Artificial Intelligence (AI) Market Size, Share & Analysis Report, 2022-2030
The global artificial intelligence (AI) market size was estimated at US$ 87.04 billion in 2021 and it is expected to hit US$ 1,597.1 billion by 2030 with a registered CAGR of 38.1% from 2022 to 2030.
-Market-2022-to-2030.jpg "Artificial Intelligence (AI) Market")
Growth Factors:
The continuous research and innovation directed by the tech giants are driving the adoption of advanced technologies in industry verticals, such as automotive, healthcare, retail, finance, and manufacturing. For instance, In November 2020, Intel Corporation acquired Cnvrg.io., an Israeli company that develops and operates a platform for data scientists to build and run machine learning models, to boost Artificial Intelligence (AI) business. However, technology has always been an essential element for these industries, but AI has brought technology to the center of organizations.
For instance, from self-driving vehicles to crucial life-saving medical gear, AI is being infused virtually into every apparatus and program. AI is proven to be a significant revolutionary element of the upcoming digital era. Tech giants like Amazon.com, Inc.; Google LLC; Apple Inc.; Facebook, International Business Machines Corporation, and Microsoft are investing significantly in the research and development of AI. These companies are working to make AI more accessible for enterprise use-cases. Moreover, various companies adopt AI technology to provide a better customer experience. For instance, in March 2020, McDonald’s made its most significant tech investment of USD 300 million to acquire AI start-up Tel Aviv to provide a personalized customer experience using AI.
The essential fact accelerating the rate of innovation in AI is accessibility to historical datasets. Since data storage and recovery have become more economical, healthcare institutions and government agencies build unstructured data accessible to the research domain. Researchers are getting access to rich datasets from historic rain trends to clinical imaging. The next-generation computing architectures, with access to rich datasets, are encouraging information scientists and researchers to innovate faster. Furthermore, progress in profound learning and ANN (Artificial Neural Networks) has also fueled the adoption of AI in several industries, such as aerospace, healthcare, manufacturing, and automotive.
Report Scope of the Artificial Intelligence Market
|
Report Coverage |
Details |
|
Market Size by 2030 |
USD 1,597.1 Billion |
|
Growth Rate from 2022 to 2030 |
CAGR of 38.1% |
|
North America Makret Share in 2021 |
42% |
|
Software Segment Makret Share in 2021 |
39% |
|
Base Year |
2021 |
|
Forecast Period |
2022 to 2030 |
|
Segments Covered |
Type, Technology, Solution, End User, Business Function, Deployment Mode, Organization Size, System Type, Geography |
|
Companies Mentioned |
Intel Corporation, Microsoft, IBM, Google, Amazon Web Services, Baidu, Inc., NVIDIA Corporation, H2O.ai., Lifegraph, Sensely, Inc., Enlitic, Inc., AiCure, HyperVerge, Inc., Arm Limited |
ANN works in recognizing similar patterns and helps in providing modified solutions. Tech companies like Google Maps have been adopting the ANN to improve their route and work on the feedback received using the ANN. ANN is substituting conventional machine learning systems to evolve precise and accurate versions. For instance, recent advancements in computer vision technology, such as GAN (Generative Adversarial Networks) and SSD (Single Shot MultiBox Detector), have led to digital image processing techniques. For instance, images and videos were taken in low light, or low resolution can be transformed into HD quality by employing these techniques. The continuous research in computer vision has built the foundation for digital image processing in security and surveillance, healthcare, and transportation, among other sectors. Such emerging machine learning methods are anticipated to alter the manner AI versions are trained and deployed.
The WHO has declared the novel coronavirus (COVID-19) outbreak a pandemic, causing a massive impact on businesses and humankind. This pandemic has emerged as an opportunity for AI-enabled computer systems to fight against the epidemic as several tech giants and start-ups are working on preventing, mitigating, and containing the virus. For instance, the Chinese tech giant Alibaba's research institute Damo Academy has developed a diagnostic algorithm to detect new coronavirus cases with the chest CT (Computed Tomography) scan. The AI model used in the system has been trained with the sample data from over 5,000 positive coronavirus cases. For instance, in June 2020, Lunit developed an AI solution for x-ray analysis of the chest for simpler management of Covid-19 cases and offered assistance in interpreting, monitoring, and patient trials.
