Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Size, Share, Growth Drivers, Trends, Opportunities, Competitive Landscape & Forecast 2025–2030

The Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market is valued at USD 1.2 Bn, fueled by tech advancements in IoT and AI for enhanced productivity and sustainability.

Region:Middle East

Author(s):Shubham

Product Code:KRAB8666

Pages:90

Published On:October 2025

About the Report

Base Year 2024

Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Overview

  • The Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market is valued at USD 1.2 billion, based on a five-year historical analysis. This growth is primarily driven by the increasing adoption of advanced technologies in agriculture, such as IoT and AI, which enhance productivity and efficiency. The rising need for food security and sustainable farming practices has further propelled the demand for predictive analytics solutions in the agricultural sector.
  • Key cities such as Riyadh, Jeddah, and Dammam dominate the market due to their robust agricultural infrastructure and investment in technology. These urban centers are witnessing a surge in smart farming initiatives, supported by government policies and private sector investments, making them pivotal in the growth of cloud-based predictive analytics for agriculture.
  • In 2023, the Saudi Arabian government implemented the National Agricultural Development Strategy, which emphasizes the integration of technology in agriculture. This initiative aims to enhance productivity and sustainability through the adoption of smart agriculture solutions, including cloud-based predictive analytics, thereby fostering innovation and growth in the sector.
Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Size

Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Segmentation

By Type:The market is segmented into various types of solutions that cater to different agricultural needs. The subsegments include Crop Monitoring Solutions, Soil Health Analytics, Weather Forecasting Tools, Yield Prediction Models, Pest and Disease Management Systems, Irrigation Management Solutions, and Others. Each of these solutions plays a crucial role in enhancing agricultural productivity and sustainability.

Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market segmentation by Type.

By End-User:The end-user segmentation includes Large Scale Farms, Smallholder Farmers, Agricultural Cooperatives, and Government Agencies. Each of these segments has unique requirements and challenges that cloud-based predictive analytics can address, thereby enhancing agricultural practices and outcomes.

Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market segmentation by End-User.

Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Competitive Landscape

The Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market is characterized by a dynamic mix of regional and international players. Leading participants such as IBM Corporation, Microsoft Corporation, SAP SE, Oracle Corporation, SAS Institute Inc., Trimble Inc., Ag Leader Technology, The Climate Corporation, Granular, Inc., Taranis, CropX, Farmers Edge, AeroFarms, AgriWebb, Ceres Imaging contribute to innovation, geographic expansion, and service delivery in this space.

IBM Corporation

1911

Armonk, New York, USA

Microsoft Corporation

1975

Redmond, Washington, USA

SAP SE

1972

Walldorf, Germany

Oracle Corporation

1977

Redwood City, California, USA

SAS Institute Inc.

1976

Cary, North Carolina, USA

Company

Establishment Year

Headquarters

Group Size (Large, Medium, or Small as per industry convention)

Revenue Growth Rate

Customer Acquisition Cost

Customer Retention Rate

Market Penetration Rate

Pricing Strategy

Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Industry Analysis

Growth Drivers

  • Increasing Demand for Food Security:The Saudi Arabian government aims to increase food production by 30% by 2030, driven by a growing population projected to reach 40 million by 2040. This demand necessitates advanced agricultural technologies, including cloud-based predictive analytics, to optimize crop yields and resource management. The World Bank reported that food security investments in the region reached approximately $1.7 billion recently, highlighting the urgency for innovative solutions in agriculture.
  • Adoption of IoT in Agriculture:The Internet of Things (IoT) is transforming agriculture in Saudi Arabia, with over 1.5 million IoT devices expected to be deployed in the sector in the near future. These devices facilitate real-time data collection and analysis, enhancing decision-making processes. The Saudi Ministry of Environment, Water, and Agriculture has allocated $600 million for IoT initiatives, underscoring the commitment to integrating technology into farming practices for improved efficiency and productivity.
  • Government Initiatives for Smart Farming:The Saudi government has launched several initiatives, including the National Agricultural Development Strategy, which aims to modernize agricultural practices. Recently, the government invested $2.5 billion in smart farming technologies, promoting the use of cloud-based predictive analytics. This investment is expected to enhance agricultural productivity and sustainability, aligning with the Vision 2030 goals of economic diversification and food security.

