Kingdom Of Saudi Arabia AI In Manufacturing Market Is Expected To Reach Revenue Of USD 7,103.7 Mn By 2033, At 36.2% CAGR: Dimension Market Research.

(MENAFN- GlobeNewsWire - Nasdaq) Advancements and Projections in the Global The Kingdom of Saudi Arabia AI in Manufacturing Market: Insights, Trends, Opportunities, and Recent Developments

New York, Jan. 28, 2025 (GLOBE NEWSWIRE) -- Overview

The Global The Kingdom of Saudi Arabia AI in Manufacturing Market is projected to reach USD 439.8 million in 2024 which is further anticipated to reach USD 7,103.7 million by 2033 at a CAGR of 36.2%.

AI in Saudi Arabia's manufacturing market is one of the fastest-growing industries, apart from the Kingdom's aspiration to diversify its economy with the latest technologies embodied in its Vision 2030. Productivity, quality, and operational efficiency have improved after the integration of AI into the sector, therefore making it globally competitive.

The investments by the government in infrastructure, R&D, and digital transformation spur the growth even more. Key applications, such as Predictive Maintenance, Process Automation, and Supply Chain Optimization, have also hastened the pace of movement toward Industry 4.0 with partnerships between local manufacturers and global leaders in technology. These are partial counterbalances to outstanding challenges: high implementation costs, resistance to change, and a shortage of AI specialists, particularly for SMEs.

While such challenges do persist, they are now being mitigated through many government initiatives, including training, education, and subsides. Furthermore, broader pathways for incremental adoption-e.g., cloud-based and modular system solutions-keep costs down, making AI even more feasible and accessible and, in turn, broader AI integration into manufacturing.

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Important Insights

• Market Overview: The AI in Manufacturing Market in Saudi Arabia is valued at USD 439.8 million in 2024 and is anticipated to grow to USD 7,103.7 million by 2033, at a CAGR of 36.2% during the forecast period.
• Key Players: Prominent companies driving the market include IBM, Microsoft, Siemens, ABB, Honeywell, GE Digital, Schneider Electric, Rockwell Automation, and others. These players are instrumental in advancing AI adoption in the manufacturing sector.
• By Technology Type : Machine Learning (ML) leads as the dominant technology, holding a 31.5% market share in 2024, owing to its pivotal role in predictive analytics and process optimization.
• By Deployment Mode: Cloud-based deployment emerges as the leading mode, capturing 44.9% of the market share in 2024, driven by scalability, cost-efficiency, and ease of implementation.

Latest Trends

• Increasing Adoption of Industry 4.0: Saudi Arabia's manufacturing sector is modernizing and adopting Industry 4.0, powered by AI through smart factories in real-time. Predictive maintenance reduces downtime of the equipment by about 30.0%, while automation using AI improves throughput by about 25.0%, thus increasing productivity and cost efficiency.
• Collaborations and Partnerships: A strategic alliance between local manufacturers and global leaders in AI has recorded a 40.0% growth, further accelerating the adoption of AI. This kind of collaboration the case of Saudi Aramco, for example, fosters knowledge sharing, innovation, and development of custom AI solutions to achieve Vision 2030 goals aimed at developing competitive energy-intensive industries.

The Kingdom of Saudi Arabia AI in Manufacturing Market: Competitive Landscape

• The manufacturing market for AI in Saudi Arabia presents a dynamic interaction between global leaders, local innovators, and public sector initiatives. Global giants like IBM, Microsoft, and Siemens are very active in their collaboration with Saudi manufacturers, deploying state-of-the-art AI technologies in predictive analytics, robotics, and supply chain optimization. These partnerships are in line with the focus of Vision 2030 on digital transformation.
• Local players like Alat, backed by the Public Investment Fund, are emerging via partnerships with global companies such as Dahua Technology and SoftBank, thereby developing capabilities in energy management and automation. Such partnerships spur knowledge transfer and local innovation.
• Public initiatives, like the National Industrial Development and Logistics Program, are the main source of finance and infrastructure, attracting world players and fuelling competition.

Some of the prominent market players:

• IBM
• Microsoft
• Siemens
• ABB
• Honeywell
• GE Digital
• Schneider Electric
• Rockwell Automation
• Oracle
• SAP
• Alat
• SAS Institute
• PTC
• Other Key Players

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The Kingdom of Saudi Arabia AI in Manufacturing Market Scope

Report Highlights	Details
Market Size (2024)	USD 439.8 Mn
Forecast Value (2033)	USD 7,103.7 Mn
CAGR (2024-2033)	36.2%
Historical Data	2018 - 2023
Forecast Data	2025 - 2033
Base Year	2023
Estimate Year	2024
Segments Covered	By Technology Type, By Deployment Mode, By Company Size, By Functionality, By Application, By Industry Vertical

Market Analysis

AI in Saudi Arabian manufacturing is enabled by ML, which takes its power from handling large volumes of data that are too complex for human processing to ensure the efficiency and innovation that characterize the sector. It also allows manufacturers to streamline their workflows, minimize errors, and predict outcomes with accuracy. It analyzes sensor data to show early wear signals that give notice for machinery life extension, hence preventing downtime.