Technology Insights
Based on the technology, the deep learning was the leading segment that constituted a market share of around 38% in 2021. This dominance is attributable to its complex applications driven by the data such as audio, video, and text recognition. The rising technological advancements in the field of deep learning is expected to overcome the challenges associated with the high volumes of data. Furthermore, the rising adoption of the deep learning technology in the medical field is expected to further fuel the growth of the segment during the forecast period.
The huge share of the machine learning in the total investments in AI technology is fueling its adoption in various applications such as hypothesis generation, clustering, altering, tagging, clustering, filtering, visualization, and navigation promotes the development of the cognitive solutions. The rising deployment of the on-premises hardware and cloud computing platforms for handling and storing huge volumes of data has significantly contributed to the rise of the data analytics platforms. The rising investments by the top tech giants in the innovation and research are expected to fuel the growth of the AI market in the upcoming future.
Solution Insights
The software segment accounted for a revenue share of over 39% in 2021. The improvements in the data storage system, parallel processing, and improved computing power are the major drivers of the software segment in the AI market. The higher demand for the software technologies for the deployment and designing of AI applications such as linear algebra, video analytics, hardware communication capacity, inference, and sparse matrices is fueling the growth of the segment. The rising need for the enterprises to gain meaningful data and information through visual content analysis is expected to boost the demand for the software solutions in the global artificial intelligence market.
The hardware is estimated to be the fastest-growing segment during the forecast period. The artificial intelligence hardware includes various components such as CPU, GPU, ASIC and FPGA. The huge demand for the CPUs and GPUs owing to their high computing power has resulted in the dominance of the CPU and GPU in the hardware segment. The rising adoption of the AI technology across the different end use verticals is expected to boost the demand for the artificial intelligence hardware systems in the forthcoming years.
End User Insights
The global artificial intelligence market, based on the end user, was dominated by the advertising & media segment that accounted for over 21% of the market share in 2021. The rising adoption of AI in the marketing applications has fueled the growth of this segment. The increased investments by the various companies in the marketing and advertisement have led to the dominance of the marketing & media segment in the global AI market.
The healthcare segment is expected to overtake the advertising & media segment during the forecast period. The increased adoption of the AI in various applications such as virtual nursing assistants, robotic surgery, clinical trials, automated image diagnosis, and so on is significantly fostering the growth of this segment. Furthermore, the rising penetration of the telehealth platforms and rising adoption of the remote monitoring systems and electronic health records is expected to boost the growth of this segment during the forecast period.
Regional Insights
North America dominated the market and accounted for revenue share of over 42.0% in 2021. This high share is attributable to favorable government initiatives to encourage the adoption of AI across various industries. For instance, in February 2019, U.S. President Donald J. Trump launched the American AI Initiative as the nation’s strategy for promoting leadership in artificial intelligence. As part of this initiative, Federal agencies have fostered public trust in AI-based systems by establishing guidelines for its development and real-life implementation across different industrial sectors.
In Asia Pacific, the market is anticipated to witness significant CAGR over the forecast period. This growth owes to the significantly increasing investments in artificial intelligence. For instance, in April 2018, Baidu, Inc., a China-based tech giant, announced that it had entered into definitive agreements with investors concerning the divestiture of its financial services group (FSG), providing wealth management, consumer credit, and other business services. The investors are led by Carlyle Investment Management LLC and Tarrant Capital IP, LLC, with participation from ABC International, and Taikanglife, among others. Also, a growing number of AI start-ups in the region are boosting the adoption of AI to improve operational efficiency and enable process automation.
