PUBLISHER: Prescient & Strategic Intelligence | PRODUCT CODE: 1596094
PUBLISHER: Prescient & Strategic Intelligence | PRODUCT CODE: 1596094
Edge AI Software Market Size & Share Analysis - Trends, Drivers, Competitive Landscape, and Forecasts (2025 - 2030)
Market Overview
The global edge AI software market is projected to generate $1,459.0 million in revenue in 2024 and is expected to reach $8,218.0 million by 2030, reflecting a compound annual growth rate (CAGR) of 33.4% during the forecast period from 2024 to 2030. This significant growth is primarily driven by the rise of 5G networks, the growing use of Internet of Things (IoT) devices, and the increasing requirement for real-time data processing. The integration of artificial intelligence (AI) into edge computing enables organizations to enhance operations and analyze data collected by edge devices more efficiently. Additionally, the expanding usage of e-commerce platforms, social media, and cloud-based edge ecosystems is further propelling market expansion.
Key Insights
The edge AI software market is segmented by component into solutions and services. Solutions encompass software platforms and tools that facilitate the deployment and management of AI applications at the edge, while services include consulting, integration, and support services. The increasing adoption of AI-driven solutions across various industries is contributing to the growth of both segments.
In terms of deployment mode, the market is divided into cloud and on-premises. Cloud deployment offers scalability and flexibility, allowing organizations to manage AI applications remotely. On-premises deployment provides enhanced security and control over data, which is crucial for industries with stringent compliance requirements. The choice between deployment modes depends on factors such as data sensitivity, regulatory considerations, and organizational preferences.
The market is further categorized by data type, including video and image data, audio data, text and language data, environmental and location data, biometric data, and multi-modal data. The proliferation of IoT devices and the need for real-time analytics are driving the demand for edge AI software capable of processing diverse data types at the edge. For instance, video and image data processing is essential for applications like surveillance and autonomous vehicles, while audio data processing is vital for voice recognition systems.
End-user industries for edge AI software encompass manufacturing, healthcare, banking, financial services, and insurance (BFSI), government, defense and aerospace, retail and e-commerce, telecommunications, and transport and logistics. The manufacturing sector is leveraging edge AI for predictive maintenance and quality control, while the healthcare industry utilizes it for patient monitoring and diagnostics. The BFSI sector employs edge AI for fraud detection and risk assessment, and the retail and e-commerce industries use it to enhance customer experiences through personalized services.
Geographically, North America holds the largest share of the edge AI software market, attributed to the early adoption of advanced technologies and the presence of key industry players. The Asia-Pacific region is expected to witness the fastest growth during the forecast period, driven by rapid industrialization, increasing investments in AI and IoT technologies, and supportive government initiatives promoting digital transformation.
Technological advancements are significantly shaping the edge AI software market. The integration of AI with edge computing enables real-time processing and reduced latency, facilitating faster and more accurate decision-making in critical applications such as autonomous vehicles, industrial automation, and smart cities. The deployment of 5G networks enhances connectivity and supports the seamless operation of edge AI applications, further driving market growth.
The market is characterized by fragmentation, with numerous players offering diverse solutions tailored to various industry needs. Key companies are focusing on strategic initiatives such as mergers, acquisitions, and partnerships to expand their product portfolios and global reach. The increasing emphasis on real-time data processing, coupled with the growing adoption of IoT devices, presents significant opportunities for innovation and growth within the edge AI software market. As organizations continue to seek efficient and scalable solutions to process data at the edge, the adoption of edge AI software is expected to rise, driving the market's expansion in the coming years.
