Artificial Intelligence (Chipsets) Market by Technology (Machine learning, Natural Language Processing, Context Aware Computing, Computer Vision), Hardware (Processor, Memory, Network), End-User Industry, and region - Global Forecast to 2026
The artificial intelligence (chipsets) market size is expected to be valued at USD 7.6 billion in 2020 and likely to reach USD 57.8 billion by 2026, at a CAGR of 40.1% during the forecast period.
Major drivers for the market are increasingly large and complex datasets driving the need for AI, the adoption of AI for improving consumer services and reducing operational costs, the growing number of AI applications, the improving computing power, and growing adoption of deep learning and neural networks.
Artificial Intelligence (Chipsets) Market Forecast to 2026
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AI involves the study and synthesis of intelligent agents—in this case, a computer system. The system perceives its environment and takes action to maximize its chance of success. AI is being developed to create expert systems and improve human intelligence in machines. AI (chipsets) are dedicated chips designed to process a complex and extensive set of instructions, especially for machine/deep learning-based applications. These chipsets deliver high performance and improved efficiency compared to the conventional processors
Artificial Intelligence (chipsets) Market Dynamics:
Driver: Adoption of AI for improving consumer services and reducing operational cost
Customers continuously seek better services and products, and companies try to achieve a model that makes both these requirements attainable without much investment. AI is gaining momentum due to its agile structure, which offers high satisfaction and customer retention. AI systems offer faster response, a tailored approach, highly accurate information, and fewer redundancies—all key factors to enhance customer experience while interacting with an organization. Moreover, AI uses data from multiple resources as a knowledge hub, which ultimately results in accurate predictions about consumers’ needs. This can strongly lead to continued collaboration and increased revenue, generating highly significant results for both sides. Companies such as eBay, Inc. use an interactive Q&A system, which suggests gift ideas to shoppers from a wide range of offered products. Here, algorithms such as optimization algorithms and text classifications are used to develop these AI systems. Similarly, the VOD service provider giant, Netflix, Inc., uses a Deep Learning technique to recommend products to its consumers. This helps the company derive recommendations based on what the viewer has liked instead of what they have merely seen previously.
Restraint: Lack of skilled AI workforce
AI is a complex system, and for developing, managing, and successfully implementing AI systems, companies require a workforce with specific skill sets. For instance, people dealing with AI systems should know about technologies such as cognitive computing, ML & machine intelligence, deep learning, and image recognition. Also, integrating AI solutions in the existing systems is a difficult task requiring extensive data processing to replicate the behavior of a human brain. Even a minor error can fail the system or adversely affect the desired result. Furthermore, the absence of professional standards and certifications in AI/ML technologies is curbing the growth of AI. Additionally, AI service providers face challenges in deploying/servicing their solutions at their customer sites. This is because of a lack of technology awareness and the limitations of AI experts.
Opportunity: Bringing AI to edge devices
Presently, the deployment of AI solutions and products is mostly in computing systems, which have large computation power and are capable of handling big data sets. However, limited processing power, bandwidth, and memory deployment of these AI solutions and products, especially those based on machine/deep learning, is challenging in edge devices/embedded systems, such as connected cars, drones, and IoT devices. Many companies are presently into the development of hardware chipsets, which can be deployed in edge devices. The companies are mainly focusing on low power consumption with high computing power. Some of these products are Movidius’s (an Intel company) Myriad 2, Mobileye’s (an Intel Company) Eye Q4 & Eye Q5, and Nvidia’s Drive PX.
Challenge: Limited structured data
Data is one vital source to train and develop a complete and robust AI system. Earlier datasets mainly were structured and were also mostly entered manually. However, the growing digitization globally and technology trends like the Internet of Things (IoT) and Industry 4.0 has resulted in data from wearable devices, smart thermostats, connected cars, IP cameras, smart appliances, manufacturing machines, industrial equipment, and various other remotely connected devices. This data is largely unstructured in the form of text, voice, and images, among others. The lack of an orderly internal structure limits the developers to extract value. However, training a machine learning tools developer requires high-quality labeled data and skilled human trainers. Extracting and labeling unstructured data required lots of skilled workforce and time. Thus, structured data plays a major role in developing an efficient AI system. On the other hand, the company is now practicing developing insights from semi-structured data (a combination of structured and unstructured data), enabling information from grouping and hierarchies. However, analytics tools and solutions for semi-structured data are at the nascent stage.
