Embedded AI Market was valued at USD 8.79 billion in 2023 and is expected to reach USD 29.07 billion by 2032, growing at a CAGR of 14.28% from 2024-2032. This market is driven by increasing consumer adoption of AI-driven technologies, coupled with significant investments in AI research and development. Ongoing advancements in AI technology and its integration into various applications, including edge devices, are reshaping the industry. Additionally, trends towards cost reduction in AI hardware and software solutions are expected to fuel growth. However, the rise in security breach incidents remains a concern, prompting continuous improvements in cybersecurity measures. This report delves into these factors, analyzing market dynamics and future growth prospects.
Drivers
Increasing IoT Adoption Drives Demand for Embedded AI Solutions in Real-Time, Smarter Devices Across Multiple Industries
As IoT expands, more devices need high-end abilities to process and evaluate data in real-time. Introducing AI on these embedded devices directly means on-the-spot decision-making at the device level with no delays required by cloud computing. The feature of local processing is necessary in IoT applications because they frequently demand critical operations to be carried out within tight deadlines. Healthcare, automotive, and manufacturing industries are using embedded AI to improve automation, predictive maintenance, and smart interactions between devices. The increasing growth of IoT networks, along with the need for more efficient and responsive systems, heavily contributes to the demand for embedded AI solutions in different industries.
Restraints
Power Consumption Challenges Limit the Widespread Adoption of Embedded AI in Power-Sensitive Applications like Portable Devices
AI processes are highly computational intensive, and hence they tend to consume high power. This proves to be a significant problem for those applications that depend on battery-powered or power-constrained devices, including mobile electronics and IoT devices. The computational intensity of AI depletes battery life in a matter of time, curtailing the feasibility of embedded AI in these devices. In energy-limited settings, including wearables and remote sensors, performance versus energy efficiency becomes a vital challenge. In addition, minimizing power consumption in embedded AI systems without affecting functionality calls for continuous innovation in hardware design and energy-efficient AI models. Consequently, power consumption is a critical factor that affects the widespread deployment of embedded AI in some applications.
Opportunities
Edge Computing Integration Enhances Real-Time Data Processing and Decision-Making, Driving Growth in the Embedded AI Market
With industries transitioning to edge computing, the embedding of AI in edge devices is increasingly valuable for real-time data processing and decision-making. Such integration enables quicker, more streamlined operations through direct processing of data on devices, decreasing latency and reliance on cloud infrastructure. In use cases like autonomous cars, industrial automation, and IoT devices, where real-time decision-making is paramount, edge AI facilitates intelligent and faster responses. This change has immense possibilities in industries like healthcare, manufacturing, and consumer electronics, where real-time intelligence is essential to boost functionality and performance. The widespread adoption of 5G networks also hastens the need for edge AI solutions, creating huge growth prospects for the embedded AI market.
Challenges
Data Privacy and Security Concerns Challenge the Adoption of AI-Powered Embedded Devices, Especially in Healthcare and Finance
Data security and privacy are ever more essential in AI-based embedded devices, particularly in healthcare and finance industries, where confidential information is being dealt with. Embedded AI systems are constantly collecting and processing massive amounts of data, so securing this data from hacks and misuse is a challenge of utmost importance. The decentralized character of embedded devices also makes it more difficult to impose standard security controls, opening up devices to vulnerabilities. Additionally, data privacy regulation requirements, e.g., GDPR, further complicate the security of AI-based embedded systems. With the increased dependence on IoT and networked devices, mitigating these security and privacy issues is imperative for building confidence and encouraging continued use of embedded AI technologies in safety-critical applications.
By Data Type
The Numeric Data segment dominated the Embedded AI Market with the highest revenue share of about 31% in 2023. This dominance is attributed to the increasing use of numerical data for decision-making, predictions, and analytics in industries such as finance, automotive, and manufacturing. Embedded AI systems process vast amounts of numeric data to deliver accurate, real-time insights and improve operational efficiency, making it a critical component for businesses looking to enhance productivity and decision-making processes.