Table of Contents
Chapter 1. Research Scope
- 1.1. Research Objectives
- 1.2. Market Definition
- 1.3. Analysis Period
- 1.4. Market Size Breakdown by Segments
- 1.4.1. Market size breakdown, by component
- 1.4.2. Market size breakdown, by deployment mode
- 1.4.3. Market size breakdown, by data type
- 1.4.4. Market size breakdown, by end user
- 1.4.5. Market size breakdown, by region
- 1.4.6. Market size breakdown, by country
- 1.5. Market Data Reporting Unit
- 1.5.1. Value
- 1.6. Key Stakeholders
Chapter 2. Research Methodology
- 2.1. Secondary Research
- 2.1.1. Paid
- 2.1.2. Unpaid
- 2.1.3. P&S Intelligence database
- 2.2. Primary Research
- 2.3. Market Size Estimation
- 2.4. Data Triangulation
- 2.5. Currency Conversion Rates
- 2.6. Assumptions for the Study
- 2.7. Notes and Caveats
Chapter 3. Executive Summary
Chapter 4. Market Indicators
Chapter 5. Industry Outlook
- 5.1. Market Dynamics
- 5.1.1. Trends
- 5.1.2. Drivers
- 5.1.3. Restraints/challenges
- 5.1.4. Impact analysis of drivers/restraints
- 5.2. Impact of COVID-19
- 5.3. Porter's Five Forces Analysis
- 5.3.1. Bargaining power of buyers
- 5.3.2. Bargaining power of suppliers
- 5.3.3. Threat of new entrants
- 5.3.4. Intensity of rivalry
- 5.3.5. Threat of substitutes
Chapter 6. Global Market
- 6.1. Overview
- 6.2. Market Revenue, by Component (2019-2030)
- 6.3. Market Revenue, by Deployment Mode (2019-2030)
- 6.4. Market Revenue, by Data Type (2019-2030)
- 6.5. Market Revenue, by End User (2019-2030)
- 6.6. Market Revenue, by Region (2019-2030)
Chapter 7. North America Market
- 7.1. Overview
- 7.2. Market Revenue, by Component (2019-2030)
- 7.3. Market Revenue, by Deployment Mode (2019-2030)
- 7.4. Market Revenue, by Data Type (2019-2030)
- 7.5. Market Revenue, by End User (2019-2030)
- 7.6. Market Revenue, by Country (2019-2030)
Chapter 8. Europe Market
- 8.1. Overview
- 8.2. Market Revenue, by Component (2019-2030)
- 8.3. Market Revenue, by Deployment Mode (2019-2030)
- 8.4. Market Revenue, by Data Type (2019-2030)
- 8.5. Market Revenue, by End User (2019-2030)
- 8.6. Market Revenue, by Country (2019-2030)
Chapter 9. APAC Market
- 9.1. Overview
- 9.2. Market Revenue, by Component (2019-2030)
- 9.3. Market Revenue, by Deployment Mode (2019-2030)
- 9.4. Market Revenue, by Data Type (2019-2030)
- 9.5. Market Revenue, by End User (2019-2030)
- 9.6. Market Revenue, by Country (2019-2030)
Chapter 10. LATAM Market
- 10.1. Overview
- 10.2. Market Revenue, by Component (2019-2030)
- 10.3. Market Revenue, by Deployment Mode (2019-2030)
- 10.4. Market Revenue, by Data Type (2019-2030)
- 10.5. Market Revenue, by End User (2019-2030)
- 10.6. Market Revenue, by Country (2019-2030)
Chapter 11. MEA Market
- 11.1. Overview
- 11.2. Market Revenue, by Component (2019-2030)
- 11.3. Market Revenue, by Deployment Mode (2019-2030)
- 11.4. Market Revenue, by Data Type (2019-2030)
- 11.5. Market Revenue, by End User (2019-2030)
- 11.6. Market Revenue, by Country (2019-2030)
Chapter 12. U.S. Market
- 12.1. Overview
- 12.2. Market Revenue, by Component (2019-2030)
- 12.3. Market Revenue, by Deployment Mode (2019-2030)
- 12.4. Market Revenue, by Data Type (2019-2030)