Artificial Intelligence (chipsets) Market Segment Insights:
Based on hardware, the memory segment to hold the highest CAGR during the forecast period
Memory requirement has increased significantly in recent years; earlier graphics cards were considered to be of high performance with 4 GB of memory frame buffer and data rates of 6–7 Gbps. Today, these data rates have increased up to 12 Gbps. High-bandwidth memory is being developed and deployed for AI applications independent of its computing architecture. A few start-up companies are exploring high-bandwidth parallel file systems to increase throughput and efficiency. Companies such as Samsung Electronics (South Korea) and Micron (US) are the major providers of memory solutions for AI technologies.
Based on technology, the machine learning segment registered the largest share during the forecast timeframe
Machine learning is expected to account for the largest market share throughout the forecast period. This is attributed to the enormous availability of data, also called big data, and increasing the adoption of ML by enterprises and federal agencies to gain valuable insights. The common applications of machine learning include computational finance, predictive maintenance in manufacturing, fraud detection, e-mail spam filtering, text processing, network security threat detection, search recommendations, and video analysis. ML is being adopted by businesses dealing with large volumes of data, where the time previously dedicated to poring over charts and spreadsheets is now being used to seek intelligent ways to automate data analysis. Big companies such as Netflix (US) and Amazon.com, Inc. (US), and Google News have deployed ML to analyze and understand user activities and preferences to recommend movies, articles, etc., and sell products.
Based on function, the inference segment accounts for the largest size of the market during the forecast period
In terms of value, the market for inference function is expected to account for a larger share of the market by 2026. The inference is sensitive to latency, and the trained model needs to analyze and provide analysis in near real-time. The requirement of the infrastructure for model deployment to be able to accelerate the data at the fastest rate is expected to drive the market for inference.
Based on end-user industry, the healthcare segment to hold the highest market share
The AI (chipsets) market for healthcare is categorized into various applications, such as patient data & risk analysis, medical imaging & diagnostics, precision medicine, lifestyle management & monitoring, drug discovery, inpatient care & hospital management, virtual assistant, wearables, and research. Among these applications, the patient data & risk analysis segment accounted for the largest market share in 2021. The growing patient data owing to the increasing adoption of EMRs and various advantages, such as predictive analytics and risk management, offered by AI systems to healthcare providers and payers contribute to the growth of the patient data & risk analysis segment. The medical imaging & diagnostics segment is expected to grow at the highest CAGR during the forecast period. Factors such as the presence of a large volume of imaging data, advantages offered by AI systems to radiologists in diagnosis and treatment management, and the influx of a large number of start-ups in this segment fuel the growth of medical imaging & diagnostics.
Regional Insights:
The Europe region is projected to grow at a higher CAGR during the forecast period
The adoption of AI (chipsets) among various end-user industries, such as marketing, security, retail, healthcare, and fintech, and the presence of domestic AI software developers supplement the overall growth of the AI (chipsets) market in the UK.
Some major companies, such as ARRIA NLG (UK) and FinGenius (UK), providing AI technology in the finance sector in Europe, are developing AI-enabled products for solving complex financial queries in the BFSI sector. Several healthcare institutions in this region are using this technology to monitor, record, and display the medical status of their patients. This is accelerating the growth of the AI (chipsets) market for the healthcare and financial sectors in Europe. Increasing the application of ML in the field of law to scroll through thousands of contracts to draw valuable precise information in a time-restricted environment is fueling the growth of the region's AI (chipsets) market.