The Sensor Data segment is expected to grow at the fastest CAGR of about 16.21% from 2024-2032. This rapid growth is driven by the increasing deployment of IoT devices and the need for real-time data collection from sensors. AI-driven analysis of sensor data allows for smarter, more efficient systems in applications like autonomous vehicles, smart cities, healthcare monitoring, and industrial automation, where real-time responsiveness and predictive maintenance are crucial for success.
By Offering
The Hardware segment dominated the Embedded AI Market with the highest revenue share of about 44% in 2023. This dominance is driven by the increasing demand for powerful, energy-efficient processors and chips that can handle AI computations within embedded systems. Specialized hardware, such as edge devices, AI accelerators, and custom-designed processors, is critical to supporting real-time data processing in sectors like automotive, healthcare, and industrial automation, making it a vital component of AI-driven embedded solutions.
The Software segment is expected to grow at the fastest CAGR of about 15.68% from 2024-2032. This rapid growth is fueled by the rising demand for AI frameworks, algorithms, and machine learning models that can be integrated into embedded systems. The increasing focus on AI software development platforms, enabling faster deployment of AI applications, and the growing trend of software-as-a-service (SaaS) solutions drive the expansion of the software segment, particularly in IoT and automation industries.
By Vertical
The Automotive segment dominated the Embedded AI Market with the highest revenue share of about 24% in 2023. This dominance is driven by the increasing adoption of AI for advanced driver-assistance systems, autonomous vehicles, and smart infotainment systems. AI enables real-time decision-making, enhancing safety features such as collision avoidance, lane detection, and adaptive cruise control. Additionally, the growing demand for electric vehicles and connected car technologies further accelerates the integration of AI in the automotive sector.
The Healthcare segment is expected to grow at the fastest CAGR of about 16.13% from 2024-2032. This rapid growth is attributed to the increasing need for advanced healthcare solutions, such as AI-powered diagnostics, predictive analytics, and personalized treatment plans. Embedded AI enables faster, more accurate decision-making, improving patient care and operational efficiency in healthcare settings. The rising adoption of wearable health devices and telemedicine also contributes to this robust market expansion.
Regional Analysis
North America dominated the Embedded AI Market with the highest revenue share of about 35% in 2023. This dominance is primarily due to the region's strong technological infrastructure, significant investments in AI research and development, and high adoption rates of AI across various industries, including automotive, healthcare, and manufacturing. The presence of major players in AI hardware and software development further bolsters the region’s market leadership, along with strong government support for AI innovation and integration.
Asia Pacific is expected to grow at the fastest CAGR of about 16.38% from 2024-2032. This rapid growth is driven by the region’s expanding manufacturing sector, the rising adoption of IoT and automation technologies, and significant investments in AI by countries like China, Japan, and India. Additionally, the growing focus on smart city initiatives, industrial robotics, and the rapid digital transformation across key industries contribute to the region's fast-paced market expansion.