Some of the prominent players in the Artificial Intelligence (AI) Market include:
Segments Covered in the Report
This research report offers market revenue, sales volume, production assessment and prognoses by classifying it on the basis of various aspects. Further, this research study investigates market size, production, consumption and its development trends at global, regional, and country level for the period of 2017 to 2030 and covers subsequent region in its scope:
By Type
By Technology
By Solution
By End User
By Business Function
By Deployment Mode
By Organization Size
By System Type
By Geography
North America
Europe
Asia Pacific
Latin America
Middle East & Africa (MEA)
Key Points Covered in Artificial Intelligence (AI) Market Study:
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. Market Dynamics Analysis and Trends
5.1. Market Dynamics
5.1.1. Market Drivers
5.1.2. Market Restraints
5.1.3. Market Opportunities
5.2. Porter’s Five Forces Analysis
5.2.1. Bargaining power of suppliers
5.2.2. Bargaining power of buyers
5.2.3. Threat of substitute
5.2.4. Threat of new entrants
5.2.5. Degree of competition
Chapter 6. Competitive Landscape
6.1.1. Company Market Share/Positioning Analysis
6.1.2. Key Strategies Adopted by Players
6.1.3. Vendor Landscape
6.1.3.1. List of Suppliers
6.1.3.2. List of Buyers
Chapter 7. Global Artificial Intelligence Market, By Type
7.1. Artificial Intelligence Market, by Type, 2022-2030
7.1.1. Narrow/Weak AI
7.1.1.1. Market Revenue and Forecast (2017-2030)
7.1.2. General/Strong AI
7.1.2.1. Market Revenue and Forecast (2017-2030)
Chapter 8. Global Artificial Intelligence Market, By Technology
8.1. Artificial Intelligence Market, by Technology, 2022-2030
8.1.1. Machine Learning
8.1.1.1. Market Revenue and Forecast (2017-2030)
8.1.2. Natural Language Processing
8.1.2.1. Market Revenue and Forecast (2017-2030)
8.1.3. Context-Aware Computing
8.1.3.1. Market Revenue and Forecast (2017-2030)
8.1.4. Computer Vision
8.1.4.1. Market Revenue and Forecast (2017-2030)
Chapter 9. Global Artificial Intelligence Market, By Solution
9.1. Artificial Intelligence Market, by Solution, 2022-2030
9.1.1. Software
9.1.1.1. Market Revenue and Forecast (2017-2030)
9.1.2. Hardware
9.1.2.1. Market Revenue and Forecast (2017-2030)
9.1.3. Services
9.1.3.1. Market Revenue and Forecast (2017-2030)
Chapter 10. Global Artificial Intelligence Market, By Business Function
10.1. Artificial Intelligence Market, by Business Function, 2022-2030
10.1.1. Marketing and Sales
10.1.1.1. Market Revenue and Forecast (2017-2030)
10.1.2. Security
10.1.2.1. Market Revenue and Forecast (2017-2030)
10.1.3. Finance
10.1.3.1. Market Revenue and Forecast (2017-2030)
10.1.4. Human Resource
10.1.4.1. Market Revenue and Forecast (2017-2030)
10.1.5. Law
10.1.5.1. Market Revenue and Forecast (2017-2030)
10.1.6. Others
10.1.6.1. Market Revenue and Forecast (2017-2030)
Chapter 11. Global Artificial Intelligence Market, By End-use
11.1. Artificial Intelligence Market, by End-use, 2022-2030
11.1.1. BFSI
11.1.1.1. Market Revenue and Forecast (2017-2030)
11.1.2. Retail
11.1.2.1. Market Revenue and Forecast (2017-2030)
11.1.3. Law
11.1.3.1. Market Revenue and Forecast (2017-2030)
11.1.4. Healthcare
11.1.4.1. Market Revenue and Forecast (2017-2030)
11.1.5. Advertising & Media
11.1.5.1. Market Revenue and Forecast (2017-2030)
11.1.6. Manufacturing
11.1.6.1. Market Revenue and Forecast (2017-2030)
11.1.7. Automotive and Transportation
11.1.7.1. Market Revenue and Forecast (2017-2030)
11.1.8. Others
11.1.8.1. Market Revenue and Forecast (2017-2030)
Chapter 12. Global Artificial Intelligence Market, By Deployment Mode
12.1. Artificial Intelligence Market, by Deployment Mode, 2022-2030
12.1.1. Cloud
12.1.1.1. Market Revenue and Forecast (2017-2030)
12.1.2. On-premises
12.1.2.1. Market Revenue and Forecast (2017-2030)
Chapter 13. Global Artificial Intelligence Market, By Company Size