Artificial Intelligence (Chipsets) Market by Region
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In the automotive sector, European automakers are partnering with companies such as NVIDIA (US), Intel (US), and Mobileye (an Intel company, Israel) to accelerate the development of AI technology in vehicles. The market in Germany is expected to grow at the highest CAGR during the forecast period. Germany is home to major automobile manufacturers, such as Volkswagen, BMW, Audi, and Daimler. Hence, significant R&D investments are chiefly made in Germany, which is a hub of technological innovations for most OEMs. It is bolstering the market growth of semiautonomous and autonomous vehicles. The German government’s Industry 4.0 project to computerize the manufacturing industry to increase resource efficiency and industrial output would lead to the growth of AI (chipsets) in manufacturing.
The North America region held the significant share of the artificial intelligence (chipsets) market in 2020
The US is one of the leading countries in the world to adopt AI technology across multiple application areas. The presence of prominent AI technology providers, such as IBM (US), Google (US), Microsoft (US), NVIDIA (US), Intel (US), Facebook (US), MetaMind (US), Tute Genomics (US), and Amazon.com (US) is complementing the growth of the market in this region. The growing concern about the security of critical infrastructure and sensitive data has increased government intervention in recent years and resulted in the adoption of AI (chipsets) in security applications. High consumerization of personal care products—routine checkup medical tools and wearable devices, is increasing the growth of AI-enabled healthcare devices in North America, thereby driving the growth of the AI (chipsets) market.
Key Market Players:
Some of the Major players in the artificial intelligence (chipsets) market are NVIDIA Corporation (NVIDIA) (US), Intel Corporation (Intel) (US), Xilinx, Inc. (Xilinx) (US), Samsung Electronics Co., Ltd. (Samsung) (South Korea), and Micron Technology, Inc. (Micron) (US). These players have adopted various growth strategies such as contracts, joint ventures, partnerships & agreements, acquisitions, and new product launches to further expand their presence in the artificial intelligence (chipsets) market.
Intel (US)
Intel (US) enjoys a strong market presence and has defended the same effectively. The company has dominated the market for microprocessors for many years. The company’s dominant market position ensures a large addressable market. Intel’s market position also provides increased scale and related benefits. The established market position provides competitive advantages and allows the company to penetrate adjacent markets effectively. One of the competitive advantages of Intel is the combination of a network of manufacturing, assembly, and test facilities with the global architecture design teams. This network gives the company more direct control over processes, quality control, product cost, production timing, performance, power consumption, and manufacturing yield.
Intel Corporation has strengthened its artificial intelligence division by acquiring Mobileye, Saffron Technologies, Altera, and Nervana Systems. Intel aims to make AI technology readily available to all with open data exchanges and initiatives. To meet this goal, the Intel Nervana AI Academy program has increased the accessibility to data, tools, training, and intelligent machines for developers, academics, and startups.
NVIDIA (US)
NVIDIA (US) is one of the global leaders in the visual computing business. It has a well-established geographic footprint and mainly deals with major OEMs, and ODMs spread across the globe. NVIDIA has made a substantial investment in its R&D division. This has resulted in its strong organic growth and robust market positioning in terms of hardware product development in the AI (chipsets) market. It uses its existing business channels to reach customers easily as part of its business strategy. NVIDIA has more than 40 offices worldwide, generating a major revenue from geographies such as Taiwan, China, the US, and Europe. Its global presence and adoption of inorganic growth strategies helped the company earn a very high rating.
Samsung Electronics (Korea)
Samsung Electronics (Korea) has been a leader in the memory segment, with product offerings like dynamic random-access memory (DRAM), NAND flash solutions, and advanced solid-state drive (SSD) products. The DRAM solutions include components and modules for PC, server, and mobile applications. Samsung offers a broad portfolio of high-performance, high-density NAND flash solutions combined with its preceding controller technologies that encompass embedded and non-embedded memory storage solutions as well as solid-state drives that can be used as data storage for PC and enterprise systems. Samsung’s advanced SSD products offer the next-generation storage solution that overcomes the shortcomings of conventional hard disk drives and suggests attractive alternates for PC and server applications while improving the stability and performance of the systems in which they are used.
