Pune, Dec. 19, 2024 (GLOBE NEWSWIRE) -- Edge AI Software Market Size Analysis:
“The Edge AI Software Market was valued at USD 1.33 Billion in 2023 and is projected to reach USD 13.67 Billion by 2032, growing at a compound annual growth rate (CAGR) of 29.58% from 2024 to 2032.”
Edge AI Software Market Driving Real-Time Intelligence Across Industries
The Edge AI software market is rapidly expanding, driven by the demand for real-time data processing and analysis at the network edge. This technology enables faster decision-making, reduced latency, and increased efficiency across industries such as manufacturing, healthcare, and telecommunications. In healthcare, for instance, edge AI facilitates remote patient monitoring by analyzing data directly on wearable devices, enabling timely interventions. By 2023, AI stroke diagnosis technology will be deployed in every UK stroke center, emphasizing its transformative potential. Globally, AI applications in healthcare are projected to save billions by reducing medication errors and optimizing operational efficiencies, including predictive maintenance for medical devices.
Industries like marketing and telecommunications are harnessing AI to enhance productivity and customer engagement. AI-driven tools, such as chatbots and personalized recommendations, boost efficiency and profitability. With its ability to revolutionize operations and drive innovation, Edge AI is shaping the future of industry and technology.
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Major Players Analysis Listed in this Report are:
- NVIDIA Corporation (NVIDIA Jetson, DeepStream SDK)
- Intel Corporation (OpenVINO, Movidius VPU)
- Qualcomm Technologies (Snapdragon Neural Processing Engine, Qualcomm AI Stack)
- Google LLC (TensorFlow Lite, Edge TPU)
- Microsoft Corporation (Azure IoT Edge, Custom Vision AI)
- Amazon Web Services (AWS) (AWS IoT Greengrass, AWS SageMaker Edge)
- Xilinx, Inc. (Vitis AI, Zynq UltraScale+ MPSoC)
- Huawei Technologies Co., Ltd. (Ascend AI Processors, MindSpore)
- Arm Holdings (Arm Cortex-M, Arm NN SDK)
- Texas Instruments Incorporated (TDA4VM Processors, Edge AI Studio)
- IBM Corporation (IBM Watson IoT, IBM Maximo Visual Inspection)
- Cisco Systems, Inc. (Cisco Edge Intelligence, Cisco Kinetic)
- Siemens AG (MindSphere, Industrial Edge)
- Edge Impulse, Inc. (Edge Impulse Studio, EON Tuner)
- Rockwell Automation (FactoryTalk, Connected Services)
- Samsung Electronics (Samsung ARTIK, SmartThings Cloud)
- Fujitsu Limited (Fujitsu Edge AI, Fujitsu Human Centric AI Zinrai)
- SAP SE (SAP Leonardo, SAP Edge Services)
- Palo Alto Networks (Cortex XSOAR, Prisma Cloud)
- C3.ai (C3 AI Suite, C3 AI Ex Machina)
Edge AI Software Market Report Scope:
| Report Attributes | Details |
| Market Size in 2023 | USD 1.33 Billion |
| Market Size by 2032 | USD 13.67 Billion |
| CAGR | CAGR of 29.58% From 2024 to 2032 |
| Base Year | 2023 |
| Forecast Period | 2024-2032 |
| Historical Data | 2020-2022 |
| Key Regional Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe [Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]). Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia Rest of Latin America) |
| Key Growth Drivers | • The need for immediate data processing is increasing, especially in industries such as healthcare, autonomous vehicles, manufacturing, and telecommunications. • The advancement of 5G technology is greatly enhancing edge AI through facilitating quicker, more dependable, and reduced-latency connectivity. |
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By Offering, Solutions Lead While Services Drive Future Growth in the Edge AI Software Market
In 2023, the Solutions segment captured over 79% of the Edge AI software market share, driven by advanced software frameworks, tools, and platforms that enable real-time AI processing on edge devices. These solutions help businesses implement AI algorithms at the data source, reducing latency and boosting productivity. For example, NVIDIA’s Jetson AI platform allows developers to integrate AI capabilities in sectors like automotive, healthcare, and retail.