Market Challenges

  • High Initial Investment Costs:The implementation of cloud-based predictive analytics in agriculture requires significant upfront investments, often exceeding $120,000 for small to medium-sized farms. This financial barrier can deter farmers from adopting advanced technologies, especially in a market where the average farm income is around $35,000 annually. Consequently, many farmers may struggle to justify the costs associated with transitioning to smart agriculture solutions.
  • Lack of Skilled Workforce:The agricultural sector in Saudi Arabia faces a shortage of skilled professionals capable of utilizing advanced technologies. According to the Saudi Ministry of Education, only 18% of agricultural graduates possess the necessary skills for modern farming practices. This skills gap hampers the effective implementation of cloud-based predictive analytics, limiting the potential benefits of technology in enhancing agricultural productivity and sustainability.

Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Future Outlook

The future of cloud-based predictive analytics in Saudi Arabia's agriculture sector appears promising, driven by technological advancements and government support. As the demand for food security intensifies, farmers are increasingly adopting innovative solutions to enhance productivity. The integration of artificial intelligence with predictive analytics is expected to revolutionize farming practices, enabling data-driven decision-making. Additionally, the expansion of e-commerce platforms for agricultural products will further facilitate market access for farmers, fostering growth in the sector.

Market Opportunities

  • Expansion of E-commerce in Agriculture:The rise of e-commerce platforms presents a significant opportunity for farmers to reach broader markets. Recently, online agricultural sales in Saudi Arabia reached $350 million, with projections indicating continued growth. This trend allows farmers to leverage cloud-based analytics for better inventory management and customer insights, enhancing their competitiveness in the market.
  • Integration of AI with Predictive Analytics:The convergence of artificial intelligence and predictive analytics offers transformative potential for smart agriculture. In the near future, investments in AI-driven agricultural technologies are expected to exceed $1.2 billion in Saudi Arabia. This integration can optimize resource allocation, improve crop forecasting, and enhance overall farm management, driving efficiency and sustainability in agricultural practices.

Scope of the Report

SegmentSub-Segments
By Type

Crop Monitoring Solutions

Soil Health Analytics

Weather Forecasting Tools

Yield Prediction Models

Pest and Disease Management Systems

Irrigation Management Solutions

Others

By End-User

Large Scale Farms

Smallholder Farmers

Agricultural Cooperatives

Government Agencies

By Application

Crop Production

Livestock Management

Aquaculture

Agroforestry

By Component

Software Solutions

Hardware Devices

Services

By Sales Channel

Direct Sales

Online Platforms

Distributors

By Distribution Mode

Retail Distribution

Wholesale Distribution

E-commerce

By Policy Support

Government Subsidies

Tax Incentives

Research Grants

Training Programs

Key Target Audience

Investors and Venture Capitalist Firms

Government and Regulatory Bodies (e.g., Ministry of Environment, Water and Agriculture)

Agricultural Technology Startups

Farm Management Software Providers

Data Analytics Service Providers

Agricultural Cooperatives and Associations

Telecommunications Companies (providing IoT solutions)

Agri-tech Research and Development Organizations

Players Mentioned in the Report:

IBM Corporation

Microsoft Corporation

SAP SE

Oracle Corporation

SAS Institute Inc.

Trimble Inc.

Ag Leader Technology

The Climate Corporation

Granular, Inc.

Taranis

CropX

Farmers Edge

AeroFarms

AgriWebb

Ceres Imaging

Table of Contents

Market Assessment Phase

1. Executive Summary and Approach


2. Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Overview

2.1 Key Insights and Strategic Recommendations

2.2 Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Overview

2.3 Definition and Scope

2.4 Evolution of Market Ecosystem

2.5 Timeline of Key Regulatory Milestones

2.6 Value Chain & Stakeholder Mapping

2.7 Business Cycle Analysis

2.8 Policy & Incentive Landscape


3. Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Analysis

3.1 Growth Drivers

3.1.1 Increasing demand for food security
3.1.2 Adoption of IoT in agriculture
3.1.3 Government initiatives for smart farming
3.1.4 Rising investment in agricultural technology

3.2 Market Challenges

3.2.1 High initial investment costs
3.2.2 Lack of skilled workforce
3.2.3 Data privacy concerns
3.2.4 Limited internet connectivity in rural areas