13.1. Artificial Intelligence Market, by Company Size, 2022-2030
13.1.1. Small
13.1.1.1. Market Revenue and Forecast (2017-2030)
13.1.2. Medium
13.1.2.1. Market Revenue and Forecast (2017-2030)
13.1.3. Large
13.1.3.1. Market Revenue and Forecast (2017-2030)
Chapter 14. Global Artificial Intelligence Market, Regional Estimates and Trend Forecast
14.1. North America
14.1.1. Market Revenue and Forecast, by Type (2017-2030)
14.1.2. Market Revenue and Forecast, by Technology (2017-2030)
14.1.3. Market Revenue and Forecast, by Solution (2017-2030)
14.1.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.1.5. Market Revenue and Forecast, by End-use (2017-2030)
14.1.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.1.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.1.8. U.S.
14.1.8.1. Market Revenue and Forecast, by Type (2017-2030)
14.1.8.2. Market Revenue and Forecast, by Technology (2017-2030)
14.1.8.3. Market Revenue and Forecast, by Solution (2017-2030)
14.1.8.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.1.8.5. Market Revenue and Forecast, by End-use (2017-2030)
14.1.8.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.1.8.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.1.9. Rest of North America
14.1.9.1. Market Revenue and Forecast, by Type (2017-2030)
14.1.9.2. Market Revenue and Forecast, by Technology (2017-2030)
14.1.9.3. Market Revenue and Forecast, by Solution (2017-2030)
14.1.9.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.1.9.5. Market Revenue and Forecast, by End-use (2017-2030)
14.1.9.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.1.9.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.2. Europe
14.2.1. Market Revenue and Forecast, by Type (2017-2030)
14.2.2. Market Revenue and Forecast, by Technology (2017-2030)
14.2.3. Market Revenue and Forecast, by Solution (2017-2030)
14.2.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.2.5. Market Revenue and Forecast, by End-use (2017-2030)
14.2.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.2.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.2.8. UK
14.2.8.1. Market Revenue and Forecast, by Type (2017-2030)
14.2.8.2. Market Revenue and Forecast, by Technology (2017-2030)
14.2.8.3. Market Revenue and Forecast, by Solution (2017-2030)
14.2.8.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.2.8.5. Market Revenue and Forecast, by End-use (2017-2030)
14.2.8.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.2.8.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.2.9. Germany
14.2.9.1. Market Revenue and Forecast, by Type (2017-2030)
14.2.9.2. Market Revenue and Forecast, by Technology (2017-2030)
14.2.9.3. Market Revenue and Forecast, by Solution (2017-2030)
14.2.9.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.2.9.5. Market Revenue and Forecast, by End-use (2017-2030)
14.2.9.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.2.9.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.2.10. France
14.2.10.1. Market Revenue and Forecast, by Type (2017-2030)
14.2.10.2. Market Revenue and Forecast, by Technology (2017-2030)
14.2.10.3. Market Revenue and Forecast, by Solution (2017-2030)
14.2.10.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.2.10.5. Market Revenue and Forecast, by End-use (2017-2030)
14.2.10.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.2.10.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.2.11. Rest of Europe
14.2.11.1. Market Revenue and Forecast, by Type (2017-2030)
14.2.11.2. Market Revenue and Forecast, by Technology (2017-2030)
14.2.11.3. Market Revenue and Forecast, by Solution (2017-2030)
14.2.11.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.2.11.5. Market Revenue and Forecast, by End-use (2017-2030)
14.2.11.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.2.11.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.3. APAC
14.3.1. Market Revenue and Forecast, by Type (2017-2030)