Xilinx (US)
Xilinx (US) is diversified in terms of its revenue generation as it caters to various markets in various regions. The company’s operations focus on diversified end markets, such as automotive, data centers, aerospace & defense, and consumer electronics, to name a few. Further, the company has a broad geographic presence and serves customers in Asia Pacific, North America, and Europe. Its diversified operations and revenue streams enable it to tap the opportunities in new and existing markets and shield it against demand fluctuations in a specific market or industry by dispersing its business risks. Xilinx is one of the largest FPGA suppliers in the world. The company has a strong focus on research and development and has been regularly expanding its FPGA product portfolio. The company also focuses on products with small form factor packages, which are critical for cost-sensitive markets.
Micron (US)
Micron (US), including its consolidated subsidiaries, is a leader in innovative memory and storage solutions. Its global brands include Micron, Crucial, and Ballistix. Its broad portfolio of high-performance memory and storage technologies is used in several disruptive trends, including artificial intelligence, machine learning, autonomous vehicles, and key market segments such as cloud, data center, networking, and mobile. All of Micron’s products are manufactured at wholly-owned or joint venture facilities, which have increased their manufacturing scale and product diversity. In addition, a strong increase in the company’s recent financials has elevated its position in the memory market.
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|
Report Metric |
Details |
| Market Size Value in 2020 | USD 7.6 billion |
| Revenue Forecast in 2026 | USD 57.8 billion |
| Growth Rate | 40.1% |
|
Market size available for years |
2017–2026 |
|
Base year |
2019 |
|
Forecast period |
2020–2026 |
|
Segments covered |
|
|
Geographic regions covered |
|
|
Companies covered |
|
| Key Market Driver | Adoption of AI for Consumer Service |
| Largest Growing Region | Asia Pacific |
| Largest Market Share Segment | Healthcare Segment |
| Highest CAGR Segment | Medical Imaging & Diagnostics Segment |
AI (chipsets) market segmentation:
In this report, the AI (chipsets) market has been segmented into the following categories:
Based on Hardware:
- Processor
- Memory
- Network
Based on Technology:
- Machine Learning
- Deep Learning
- Supervised Learning
- Reinforced Learning
- Unsupervised Learning
- Others
- Natural Language Processing
- Context-aware Computing
- Computer Vision
- Predictive Analysis
Based on Function:
- Training
- Inference
Based on the End-user Industry:
- Healthcare
- Manufacturing
- Automotive
- Agriculture
- Retail
- Cybersecurity
- Human Resources
- Marketing
- Law
- Fintech
- Government
Based on Region:
- North America
- Europe
- Asia Pacific
- Rest of the World (RoW)
Artificial Intelligence (Chipsets) Market Highlights:
What is new?
- Artificial intelligence (chipsets) market players are expected to focus on the wearable healthcare segment in the coming years
Wearable devices are useful for improved monitoring of real-time, long-term, and dynamic physiological and pathological processes. These are convenient for managing chronic illnesses like cardiovascular diseases, sleep disorders, and cognitive impairment. The adoption of health and wellness devices that track consumer fitness activities, sleeping habits, body temperature, and heart rate is growing. Such wearable devices help capture relevant patient health information and are convenient and user-friendly. The wearable technology allows physicians to monitor and track patient health remotely. Thus, the adoption of this technology in healthcare practices will reduce patient visits to hospitals.
- Coverage of new market players and change in the market share of existing artificial intelligence (chipsets) players
Company profiles: Company profiles give a glimpse of the key players in the market with respect to their business overviews, financials, product offerings, recent developments undertaken by them, and MnM view. In the new edition of the report, we have 25 players (10 major and 15 Other key companies).
- Updated financial information and product portfolios of players operating in the Artificial intelligence (chipsets) market
Newer and improved representation of financial information: The latest edition of the report provides updated financial information in the context of the artificial intelligence (chipsets) market till 2017/2020 for each listed company in the graphical representation in a single diagram (instead of multiple tables). This would help to quickly analyze the present status of profiled companies in terms of their financial strength, profitability, key revenue-generating region/country, business segment focus in terms of the highest revenue-generating segment, and investment in research and development activities.