- 12.5. Market Revenue, by End User (2019-2030)
Chapter 13. Canada Market
- 13.1. Overview
- 13.2. Market Revenue, by Component (2019-2030)
- 13.3. Market Revenue, by Deployment Mode (2019-2030)
- 13.4. Market Revenue, by Data Type (2019-2030)
- 13.5. Market Revenue, by End User (2019-2030)
Chapter 14. Germany Market
- 14.1. Overview
- 14.2. Market Revenue, by Component (2019-2030)
- 14.3. Market Revenue, by Deployment Mode (2019-2030)
- 14.4. Market Revenue, by Data Type (2019-2030)
- 14.5. Market Revenue, by End User (2019-2030)
Chapter 15. France Market
- 15.1. Overview
- 15.2. Market Revenue, by Component (2019-2030)
- 15.3. Market Revenue, by Deployment Mode (2019-2030)
- 15.4. Market Revenue, by Data Type (2019-2030)
- 15.5. Market Revenue, by End User (2019-2030)
Chapter 16. U.K. Market
- 16.1. Overview
- 16.2. Market Revenue, by Component (2019-2030)
- 16.3. Market Revenue, by Deployment Mode (2019-2030)
- 16.4. Market Revenue, by Data Type (2019-2030)
- 16.5. Market Revenue, by End User (2019-2030)
Chapter 17. Italy Market
- 17.1. Overview
- 17.2. Market Revenue, by Component (2019-2030)
- 17.3. Market Revenue, by Deployment Mode (2019-2030)
- 17.4. Market Revenue, by Data Type (2019-2030)
- 17.5. Market Revenue, by End User (2019-2030)
Chapter 18. Spain Market
- 18.1. Overview
- 18.2. Market Revenue, by Component (2019-2030)
- 18.3. Market Revenue, by Deployment Mode (2019-2030)
- 18.4. Market Revenue, by Data Type (2019-2030)
- 18.5. Market Revenue, by End User (2019-2030)
Chapter 19. Japan Market
- 19.1. Overview
- 19.2. Market Revenue, by Component (2019-2030)
- 19.3. Market Revenue, by Deployment Mode (2019-2030)
- 19.4. Market Revenue, by Data Type (2019-2030)
- 19.5. Market Revenue, by End User (2019-2030)
Chapter 20. China Market
- 20.1. Overview
- 20.2. Market Revenue, by Component (2019-2030)
- 20.3. Market Revenue, by Deployment Mode (2019-2030)
- 20.4. Market Revenue, by Data Type (2019-2030)
- 20.5. Market Revenue, by End User (2019-2030)
Chapter 21. India Market
- 21.1. Overview
- 21.2. Market Revenue, by Component (2019-2030)
- 21.3. Market Revenue, by Deployment Mode (2019-2030)
- 21.4. Market Revenue, by Data Type (2019-2030)
- 21.5. Market Revenue, by End User (2019-2030)
Chapter 22. Australia Market
- 22.1. Overview
- 22.2. Market Revenue, by Component (2019-2030)
- 22.3. Market Revenue, by Deployment Mode (2019-2030)
- 22.4. Market Revenue, by Data Type (2019-2030)
- 22.5. Market Revenue, by End User (2019-2030)
Chapter 23. South Korea Market
- 23.1. Overview
- 23.2. Market Revenue, by Component (2019-2030)
- 23.3. Market Revenue, by Deployment Mode (2019-2030)
- 23.4. Market Revenue, by Data Type (2019-2030)
- 23.5. Market Revenue, by End User (2019-2030)
Chapter 24. Brazil Market
- 24.1. Overview
- 24.2. Market Revenue, by Component (2019-2030)
- 24.3. Market Revenue, by Deployment Mode (2019-2030)
- 24.4. Market Revenue, by Data Type (2019-2030)
- 24.5. Market Revenue, by End User (2019-2030)
Chapter 25. Mexico Market
- 25.1. Overview
- 25.2. Market Revenue, by Component (2019-2030)
- 25.3. Market Revenue, by Deployment Mode (2019-2030)