Computer vision detects defective products more precisely to ensure standards are maintained and waste is minimal. As Industry 4.0 continues to evolve, so does the role of ML in enabling real-time decisions and driving autonomy and smart factory initiatives in Saudi Arabia, among other countries.

The Kingdom of Saudi Arabia AI in Manufacturing Market Segmentation

By Technology Type

• Machine Learning (ML)
• Computer Vision
• Natural Language Processing (NLP)
• Robotics and Automation
• Internet of Things (IoT) with AI Integration

By Deployment Mode

• Cloud-Based
• On-Premises
• Hybrid Deployment

By Company Size

• Small and Medium Enterprises (SMEs)
• Large Enterprises

By Functionality

• Planning and Scheduling
• Product Design and Customization
• Workforce Management

By Application

• Predictive Maintenance and Machine Monitoring
• Quality Control and Inspection
• Supply Chain Optimization
• Process Automation
• Energy Management

By Industry Vertical

• Automotive Manufacturing
• Chemical and Petrochemicals
• Food and Beverage
• Metals and Machinery
• Electronics and Semiconductor

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Growth Drivers

• Government Initiatives and Investments: Vision 2030 and NIDLP prioritize AI research and training of over 50,000 professionals by investing US $500 Million by 2023 for AI R&D as well as AI integration within manufacturing processes to maximize productivity and competitiveness.
  Growing Demand for Efficiency: AI applications in automation and supply chain analytics reduce costs by 20%, while energy management systems lower energy expenses by 15-25% which aligning with sustainability goals while positioning Saudi Arabia as a high-tech manufacturing hub.

Restraints

• High Initial Costs: AI implementation costs, ranging from USD 100,000 to USD 1 million, deter SMEs, requiring grants, financing, and public-private partnerships to facilitate adoption.
• Lack of Skilled Workforce: AI implementation costs can range between USD 100,000 to USD 1.0 Million for small and mid-sized enterprises (SMEs), deterring them from adopting it unless grants, financial, ng, and public-private partnerships can help ease its adoption.

Growth Opportunities

• AI in Energy Management: Due to an acute shortage of skilled AI workers (30%), full deployment cannot yet occur. Therefore, more education on AI-focused topics and partnerships between countries for talent development and training programs are urgently required to bridge this skills gap and unleash AI's full potential.
• Custom AI Solutions for SMEs: AI can optimize energy usage across petrochemical and metal industries, cutting energy costs by up to 30 % in pilot programs while also upholding sustainability standards - ultimately contributing to improved global competitiveness while decreasing carbon footprints.

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Recent Developments in the Kingdom of Saudi Arabia AI in the Manufacturing Market

• November 2024: Saudi Arabia announced a USD 100.0 million initiative to establish an AI technology hub, aiming to lead the region in AI innovation.
• November 2024: Elon Musk engaged Middle Eastern investors, including Saudi Arabia, for xAI funding, potentially raising its valuation to USD 45.0 million.
• October 2024: The Public Investment Fund (PIF) shifted focus to domestic projects, prioritizing AI investments aligned with Vision 2030 objectives.
• September 2024: A research report on Saudi Arabia's AI manufacturing industry emphasized collaborations with global tech leaders to accelerate AI adoption.
• August 2024: Saudi Arabia's PIF announced a USD 40.0 million fund for AI investments, exploring collaborations with firms like Andreessen Horowitz.
• February 2024: Crown Prince Mohammed bin Salman launched 'Alat,' a PIF-owned conglomerate to position Saudi Arabia as a global AI-driven manufacturing hub.
• February 2024: Alat partnered with global firms like Carrier Global, Dahua Technology, and SoftBank to enhance AI and advanced manufacturing capabilities.

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About Dimension Market Research (DMR):

Dimension Market Research (DMR) is a market research and consulting firm based in India & US, with its headquarters located in the USA (New York). The company believes in providing the best and most valuable data to its customers using the best resources analysts work, to create unmatchable insights into the industries, and markets while offering in-depth results of over 30 industries, and all major regions across the world. We also believe that our clients don't always want what they see, so we provide customized reports as well, as per their specific requirements to create the best possible outcomes for them and enhance their business through our data and insights in every possible way.

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