- Updated market developments of the profiled players
Recent Developments: Updated market developments such as contracts, joint ventures, partnerships & agreements, acquisitions, new service launches, new product launches, investments, funding, and certification have been mapped for the years 2018 to 2020.
Recent Developments
- In September 2022, Nvidia Corp announced new flagship chips for video gamers that use artificial intelligence to enhance gaming graphics. The Lovelace chips have extended that technique to generate entire frames of a game using AI.
- In May 2022, Intel Corp launched a new chip called Gaudi2 focused on artificial intelligence computing, to compete against Nvidia. Gaudi2 is the second generation processor of Habana Labs, an Israeli start-up bought by Intel in 2019.
- In June 2021, Xilinx introduced the Versal AI Edge series, designed to enable AI innovation from the edge to the endpoint. With 4X the AI performance-per-watt versus GPUs1 and 10X greater compute density versus previous-generation adaptive SoCs, the Versal AI Edge series is the world’s most scalable and adaptable portfolio for next-generation distributed intelligent systems.
Frequently Asked Questions (FAQ):
What is the current size of the artificial intelligence (chipsets) market?
The artificial intelligence (chipsets) market is projected to grow from USD 7.6 billion in 2020 to USD 57.8 Billion by 2026, at a CAGR of 40.1% from 2020 to 2026.
Who are the winners in the artificial intelligence (chipsets) market?
NVIDIA Corporation (NVIDIA) (US), Intel Corporation (Intel) (US), Xilinx, Inc. (Xilinx) (US), Samsung Electronics Co., Ltd. (Samsung) (South Korea), and Micron Technology, Inc. (Micron) (US).
What are the opportunities for new market entrants?
The next-generation AI chips are the neuromorphic computing chips, which extend AI into areas that correspond to human cognition, such as interpretation and autonomous adaptation. Although, there are challenges associated with neuromorphic chip development, such as human's flexibility and the ability to learn from unstructured stimuli with the energy efficiency of the human brain but newer neural network models such as the spiking neural network (SNN) are being developed to emulate the natural neural network existing in the biological brain.
What are the drivers and opportunities for the artificial intelligence (chipsets) market?
Diverse applications across various industry verticals, such as agriculture, healthcare, BFSI, manufacturing, automobile, media, and advertising, drive the growth of this market. Increased productivity and improved customer satisfaction are other key factors driving this market. The availability of big data, coupled with AI algorithms for an extensive range of application areas, is fueling the growth of the AI market. Also, improving the computing efficiency of chipsets and reducing hardware costs are further supplementing the growth of the AI (chipsets) market.
What are the different types of artificial intelligence (chipsets) technologies available in the market?
The different types of technologies available in the market are machine learning, natural language processing, context-aware computing, computer vision, predictive analysis, and others.