HPE (HPE Edgeline Converged Edge Systems, HPE ProLiant Servers)
Google (TensorFlow, Edge TPU)
IBM (IBM Watson, IBM Edge Application Manager)
Intel (Intel Movidius, Intel Neural Compute Stick)
LUIS Technology (LUIS Edge AI, LUIS AI Modules)
Microsoft (Azure IoT, Microsoft Azure Percept)
NVIDIA (Jetson Nano, NVIDIA TensorRT)
Oracle (Oracle AI Platform, Oracle Cloud Infrastructure)
Qualcomm (Snapdragon, Qualcomm AI Engine)
Salesforce (Salesforce Einstein, Salesforce IoT)
Siemens (Siemens Industrial Edge, MindSphere)
LUIS Technology (LUIS Edge AI, LUIS AI Modules)
Code Time Technologies (AI Time Series Analyzer, Real-Time AI Engine)
HiSilicon (Ascend AI Processor, Kirin AI)
VectorBlox (VectorBlox AI Accelerator, VectorBlox Vision AI)
AU-Zone Technologies (AIoT Edge Platform, Embedded AI Module)
STMicroelectronics (STM32, STAI Processor)
SenseTime (AI Edge Solutions, Face Recognition AI)
Edge Impulse (Edge Impulse Studio, Edge Impulse SDK)
Perceive (Perceive AI Edge Processor, Perceive Edge Vision)
Eta Compute (Eta AI Chip, Eta Edge Platform)
SensiML (SensiML Analytics Studio, SensiML SensorFusion)
Syntiant (Syntiant NDP, NDP Chipset)
Graphcore (IPU-POD, Graphcore IPU)
In 2024, STMicroelectronics showcased its latest embedded AI innovations at Embedded World, highlighting the power of edge AI in reducing latency, improving privacy, and enabling real-time decision-making in various applications
In 2024, Edge Impulse participated in Embedded World, showcasing its platform's capabilities for building and deploying edge AI solutions, in collaboration with partners like Nordic Semiconductor.
| Report Attributes | Details |
|---|---|
| Market Size in 2023 | USD 8.79 Billion |
| Market Size by 2032 | USD 29.07 Billion |
| CAGR | CAGR of 14.28% From 2024 to 2032 |
| Base Year | 2023 |
| Forecast Period | 2024-2032 |
| Historical Data | 2020-2022 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Offering (Hardware, Software, Services) • By Data Type (Sensor Data, Image & Video Data, Numeric Data, Categorical Data, Others) • By Vertical (Healthcare, BFSI, IT & Telecom, Retail, Media & Entertainment, Automotive, Manufacturing, Others) |
| Regional Analysis/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) |
| Company Profiles | HPE, Google, IBM, Intel, LUIS Technology, Microsoft, NVIDIA, Oracle, Qualcomm, Salesforce, Siemens, Code Time Technologies, HiSilicon, VectorBlox, AU-Zone Technologies, STMicroelectronics, SenseTime, Edge Impulse, Perceive, Eta Compute, SensiML, Syntiant, Graphcore |
ANS: Embedded AI Market was valued at USD 8.79 billion in 2023 and is expected to reach USD 29.07 billion by 2032, growing at a CAGR of 14.28% from 2024-2032
ANS: The Hardware segment dominated the Embedded AI Market in 2023, with a significant share of about 44%, driven by the increasing demand for powerful processors and chips capable of handling AI computations in embedded systems.
ANS: North America dominated the Embedded AI Market with a revenue share of about 35% in 2023, due to strong technological infrastructure, substantial investments in AI R&D.
ANS: The Automotive segment dominated the market with a revenue share of about 24% in 2023, driven by the increasing adoption of AI for autonomous vehicles, driver-assistance systems, and smart infotainment technologies.
ANS: The integration of AI in edge computing devices presents a key opportunity for the Embedded AI Market, enabling real-time decision-making, faster data processing.