3.3 Market Opportunities

3.3.1 Expansion of e-commerce in agriculture
3.3.2 Integration of AI with predictive analytics
3.3.3 Development of mobile applications for farmers
3.3.4 Collaborations with research institutions

3.4 Market Trends

3.4.1 Shift towards sustainable farming practices
3.4.2 Increasing use of drones for crop monitoring
3.4.3 Growth of precision agriculture technologies
3.4.4 Rise in consumer demand for organic produce

3.5 Government Regulation

3.5.1 National Agricultural Development Strategy
3.5.2 Regulations on data usage in agriculture
3.5.3 Incentives for technology adoption
3.5.4 Environmental protection laws affecting agriculture

4. SWOT Analysis


5. Stakeholder Analysis


6. Porter's Five Forces Analysis


7. Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Market Size, 2019-2024

7.1 By Value

7.2 By Volume

7.3 By Average Selling Price


8. Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Segmentation

8.1 By Type

8.1.1 Crop Monitoring Solutions
8.1.2 Soil Health Analytics
8.1.3 Weather Forecasting Tools
8.1.4 Yield Prediction Models
8.1.5 Pest and Disease Management Systems
8.1.6 Irrigation Management Solutions
8.1.7 Others

8.2 By End-User

8.2.1 Large Scale Farms
8.2.2 Smallholder Farmers
8.2.3 Agricultural Cooperatives
8.2.4 Government Agencies

8.3 By Application

8.3.1 Crop Production
8.3.2 Livestock Management
8.3.3 Aquaculture
8.3.4 Agroforestry

8.4 By Component

8.4.1 Software Solutions
8.4.2 Hardware Devices
8.4.3 Services

8.5 By Sales Channel

8.5.1 Direct Sales
8.5.2 Online Platforms
8.5.3 Distributors

8.6 By Distribution Mode

8.6.1 Retail Distribution
8.6.2 Wholesale Distribution
8.6.3 E-commerce

8.7 By Policy Support

8.7.1 Government Subsidies
8.7.2 Tax Incentives
8.7.3 Research Grants
8.7.4 Training Programs

9. Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Competitive Analysis

9.1 Market Share of Key Players

9.2 Cross Comparison of Key Players

9.2.1 Company Name
9.2.2 Group Size (Large, Medium, or Small as per industry convention)
9.2.3 Revenue Growth Rate
9.2.4 Customer Acquisition Cost
9.2.5 Customer Retention Rate
9.2.6 Market Penetration Rate
9.2.7 Pricing Strategy
9.2.8 Average Deal Size
9.2.9 Product Development Cycle Time
9.2.10 Customer Satisfaction Score

9.3 SWOT Analysis of Top Players

9.4 Pricing Analysis

9.5 Detailed Profile of Major Companies

9.5.1 IBM Corporation
9.5.2 Microsoft Corporation
9.5.3 SAP SE
9.5.4 Oracle Corporation
9.5.5 SAS Institute Inc.
9.5.6 Trimble Inc.
9.5.7 Ag Leader Technology
9.5.8 The Climate Corporation
9.5.9 Granular, Inc.
9.5.10 Taranis
9.5.11 CropX
9.5.12 Farmers Edge
9.5.13 AeroFarms
9.5.14 AgriWebb
9.5.15 Ceres Imaging

10. Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market End-User Analysis

10.1 Procurement Behavior of Key Ministries

10.1.1 Ministry of Environment, Water and Agriculture
10.1.2 Ministry of Finance
10.1.3 Ministry of Commerce

10.2 Corporate Spend on Infrastructure & Energy

10.2.1 Investment in Smart Agriculture Technologies
10.2.2 Budget Allocation for Research and Development

10.3 Pain Point Analysis by End-User Category

10.3.1 Cost of Technology Implementation
10.3.2 Access to Reliable Data
10.3.3 Integration with Existing Systems

10.4 User Readiness for Adoption

10.4.1 Awareness of Benefits
10.4.2 Training and Support Needs

10.5 Post-Deployment ROI and Use Case Expansion

10.5.1 Measurement of Success Metrics
10.5.2 Opportunities for Upscaling

11. Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market Future Size, 2025-2030