To speak to our analyst for a discussion on the above findings, click Speak to Analyst
TABLE OF CONTENTS
1 INTRODUCTION (Page No. - 35)
1.1 OBJECTIVES OF THE STUDY
1.2 DEFINITION
1.3 STUDY SCOPE
1.3.1 MARKET COVERED
1.3.2 YEARS CONSIDERED FOR THE STUDY
1.4 CURRENCY
1.5 STAKEHOLDERS
2 RESEARCH METHODOLOGY (Page No. - 38)
2.1 RESEARCH DATA
FIGURE 1 RESEARCH DESIGN
2.1.1 SECONDARY AND PRIMARY RESEARCH
2.1.2 SECONDARY DATA
2.1.2.1 Major secondary sources
2.1.2.2 Secondary sources
2.1.3 PRIMARY DATA
2.1.3.1 Primary interviews with experts
2.1.3.2 Primary sources
2.1.3.3 Breakdown of primaries
2.1.3.4 Key industry insights
2.2 MARKET SIZE ESTIMATION
2.2.1 BOTTOM-UP APPROACH
2.2.1.1 Approach for capturing market share by bottom-up analysis (demand side)
FIGURE 2 BOTTOM-UP APPROACH
2.2.2 TOP-DOWN APPROACH
2.2.2.1 Approach for capturing market share by top-down analysis (supply side)
FIGURE 3 TOP-DOWN APPROACH
2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
FIGURE 4 DATA TRIANGULATION
2.4 ASSUMPTIONS
3 EXECUTIVE SUMMARY (Page No. - 48)
FIGURE 5 AI (CHIPSETS) MARKET, BY HARDWARE, 2020 VS. 2026 (USD MILLION)
FIGURE 6 AI (CHIPSETS) MARKET, BY PROCESSOR, 2020 VS. 2026 (USD MILLION)
FIGURE 7 AI (CHIPSETS) MARKET, BY TECHNOLOGY, 2017-2026 (USD MILLION)
FIGURE 8 AI (CHIPSETS) MARKET, BY END-USER INDUSTRY, 2020 VS. 2026 (%)
FIGURE 9 AI (CHIPSETS) MARKET, BY REGION, 2019
3.1 COVID-19 IMPACT ANALYSIS
FIGURE 10 PRE- AND POST-COVID-19 SCENARIO ANALYSIS FOR AI (CHIPSETS) MARKET
3.1.1 PRE-COVID-19 SCENARIO
3.1.2 POST-COVID-19 SCENARIO
4 PREMIUM INSIGHTS (Page No. - 54)
4.1 OVERVIEW OF THE AI (CHIPSETS) MARKET
FIGURE 11 IMPROVING COMPUTING EFFICIENCY OF AI CHIPSETS IS EXPECTED TO DRIVE THE MARKET BETWEEN 2020 AND 2026
4.2 AI (CHIPSETS) MARKET, BY HARDWARE
FIGURE 12 PROCESSOR TO HOLD THE LARGEST SHARE OF THE AI (CHIPSETS) MARKET DURING THE FORECAST PERIOD
4.3 MACHINE LEARNING AI (CHIPSETS) MARKET, BY SUBTYPE
FIGURE 13 AI (CHIPSETS) MARKET FOR SUPERVISED LEARNING TO HOLD THE LARGEST SIZE BETWEEN 2020 AND 2026
4.4 ASIA PACIFIC: AI (CHIPSETS) MARKET, BY END-USER INDUSTRY AND COUNTRY
FIGURE 14 CHINA EXPECTED TO HOLD THE LARGEST SHARE OF THE APAC AI (CHIPSETS) MARKET IN 2018
4.5 AI (CHIPSETS) MARKET, BY COUNTRY
FIGURE 15 US TO HOLD THE LARGEST SHARE OF THE AI (CHIPSETS) MARKET IN 2019
5 MARKET OVERVIEW (Page No. - 57)
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
FIGURE 16 GROWING NUMBER OF APPLICATIONS OF AI TECHNOLOGIES IN VARIOUS INDUSTRY VERTICALS ARE DRIVING MARKET GROWTH
5.2.1 DRIVERS
5.2.1.1 Increasingly large and complex dataset driving the need for AI
TABLE 1 AVERAGE NUMBER OF CONNECTED DEVICES PER CAPITA
FIGURE 17 IP TRAFFIC GROWTH PROJECTIONS UNTIL 2021
5.2.1.2 Adoption of AI for improving consumer services and reducing operational cost