Table of Contents:
1. Introduction
1.1 Market Definition
1.2 Scope (Inclusion and Exclusions)
1.3 Research Assumptions
2. Executive Summary
2.1 Market Overview
2.2 Regional Synopsis
2.3 Competitive Summary
3. Research Methodology
3.1 Top-Down Approach
3.2 Bottom-up Approach
3.3. Data Validation
3.4 Primary Interviews
4. Market Dynamics Impact Analysis
4.1 Market Driving Factors Analysis
4.1.1 Drivers
4.1.2 Restraints
4.1.3 Opportunities
4.1.4 Challenges
4.2 PESTLE Analysis
4.3 Porter’s Five Forces Model
5. Statistical Insights and Trends Reporting
5.1 Consumer Adoption Rate
5.2 Investment Trends
5.3 Technology Development
5.4 Cost Reduction Trends
5.5 Security Breach Incidence
6. Competitive Landscape
6.1 List of Major Companies, By Region
6.2 Market Share Analysis, By Region
6.3 Product Benchmarking
6.3.1 Product specifications and features
6.3.2 Pricing
6.4 Strategic Initiatives
6.4.1 Marketing and promotional activities
6.4.2 Distribution and supply chain strategies
6.4.3 Expansion plans and new product launches
6.4.4 Strategic partnerships and collaborations
6.5 Technological Advancements
6.6 Market Positioning and Branding
7. Embedded AI Market Segmentation, By Offering
7.1 Chapter Overview
7.2 Hardware
7.2.1 Hardware Market Trends Analysis (2020-2032)
7.2.2 Hardware Market Size Estimates and Forecasts to 2032 (USD Billion)
7.3 Software
7.3.1 Software Market Trends Analysis (2020-2032)
7.3.2 Software Market Size Estimates and Forecasts to 2032 (USD Billion)
7.4 Services
7.4.1 Services Market Trends Analysis (2020-2032)
7.4.2 Services Market Size Estimates and Forecasts to 2032 (USD Billion)
8. Embedded AI Market Segmentation, By Data Type
8.1 Chapter Overview
8.2 Sensor Data
8.2.1 Sensor Data Market Trends Analysis (2020-2032)
8.2.2 Sensor Data Market Size Estimates and Forecasts to 2032 (USD Billion)
8.3 Image & Video Data
8.3.1 Image & Video Data Market Trends Analysis (2020-2032)
8.3.2 Image & Video Data Market Size Estimates and Forecasts to 2032 (USD Billion)
8.4 Numeric Data
8.4.1 Numeric Data Market Trends Analysis (2020-2032)
8.4.2 Numeric Data Market Size Estimates and Forecasts to 2032 (USD Billion)
8.5 Categorial Data
8.5.1 Categorial Data Market Trends Analysis (2020-2032)
8.5.2 Categorial Data Market Size Estimates and Forecasts to 2032 (USD Billion)
8.6 Others
8.6.1 Others Market Trends Analysis (2020-2032)
8.6.2 Others Market Size Estimates and Forecasts to 2032 (USD Billion)
9. Embedded AI Market Segmentation, By Vertical
9.1 Chapter Overview
9.2 Healthcare
9.2.1 Healthcare Market Trends Analysis (2020-2032)
9.2.2 Healthcare Market Size Estimates and Forecasts to 2032 (USD Billion)
9.3 BFSI
9.3.1 BFSI Market Trends Analysis (2020-2032)
9.3.2 BFSI Market Size Estimates and Forecasts to 2032 (USD Billion)
9.4 IT & Telecom
9.4.1 IT & Telecom Market Trends Analysis (2020-2032)
9.4.2 IT & Telecom Market Size Estimates and Forecasts to 2032 (USD Billion)
9.5 Retail
9.5.1 Retail Market Trends Analysis (2020-2032)
9.5.2 Retail Market Size Estimates and Forecasts to 2032 (USD Billion)
9.6 Media & Entertainment
9.6.1 Media & Entertainment Market Trends Analysis (2020-2032)
9.6.2 Media & Entertainment Market Size Estimates and Forecasts to 2032 (USD Billion)
9.7 Automotive
9.7.1 Automotive Market Trends Analysis (2020-2032)
9.7.2 Automotive Market Size Estimates and Forecasts to 2032 (USD Billion)
9.8 Manufacturing
9.8.1 Manufacturing Market Trends Analysis (2020-2032)
9.8.2 Manufacturing Market Size Estimates and Forecasts to 2032 (USD Billion)
9.9 Others
9.9.1 Others Market Trends Analysis (2020-2032)
9.9.2 Others Market Size Estimates and Forecasts to 2032 (USD Billion)
10. Regional Analysis
10.1 Chapter Overview
10.2 North America
10.2.1 Trends Analysis
10.2.2 North America Embedded AI Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.2.3 North America Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.2.4 North America Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.2.5 North America Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.2.6 USA
10.2.6.1 USA Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.2.6.2 USA Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.2.6.3 USA Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.2.7 Canada
10.2.7.1 Canada Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.2.7.2 Canada Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.2.7.3 Canada Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.2.8 Mexico
10.2.8.1 Mexico Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.2.8.2 Mexico Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.2.8.3 Mexico Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3 Europe
10.3.1 Eastern Europe
10.3.1.1 Trends Analysis
10.3.1.2 Eastern Europe Embedded AI Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.3.1.3 Eastern Europe Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.1.4 Eastern Europe Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.1.5 Eastern Europe Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.1.6 Poland
10.3.1.6.1 Poland Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.1.6.2 Poland Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.1.6.3 Poland Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.1.7 Romania