14.3.2. Market Revenue and Forecast, by Technology (2017-2030)
14.3.3. Market Revenue and Forecast, by Solution (2017-2030)
14.3.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.3.5. Market Revenue and Forecast, by End-use (2017-2030)
14.3.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.3.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.3.8. India
14.3.8.1. Market Revenue and Forecast, by Type (2017-2030)
14.3.8.2. Market Revenue and Forecast, by Technology (2017-2030)
14.3.8.3. Market Revenue and Forecast, by Solution (2017-2030)
14.3.8.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.3.8.5. Market Revenue and Forecast, by End-use (2017-2030)
14.3.8.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.3.8.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.3.9. China
14.3.9.1. Market Revenue and Forecast, by Type (2017-2030)
14.3.9.2. Market Revenue and Forecast, by Technology (2017-2030)
14.3.9.3. Market Revenue and Forecast, by Solution (2017-2030)
14.3.9.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.3.9.5. Market Revenue and Forecast, by End-use (2017-2030)
14.3.9.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.3.9.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.3.10. Japan
14.3.10.1. Market Revenue and Forecast, by Type (2017-2030)
14.3.10.2. Market Revenue and Forecast, by Technology (2017-2030)
14.3.10.3. Market Revenue and Forecast, by Solution (2017-2030)
14.3.10.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.3.10.5. Market Revenue and Forecast, by End-use (2017-2030)
14.3.10.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.3.10.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.3.11. Rest of APAC
14.3.11.1. Market Revenue and Forecast, by Type (2017-2030)
14.3.11.2. Market Revenue and Forecast, by Technology (2017-2030)
14.3.11.3. Market Revenue and Forecast, by Solution (2017-2030)
14.3.11.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.3.11.5. Market Revenue and Forecast, by End-use (2017-2030)
14.3.11.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.3.11.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.4. MEA
14.4.1. Market Revenue and Forecast, by Type (2017-2030)
14.4.2. Market Revenue and Forecast, by Technology (2017-2030)
14.4.3. Market Revenue and Forecast, by Solution (2017-2030)
14.4.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.4.5. Market Revenue and Forecast, by End-use (2017-2030)
14.4.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.4.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.4.8. GCC
14.4.8.1. Market Revenue and Forecast, by Type (2017-2030)
14.4.8.2. Market Revenue and Forecast, by Technology (2017-2030)
14.4.8.3. Market Revenue and Forecast, by Solution (2017-2030)
14.4.8.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.4.8.5. Market Revenue and Forecast, by End-use (2017-2030)
14.4.8.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.4.8.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.4.9. North Africa
14.4.9.1. Market Revenue and Forecast, by Type (2017-2030)
14.4.9.2. Market Revenue and Forecast, by Technology (2017-2030)
14.4.9.3. Market Revenue and Forecast, by Solution (2017-2030)
14.4.9.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.4.9.5. Market Revenue and Forecast, by End-use (2017-2030)
14.4.9.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.4.9.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.4.10. South Africa
14.4.10.1. Market Revenue and Forecast, by Type (2017-2030)
14.4.10.2. Market Revenue and Forecast, by Technology (2017-2030)
14.4.10.3. Market Revenue and Forecast, by Solution (2017-2030)
14.4.10.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.4.10.5. Market Revenue and Forecast, by End-use (2017-2030)
14.4.10.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.4.10.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.4.11. Rest of MEA