The Services segment is projected to grow at the fastest CAGR from 2024 to 2032, fueled by the increasing need for consultation, integration, and maintenance of edge AI deployments. Companies require expert services to incorporate, troubleshoot, and optimize their AI systems. Microsoft Azure’s AI Edge services and IBM’s support services for AI workloads are examples of offerings that assist businesses in smoothly integrating AI models on edge devices across industries such as manufacturing and logistics.
By Data Type, Video and Image Recognition Lead While Audio Data Becomes the Fastest Growing Segment in the Edge AI Software Market
In 2023, Video and Image Recognition captured a 32% Edge AI software market share, driven by its widespread applications in industries like security, healthcare, and retail. The demand for real-time solutions in image analysis, object detection, and facial recognition has surged. Companies like Amazon (AWS DeepLens) and Google (Google Cloud Vision AI) are leveraging this technology to enhance customer experiences and operational efficiency. For example, Tesla relies heavily on video and image recognition in its self-driving cars to process visual data for navigation and security.
The Audio Data segment is projected to experience the fastest CAGR from 2024 to 2032, driven by the rising popularity of voice-controlled devices like Amazon Alexa and Google Assistant. The growing demand for hands-free technology in consumer electronics, automotive, and healthcare sectors is propelling this growth. Companies such as Nuance Communications are offering AI-driven audio solutions for speech recognition in healthcare and automotive applications.
Edge AI Software Market Segmentation:
By Type:
- Simple Programmable Logic Devices
- Complex Programmable Logic Devices
By Product Type:
- 8 Bits
- 16 Bits
- 32 Bits
By Application:
- Telecommunication
- Automotive
- Consumer Electronics
- Healthcare
- Industrial
- Others
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North America Leads While Asia-Pacific Shows the Fastest Growth in the Edge AI Software Market
In 2023, North America held a dominant 35% Edge AI software market share, fueled by rapid AI integration, robust IT infrastructure, and substantial investments from tech giants like IBM, Google, and Microsoft. The region's leadership is bolstered by high demand from industries such as automotive, healthcare, and manufacturing, with companies like Tesla and GE Healthcare utilizing edge AI for autonomous vehicles and predictive diagnostics. Additionally, government initiatives like the U.S. National AI Initiative support this growth.
The Asia-Pacific region is expected to grow at the fastest CAGR between 2024 and 2032, driven by increased digitalization, widespread IoT adoption, and investments in smart cities, particularly in China, Japan, and South Korea. Companies like Huawei and Samsung are advancing edge AI solutions in telecommunications and consumer electronics, while sectors like manufacturing automation and retail, particularly in China, continue to fuel regional growth.
Key Developments in the Edge AI Software Market
- In July 2024, NVIDIA launched its AI Workbench, simplifying the development, testing, and deployment of generative AI models across edge devices.
- In March 2024, Qualcomm introduced Snapdragon Smart Platforms, enhancing AI-driven edge computing for industries like automotive, IoT, and healthcare.
- In November 2023, AWS released IoT Greengrass 3.0, upgrading its edge AI software for IoT devices with improved machine learning models and cloud AI integration.
Table of Contents – Major Key Points
1. Introduction
2. Executive Summary
3. Research Methodology
4. Market Dynamics Impact Analysis
5. Statistical Insights and Trends Reporting
6. Competitive Landscape
7. Edge AI Software Market Segmentation, By Offering
8. Edge AI Software Market Segmentation, By Data Type
9. Edge AI Software Market Segmentation, by Vertical
10. Regional Analysis
11. Company Profiles
12. Use Cases and Best Practices
13. Conclusion
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