10.3.1.7.1 Romania Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.1.7.2 Romania Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.1.7.3 Romania Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.1.8 Hungary
10.3.1.8.1 Hungary Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.1.8.2 Hungary Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.1.8.3 Hungary Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.1.9 Turkey
10.3.1.9.1 Turkey Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.1.9.2 Turkey Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.1.9.3 Turkey Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.1.10 Rest of Eastern Europe
10.3.1.10.1 Rest of Eastern Europe Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.1.10.2 Rest of Eastern Europe Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.1.10.3 Rest of Eastern Europe Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.2 Western Europe
10.3.2.1 Trends Analysis
10.3.2.2 Western Europe Embedded AI Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.3.2.3 Western Europe Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.2.4 Western Europe Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.2.5 Western Europe Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.2.6 Germany
10.3.2.6.1 Germany Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.2.6.2 Germany Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.2.6.3 Germany Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.2.7 France
10.3.2.7.1 France Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.2.7.2 France Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.2.7.3 France Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.2.8 UK
10.3.2.8.1 UK Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.2.8.2 UK Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.2.8.3 UK Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.2.9 Italy
10.3.2.9.1 Italy Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.2.9.2 Italy Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.2.9.3 Italy Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.2.10 Spain
10.3.2.10.1 Spain Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.2.10.2 Spain Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.2.10.3 Spain Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.2.11 Netherlands
10.3.2.11.1 Netherlands Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.2.11.2 Netherlands Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.2.11.3 Netherlands Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.2.12 Switzerland
10.3.2.12.1 Switzerland Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.2.12.2 Switzerland Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.2.12.3 Switzerland Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.2.13 Austria
10.3.2.13.1 Austria Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.2.13.2 Austria Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.2.13.3 Austria Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.3.2.14 Rest of Western Europe
10.3.2.14.1 Rest of Western Europe Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.3.2.14.2 Rest of Western Europe Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.3.2.14.3 Rest of Western Europe Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.4 Asia Pacific
10.4.1 Trends Analysis
10.4.2 Asia Pacific Embedded AI Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.4.3 Asia Pacific Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.4.4 Asia Pacific Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.4.5 Asia Pacific Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.4.6 China
10.4.6.1 China Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.4.6.2 China Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.4.6.3 China Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.4.7 India
10.4.7.1 India Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.4.7.2 India Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.4.7.3 India Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.4.8 Japan
10.4.8.1 Japan Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.4.8.2 Japan Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.4.8.3 Japan Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.4.9 South Korea
10.4.9.1 South Korea Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.4.9.2 South Korea Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.4.9.3 South Korea Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.4.10 Vietnam
10.4.10.1 Vietnam Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.4.10.2 Vietnam Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.4.10.3 Vietnam Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.4.11 Singapore
10.4.11.1 Singapore Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.4.11.2 Singapore Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.4.11.3 Singapore Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.4.12 Australia
10.4.12.1 Australia Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.4.12.2 Australia Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.4.12.3 Australia Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.4.13 Rest of Asia Pacific