5.2.1.3 Growing number of AI applications
5.2.1.4 Improving computing power
5.2.1.5 Growing adoption of deep learning and neural networks
5.2.2 RESTRAINTS
5.2.2.1 Lack of skilled AI workforce
5.2.3 OPPORTUNITIES
5.2.3.1 Increasing focus on developing human-aware AI systems
5.2.3.2 Bringing AI to edge devices
5.2.4 CHALLENGES
5.2.4.1 Low return on investment
TABLE 2 SOME PROMINENT INVESTMENTS IN THE AI MARKET IN THE PAST YEAR
5.2.4.2 Creating models and mechanisms for AI
5.2.4.3 Limited structured data
5.3 IMPACT OF COVID-19
5.4 ECOSYSTEM
FIGURE 18 ECOSYSTEM VIEW
5.5 PRICING ANALYSIS
TABLE 3 PRICE COMPARISON: AI CHIPSETS (LEADING COMPANIES)
5.6 TECHNOLOGY ANALYSIS
TABLE 4 COMPARISON OF AI CHIP TYPE
5.7 LIST OF EMERGING SME'S AND START-UPS OF AI (CHIPSETS) MARKET
5.8 CASE STUDIES
5.8.1 ACCELERATE ADOPTION OF AI IN DIAGNOSTIC RADIOLOGY
5.8.2 DETECTING GRAVITATIONAL WAVES MILLIONS OF LIGHT YEARS AWAY IN REAL-TIME
5.8.3 WIPRO’S PIPE SLEUTH WITH OPTIMIZED INFERENCE ON INTEL’S PROCESSORS ENABLES ANOMALY DETECTION
5.8.4 AI CATALYZES OPERATIONAL IMPROVEMENTS FOR MANUFACTURING AND SMART CITIES
5.8.5 INTEL’S DEEP LEARNING SOLUTIONS BRINGS TOUCH TO SOMATIC’S ROBOTS
6 ARTIFICIAL INTELLIGENCE (CHIPSETS) MARKET, BY HARDWARE (Page No. - 74)
6.1 INTRODUCTION
TABLE 5 AI (CHIPSETS) MARKET, BY HARDWARE, 2017–2019 (USD MILLION)
TABLE 6 AI (CHIPSETS) MARKET, BY HARDWARE, 2020–2026 (USD MILLION)
6.2 PROCESSOR
6.2.1 HIGH PARALLEL PROCESSING CAPABILITIES AND IMPROVED COMPUTING POWER HAVE RESULTED IN ADOPTION OF PROCESSORS
FIGURE 19 AI (CHIPSETS) PROCESSOR MARKET FOR GPU TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 7 AI (CHIPSETS) MARKET, BY PROCESSOR, 2017–2019 (USD MILLION)
TABLE 8 AI (CHIPSETS) MARKET, BY PROCESSOR, 2020–2026 (USD MILLION)
6.3 MEMORY
6.3.1 HIGH-BANDWIDTH MEMORY IS BEING DEVELOPED AND DEPLOYED FOR AI APPLICATIONS, INDEPENDENT OF ITS COMPUTING ARCHITECTURE
6.4 NETWORK
6.4.1 NVIDIA (US) AND INTEL (US) ARE KEY PROVIDERS OF NETWORK INTERCONNECT ADAPTERS FOR AI APPLICATIONS
7 ARTIFICIAL INTELLIGENCE (CHIPSETS) MARKET, BY TECHNOLOGY (Page No. - 79)
7.1 INTRODUCTION
TABLE 9 AI (CHIPSETS) MARKET, BY TECHNOLOGY, 2017–2019 (USD MILLION)
TABLE 10 AI (CHIPSETS) MARKET, BY TECHNOLOGY, 2020–2026 (USD MILLION)
7.2 MACHINE LEARNING
FIGURE 20 SUPERVISED LEARNING TO ACCOUNT FOR LARGEST SIZE OF AI (CHIPSETS) MARKET FOR MACHINE LEARNING THROUGHOUT FORECAST PERIOD
TABLE 11 AI (CHIPSETS) MARKET FOR MACHINE LEARNING, BY SUBTYPE, 2017–2019 (USD MILLION)
TABLE 12 AI (CHIPSETS) MARKET FOR MACHINE LEARNING, BY SUBTYPE, 2020–2026 (USD MILLION)
7.2.1 DEEP LEARNING
7.2.1.1 Deep learning uses artificial neural networks to learn multiple levels of data
7.2.2 SUPERVISED LEARNING