14.4.11.1. Market Revenue and Forecast, by Type (2017-2030)
14.4.11.2. Market Revenue and Forecast, by Technology (2017-2030)
14.4.11.3. Market Revenue and Forecast, by Solution (2017-2030)
14.4.11.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.4.11.5. Market Revenue and Forecast, by End-use (2017-2030)
14.4.11.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.4.11.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.5. Latin America
14.5.1. Market Revenue and Forecast, by Type (2017-2030)
14.5.2. Market Revenue and Forecast, by Technology (2017-2030)
14.5.3. Market Revenue and Forecast, by Solution (2017-2030)
14.5.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.5.5. Market Revenue and Forecast, by End-use (2017-2030)
14.5.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.5.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.5.8. Brazil
14.5.8.1. Market Revenue and Forecast, by Type (2017-2030)
14.5.8.2. Market Revenue and Forecast, by Technology (2017-2030)
14.5.8.3. Market Revenue and Forecast, by Solution (2017-2030)
14.5.8.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.5.8.5. Market Revenue and Forecast, by End-use (2017-2030)
14.5.8.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.5.8.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
14.5.9. Rest of LATAM
14.5.9.1. Market Revenue and Forecast, by Type (2017-2030)
14.5.9.2. Market Revenue and Forecast, by Technology (2017-2030)
14.5.9.3. Market Revenue and Forecast, by Solution (2017-2030)
14.5.9.4. Market Revenue and Forecast, by Business Function (2017-2030)
14.5.9.5. Market Revenue and Forecast, by End-use (2017-2030)
14.5.9.6. Market Revenue and Forecast, by Company Size (2017-2030)
14.5.9.7. Market Revenue and Forecast, by Deployment Mode (2017-2030)
Chapter 15. Company Profiles
15.1. Intel Corporation
15.1.1. Company Overview
15.1.2. Product Offerings
15.1.3. Financial Performance
15.1.4. Recent Initiatives
15.2. Microsoft
15.2.1. Company Overview
15.2.2. Product Offerings
15.2.3. Financial Performance
15.2.4. Recent Initiatives
15.3. IBM
15.3.1. Company Overview
15.3.2. Product Offerings
15.3.3. Financial Performance
15.3.4. Recent Initiatives
15.4. Google
15.4.1. Company Overview
15.4.2. Product Offerings
15.4.3. Financial Performance
15.4.4. Recent Initiatives
15.5. Amazon Web Services
15.5.1. Company Overview
15.5.2. Product Offerings
15.5.3. Financial Performance
15.5.4. Recent Initiatives
15.6. Baidu, Inc.
15.6.1. Company Overview
15.6.2. Product Offerings
15.6.3. Financial Performance
15.6.4. Recent Initiatives
15.7. NVIDIA Corporation
15.7.1. Company Overview
15.7.2. Product Offerings
15.7.3. Financial Performance
15.7.4. Recent Initiatives
15.8. H2O.ai.
15.8.1. Company Overview
15.8.2. Product Offerings
15.8.3. Financial Performance
15.8.4. Recent Initiatives
15.9. Lifegraph
15.9.1. Company Overview
15.9.2. Product Offerings
15.9.3. Financial Performance
15.9.4. Recent Initiatives
15.10. Sensely, Inc.
15.10.1. Company Overview
15.10.2. Product Offerings
15.10.3. Financial Performance
15.10.4. Recent Initiatives
15.11. Enlitic, Inc.
15.11.1. Company Overview
15.11.2. Product Offerings
15.11.3. Financial Performance
15.11.4. Recent Initiatives
15.12. AiCure
15.12.1. Company Overview
15.12.2. Product Offerings
15.12.3. Financial Performance
15.12.4. Recent Initiatives
15.13. HyperVerge, Inc.
15.13.1. Company Overview
15.13.2. Product Offerings
15.13.3. Financial Performance
15.13.4. Recent Initiatives
Chapter 16. Research Methodology
16.1. Primary Research
16.2. Secondary Research
16.3. Assumptions
Chapter 17. Appendix
17.1. About Us
17.2. Glossary of Terms
Cross-segment Market Size and Analysis for
Mentioned Segments
Additional Company Profiles (Upto 5 With No Cost)
Additional Countries (Apart From Mentioned Countries)
Country/Region-specific Report
Go To Market Strategy
Region Specific Market DynamicsRegion Level Market Share Import Export AnalysisProduction AnalysisOthers