.4.1. AI-Powered Robotics and Automation
3.4.2. Cloud-Based AI Solutions and Edge Computing
3.4.3. AI-Driven Predictive Maintenance in Oil & Gas
3.4.4. AI-Based Fraud Detection in Banking
3.5. Government Regulation
3.5.1. AI-Specific Policy Framework (SDAIA Initiatives)
3.5.2. Vision 2030 AI Adoption Goals
3.5.3. Saudi Arabias AI Ethical Guidelines
3.5.4. Public-Private Partnerships in AI Implementation
3.6. SWOT Analysis
3.7. Stakeholder Ecosystem
3.8. Competitive Ecosystem
4.1. By Application (in value%)
4.1.1. Healthcare
4.1.2. Smart Cities
4.1.3. Finance
4.1.4. Energy
4.1.5. Transportation
4.2. By Deployment Model (in value%)
4.2.1. Cloud-Based
4.2.2. On-Premise
4.2.3. Hybrid
4.3. By Region (in value%)
4.3.1. Central (Riyadh)
4.3.2. Western (Jeddah, Neom)
4.3.3. Eastern (Dammam, Al Khobar)
4.3.4. Southern (Jizan, Abha)
5.1. Detailed Profiles of Major Companies
5.1.1. IBM
5.1.2. Microsoft
5.1.3. Google
5.1.4. Saudi Telecom Company (STC)
5.1.5. Saudi Data and Artificial Intelligence Authority (SDAIA)
5.1.6. Oracle
5.1.7. Amazon Web Services (AWS)
5.1.8. Huawei
5.1.9. Nvidia
5.1.10. Accenture
5.1.11. Aramco
5.1.12. Neom (AI Division)
5.1.13. King Abdullah University of Science and Technology (KAUST)
5.1.14. TCS (Tata Consultancy Services)
5.1.15. SAP
5.2. Cross Comparison Parameters (Revenue, Headquarters, Employee Count, AI Investments)
6.1. Market Share Analysis (Top Players)
6.2. Strategic Initiatives (Partnerships, Collaborations)
6.3. Mergers and Acquisitions (Investment Patterns)
6.4. Investment Analysis
6.4.1. Government AI Investments
6.4.2. Venture Capital Funding
6.4.3. Private Equity Involvement
7.1. Compliance with National AI Guidelines
7.2. AI Certification Processes
7.3. Data Protection Laws Impacting AI Development
7.4. Sector-Specific AI Regulations (Healthcare, Finance)
8.1. Market Size Forecast (in USD Bn)
8.2. Key Factors Driving Future Market Growth
8.3. Sector-Specific Projections (Healthcare, Smart Cities, BFSI)
8.4. Technological Advancements Supporting Future Growth
9.1. By Application (Future Impact on Sectors)
9.2. By Deployment Type (Cloud, On-Premise, Hybrid)
9.3. By Region (Future Geographical Distribution)
10.1. Total Addressable Market (TAM) and Serviceable Obtainable Market (SOM)
10.2. Industry-Specific Customer Analysis
10.3. Marketing Strategies for AI Companies
10.4. Opportunities for Growth in Untapped Segments
Ecosystem creation for all the major entities and referring to multiple secondary and proprietary databases to perform desk research around market to collate industry level information.
Collating statistics on this industry over the years, penetration of marketplaces and service providers ratio to compute revenue generated for KSA Artificial Intelligence industry. We will also review service quality statistics to understand revenue generated which can ensure accuracy behind the data points shared.
Building market hypothesis and conducting CATIs with industry experts belonging to different companies to validate statistics and seek operational and financial information from company representatives.
Our team will approach multiple technology companies and understand nature of product segments and sales, consumer preference and other parameters, which will support us validate statistics derived through bottom to top approach from such technology companies.
The KSA Artificial Intelligence Market was valued at USD 1.5 billion experienced rapid growth, reflecting global trends in AI adoption and innovation.
Challenges in the KSA Artificial Intelligence market include shortage of skilled AI professionals, high implementation costs for AI technologies, data privacy concerns, and regulatory hurdles related to the ethical use of AI.
Key players in the KSA Artificial Intelligence market include IBM, Microsoft, Google, Saudi Telecom Company (STC), and the Saudi Data and Artificial Intelligence Authority (SDAIA), all playing pivotal roles in AI innovation and deployment.
The growth of the KSA Artificial Intelligence market is driven by government initiatives like Vision 2030, increased AI adoption in healthcare, energy, and financial services, and major investments in smart city projects, especially in Riyadh and Neom.
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