11.1 By Value

11.2 By Volume

11.3 By Average Selling Price


Go-To-Market Strategy Phase

1. Whitespace Analysis + Business Model Canvas

1.1 Market Gaps Identification

1.2 Business Model Framework


2. Marketing and Positioning Recommendations

2.1 Branding Strategies

2.2 Product USPs


3. Distribution Plan

3.1 Urban Retail Strategies

3.2 Rural NGO Tie-ups


4. Channel & Pricing Gaps

4.1 Underserved Routes

4.2 Pricing Bands


5. Unmet Demand & Latent Needs

5.1 Category Gaps

5.2 Consumer Segments


6. Customer Relationship

6.1 Loyalty Programs

6.2 After-sales Service


7. Value Proposition

7.1 Sustainability

7.2 Integrated Supply Chains


8. Key Activities

8.1 Regulatory Compliance

8.2 Branding

8.3 Distribution Setup


9. Entry Strategy Evaluation

9.1 Domestic Market Entry Strategy

9.1.1 Product Mix
9.1.2 Pricing Band
9.1.3 Packaging

9.2 Export Entry Strategy

9.2.1 Target Countries
9.2.2 Compliance Roadmap

10. Entry Mode Assessment

10.1 Joint Ventures

10.2 Greenfield Investments

10.3 Mergers & Acquisitions

10.4 Distributor Model


11. Capital and Timeline Estimation

11.1 Capital Requirements

11.2 Timelines


12. Control vs Risk Trade-Off

12.1 Ownership vs Partnerships


13. Profitability Outlook

13.1 Breakeven Analysis

13.2 Long-term Sustainability


14. Potential Partner List

14.1 Distributors

14.2 Joint Ventures

14.3 Acquisition Targets


15. Execution Roadmap

15.1 Phased Plan for Market Entry

15.1.1 Market Setup
15.1.2 Market Entry
15.1.3 Growth Acceleration
15.1.4 Scale & Stabilize

15.2 Key Activities and Milestones

15.2.1 Activity Timeline
15.2.2 Milestone Tracking

Research Methodology

ApproachModellingSample

Phase 1: Approach1

Desk Research

  • Analysis of government reports on agricultural technology initiatives in Saudi Arabia
  • Review of industry publications and white papers on cloud-based predictive analytics
  • Examination of market trends and forecasts from agricultural technology associations

Primary Research

  • Interviews with agricultural technology experts and data scientists
  • Surveys with farmers and agribusinesses utilizing smart agriculture platforms
  • Focus groups with stakeholders in the Saudi agricultural sector

Validation & Triangulation

  • Cross-validation of findings with multiple data sources, including academic studies
  • Triangulation of insights from primary interviews and secondary data analysis
  • Sanity checks through expert panel discussions and feedback sessions

Phase 2: Market Size Estimation1

Top-down Assessment

  • Estimation of market size based on national agricultural spending and technology adoption rates
  • Segmentation of the market by crop type and technology application
  • Incorporation of government initiatives promoting smart agriculture solutions

Bottom-up Modeling

  • Collection of data from leading cloud-based analytics providers in agriculture
  • Estimation of user adoption rates and average revenue per user (ARPU)
  • Volume and pricing analysis based on service offerings and market demand

Forecasting & Scenario Analysis

  • Multi-variable regression analysis incorporating economic indicators and technology trends
  • Scenario modeling based on potential regulatory changes and climate impacts
  • Development of baseline, optimistic, and pessimistic market growth projections through 2030

Phase 3: CATI Sample Composition1

Scope Item/SegmentSample SizeTarget Respondent Profiles
Cloud-Based Analytics Adoption in Crop Management150Agricultural Technologists, Farm Managers
Smart Irrigation Systems Utilization100Irrigation Specialists, Agronomists
Data-Driven Decision Making in Livestock Management80Livestock Farmers, Veterinary Consultants
Integration of IoT in Agriculture70IoT Solution Providers, Agricultural Engineers
Impact of Predictive Analytics on Yield Optimization90Crop Scientists, Agricultural Economists

Frequently Asked Questions

What is the current value of the Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market?

The Saudi Arabia Cloud-Based Predictive Analytics for Smart Agriculture Platforms Market is valued at approximately USD 1.2 billion, reflecting significant growth driven by the adoption of advanced technologies in agriculture, such as IoT and AI, to enhance productivity and efficiency.

What are the key drivers of growth in this market?

Which cities in Saudi Arabia are leading in this market?

What types of solutions are included in the market segmentation?

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