10.4.13.1 Rest of Asia Pacific Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.4.13.2 Rest of Asia Pacific Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.4.13.3 Rest of Asia Pacific Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.5 Middle East and Africa
10.5.1 Middle East
10.5.1.1 Trends Analysis
10.5.1.2 Middle East Embedded AI Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.5.1.3 Middle East Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.5.1.4 Middle East Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.5.1.5 Middle East Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.5.1.6 UAE
10.5.1.6.1 UAE Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.5.1.6.2 UAE Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.5.1.6.3 UAE Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.5.1.7 Egypt
10.5.1.7.1 Egypt Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.5.1.7.2 Egypt Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.5.1.7.3 Egypt Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.5.1.8 Saudi Arabia
10.5.1.8.1 Saudi Arabia Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.5.1.8.2 Saudi Arabia Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.5.1.8.3 Saudi Arabia Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.5.1.9 Qatar
10.5.1.9.1 Qatar Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.5.1.9.2 Qatar Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.5.1.9.3 Qatar Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.5.1.10 Rest of Middle East
10.5.1.10.1 Rest of Middle East Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.5.1.10.2 Rest of Middle East Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.5.1.10.3 Rest of Middle East Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.5.2 Africa
10.5.2.1 Trends Analysis
10.5.2.2 Africa Embedded AI Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.5.2.3 Africa Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.5.2.4 Africa Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.5.2.5 Africa Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.5.2.6 South Africa
10.5.2.6.1 South Africa Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.5.2.6.2 South Africa Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.5.2.6.3 South Africa Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.5.2.7 Nigeria
10.5.2.7.1 Nigeria Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.5.2.7.2 Nigeria Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.5.2.7.3 Nigeria Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.5.2.8 Rest of Africa
10.5.2.8.1 Rest of Africa Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.5.2.8.2 Rest of Africa Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.5.2.8.3 Rest of Africa Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.6 Latin America
10.6.1 Trends Analysis
10.6.2 Latin America Embedded AI Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.6.3 Latin America Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.6.4 Latin America Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.6.5 Latin America Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.6.6 Brazil
10.6.6.1 Brazil Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.6.6.2 Brazil Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.6.6.3 Brazil Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.6.7 Argentina
10.6.7.1 Argentina Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.6.7.2 Argentina Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.6.7.3 Argentina Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.6.8 Colombia
10.6.8.1 Colombia Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.6.8.2 Colombia Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.6.8.3 Colombia Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
10.6.9 Rest of Latin America
10.6.9.1 Rest of Latin America Embedded AI Market Estimates and Forecasts, By Offering (2020-2032) (USD Billion)
10.6.9.2 Rest of Latin America Embedded AI Market Estimates and Forecasts, By Data Type (2020-2032) (USD Billion)
10.6.9.3 Rest of Latin America Embedded AI Market Estimates and Forecasts, By Vertical (2020-2032) (USD Billion)
11. Company Profiles
11.1 HPE
11.1.1 Company Overview
11.1.2 Financial
11.1.3 Products/ Services Offered
11.1.4 SWOT Analysis
11.2 Google
11.2.1 Company Overview
11.2.2 Financial
11.2.3 Products/ Services Offered
11.2.4 SWOT Analysis
11.3 IBM
11.3.1 Company Overview
11.3.2 Financial
11.3.3 Products/ Services Offered
11.3.4 SWOT Analysis
11.4 Intel
11.4.1 Company Overview
11.4.2 Financial
11.4.3 Products/ Services Offered
11.4.4 SWOT Analysis
11.5 LUIS Technology
11.5.1 Company Overview
11.5.2 Financial
11.5.3 Products/ Services Offered
11.5.4 SWOT Analysis
11.6 Microsoft
11.6.1 Company Overview
11.6.2 Financial
11.6.3 Products/ Services Offered
11.6.4 SWOT Analysis
11.7 NVIDIA
11.7.1 Company Overview
11.7.2 Financial
11.7.3 Products/ Services Offered
11.7.4 SWOT Analysis
11.8 Oracle
11.8.1 Company Overview
11.8.2 Financial
11.8.3 Products/ Services Offered
11.8.4 SWOT Analysis
11.9 Qualcomm
11.9.1 Company Overview
11.9.2 Financial
11.9.3 Products/ Services Offered
11.9.4 SWOT Analysis
11.10 Salesforce
11.10.1 Company Overview
11.10.2 Financial
11.10.3 Products/ Services Offered
11.10.4 SWOT Analysis
12. Use Cases and Best Practices
13. Conclusion
An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.