- 25.4. Market Revenue, by Data Type (2019-2030)
- 25.5. Market Revenue, by End User (2019-2030)
Chapter 26. Saudi Arabia Market
- 26.1. Overview
- 26.2. Market Revenue, by Component (2019-2030)
- 26.3. Market Revenue, by Deployment Mode (2019-2030)
- 26.4. Market Revenue, by Data Type (2019-2030)
- 26.5. Market Revenue, by End User (2019-2030)
Chapter 27. South Africa Market
- 27.1. Overview
- 27.2. Market Revenue, by Component (2019-2030)
- 27.3. Market Revenue, by Deployment Mode (2019-2030)
- 27.4. Market Revenue, by Data Type (2019-2030)
- 27.5. Market Revenue, by End User (2019-2030)
Chapter 28. U.A.E. Market
- 28.1. Overview
- 28.2. Market Revenue, by Component (2019-2030)
- 28.3. Market Revenue, by Deployment Mode (2019-2030)
- 28.4. Market Revenue, by Data Type (2019-2030)
- 28.5. Market Revenue, by End User (2019-2030)
Chapter 29. Competitive Landscape
- 29.1. List of Market Players and their Offerings
- 29.2. Competitive Benchmarking of Key Players
- 29.3. Product Benchmarking of Key Players
- 29.4. Recent Strategic Developments
Chapter 30. Company Profiles
- 30.1. Microsoft Corporation
- 30.1.1. Business overview
- 30.1.2. Product and service offerings
- 30.1.3. Key financial summary
- 30.2. International Business Machines Corporation
- 30.2.1. Business overview
- 30.2.2. Product and service offerings
- 30.2.3. Key financial summary
- 30.3. NVIDIA Corporation
- 30.3.1. Business overview
- 30.3.2. Product and service offerings
- 30.3.3. Key financial summary
- 30.4. Advantech Co. Ltd.
- 30.4.1. Business overview
- 30.4.2. Product and service offerings
- 30.4.3. Key financial summary
- 30.5. Amazon Web Services Inc.
- 30.5.1. Business overview
- 30.5.2. Product and service offerings
- 30.5.3. Key financial summary
- 30.6. Edge Impulse Inc.
- 30.6.1. Business overview
- 30.6.2. Product and service offerings
- 30.6.3. Key financial summary
- 30.7. Nutanix Inc.
- 30.7.1. Business overview
- 30.7.2. Product and service offerings
- 30.7.3. Key financial summary
- 30.8. Vapor IO Inc.
- 30.8.1. Business overview
- 30.8.2. Product and service offerings
- 30.8.3. Key financial summary
- 30.9. Hewlett Packard Enterprise Development LP
- 30.9.1. Business overview
- 30.9.2. Product and service offerings
- 30.9.3. Key financial summary
- 30.10. Intel Corporation
- 30.10.1. Business overview
- 30.10.2. Product and service offerings
- 30.10.3. Key financial summary
- 30.11. Oracle Corporation
- 30.11.1. Business overview
- 30.11.2. Product and service offerings
- 30.11.3. Key financial summary
- 30.12. Gorilla Technology Group
- 30.12.1. Business overview
- 30.12.2. Product and service offerings
- 30.12.3. Key financial summary
- 30.13. Foghorn Systems Inc.
- 30.13.1. Business overview
- 30.13.2. Product and service offerings
- 30.13.3. Key financial summary
- 30.14. Azion Technologies Inc.
- 30.14.1. Business overview
- 30.14.2. Product and service offerings
- 30.14.3. Key financial summary
- 30.15. Akamai Technologies Inc.
- 30.15.1. Business overview
- 30.15.2. Product and service offerings
- 30.15.3. Key financial summary
Chapter 31. Appendix
- 31.1. Abbreviations
- 31.2. Sources and References
- 31.3. Related Reports