Each report that we prepare takes a timeframe of 350-400 business hours for production. Starting from the selection of titles through a couple of in-depth brain storming session to the final QC process before uploading our titles on our website we dedicate around 350 working hours. The titles are selected based on their current market cap and the foreseen CAGR and growth.
The 5 steps process:
Step 1: Secondary Research:
Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.
Step 2: Primary Research
When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data. This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.
We at SNS Insider have divided Primary Research into 2 parts.
Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.
This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.
Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.
Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.
Step 3: Data Bank Validation
Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.
Step 4: QA/QC Process
After all the data collection and validation our team does a final level of quality check and quality assurance to get rid of any unwanted or undesired mistakes. This might include but not limited to getting rid of the any typos, duplication of numbers or missing of any important information. The people involved in this process include technical content writers, research heads and graphics people. Once this process is completed the title gets uploader on our platform for our clients to read it.
Step 5: Final QC/QA Process:
This is the last process and comes when the client has ordered the study. In this process a final QA/QC is done before the study is emailed to the client. Since we believe in giving our clients a good experience of our research studies, therefore, to make sure that we do not lack at our end in any way humanly possible we do a final round of quality check and then dispatch the study to the client.
Key Segments:
By Offering
Hardware
Software
Services
By Data Type
Sensor Data
Image & Video Data
Numeric Data
Categorial Data
Others
By Vertical
Healthcare
BFSI
IT & Telecom
Retail
Media & Entertainment
Automotive
Manufacturing
Others
Request for Segment Customization as per your Business Requirement: Segment Customization Request
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
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Available Customization
With the given market data, SNS Insider offers customization as per the company’s specific needs. The following customization options are available for the report:
Detailed Volume Analysis
Criss-Cross segment analysis (e.g. Product X Application)
Competitive Product Benchmarking
Geographic Analysis
Additional countries in any of the regions
Customized Data Representation
Detailed analysis and profiling of additional market players
The P2P Payment Market Size was USD 256.5 Billion in 2023 & is expected to reach USD 901.3 Bn by 2032 & grow at a CAGR of 15%, forecast period of 2024-2032.
The Green Data Center Market size was valued at USD 62.9 billion in 2023 and will reach USD 272.2 billion by 2032 and grow at a CAGR of 17.7% by 2032.
The Software as a Service (SaaS) Market size was recorded at USD 335.21 billion in 2023 and is expected to reach USD 1057.8 billion by 2032, growing at a CAGR of 13.62 % over the forecast period of 2024-2032.
The Deepfake AI Market was valued at USD 563.6 Million in 2023 and is expected to reach USD 13889.8 Million by 2032, growing at a CAGR of 42.79% by 2032.
The Cloud Radio Access Network (C-RAN) Ecosystem Market Size was valued at USD 15.89 Billion in 2023 and is expected to reach USD 101.02 Billion by 2032 and grow at a CAGR of 23.07% over the forecast period 2024-2032.
The Web Hosting Services Market Size was valued at USD 103.1 Billion in 2023 and will reach USD 508.0 Billion by 2032, growing at a CAGR of 19.4% by 2032.
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