7.2.2.1 Classification and regression are major segments of supervised learning
7.2.3 UNSUPERVISED LEARNING
7.2.3.1 Unsupervised learning includes clustering methods consisting of algorithms with unlabeled training data
7.2.4 REINFORCEMENT LEARNING
7.2.4.1 Reinforcement learning allows systems and software to determine ideal behavior for maximizing the performance of systems
7.2.5 OTHERS
7.3 NATURAL LANGUAGE PROCESSING
7.3.1 NLP IS DEVELOPED FOR REAL-TIME TRANSLATION AND DEVELOPING SYSTEMS THAT CAN INTERACT THROUGH DIALOGUES
7.4 CONTEXT AWARE COMPUTING
7.4.1 DEVELOPMENT OF MORE SOPHISTICATED HARD AND SOFT SENSORS HAS ACCELERATED THE GROWTH OF CONTEXT AWARE COMPUTING
7.5 COMPUTER VISION
7.5.1 COMPUTER VISION ANALYZES INFORMATION OF DIFFERENT GEOMETRIC SHAPES, VOLUMES, AND PATTERN
7.6 PREDICTIVE ANALYSIS
7.6.1 PREDICTIVE ANALYSIS IS MAJORLY USED IN AGRICULTURE APPLICATIONS
8 ARTIFICIAL INTELLIGENCE (CHIPSETS) MARKET, BY FUNCTION (Page No. - 87)
8.1 INTRODUCTION
FIGURE 21 AI (CHIPSETS) MARKET FOR THE TRAINING FUNCTION IS PROJECTED TO GROW AT A HIGHER CAGR DURING FORECAST PERIOD
TABLE 13 AI (CHIPSETS) MARKET, BY FUNCTION, 2017–2019 (USD MILLION)
TABLE 14 AI (CHIPSETS) MARKET, BY FUNCTION, 2020–2026 (USD MILLION)
8.2 TRAINING
8.2.1 BUILDING A GOOD MODEL IS DIRECTLY RELATED TO THE QUALITY AND QUANTITY OF DATA USED IN THE PROCESS OF A LEARNING MODEL
8.3 INFERENCE
8.3.1 ON-PREMISES INFERENCE PLATFORM IS ADOPTED TO GAIN FASTER RESULTS THAN THAT OF CLOUD
9 ARTIFICIAL INTELLIGENCE (CHIPSETS) MARKET, BY END-USER INDUSTRY (Page No. - 90)
9.1 INTRODUCTION
FIGURE 22 AI (CHIPSETS) MARKET FOR MANUFACTURING TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 15 AI (CHIPSETS) MARKET, BY END-USER INDUSTRY, 2017–2019 (USD MILLION)
TABLE 16 AI (CHIPSETS) MARKET, BY END-USER INDUSTRY, 2020–2026 (USD MILLION)
9.2 HEALTHCARE
9.2.1 GROWING PATIENT DATA IS DRIVING THE ADOPTION AI IN HEALTHCARE
TABLE 17 AI (CHIPSETS) MARKET FOR HEALTHCARE, BY REGION, 2017–2019 (USD MILLION)
TABLE 18 AI (CHIPSETS) MARKET FOR HEALTHCARE, BY REGION, 2020–2026 (USD MILLION)
TABLE 19 NORTH AMERICA: AI (CHIPSETS) MARKET FOR HEALTHCARE, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 20 NORTH AMERICA: AI (CHIPSETS) MARKET FOR HEALTHCARE, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 21 EUROPE: AI (CHIPSETS) MARKET FOR HEALTHCARE, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 22 EUROPE: AI (CHIPSETS) MARKET FOR HEALTHCARE, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 23 APAC: AI (CHIPSETS) MARKET FOR HEALTHCARE, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 24 APAC: AI (CHIPSETS) MARKET FOR HEALTHCARE, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 25 ROW: AI (CHIPSETS) MARKET FOR HEALTHCARE, BY REGION, 2017–2019 (USD MILLION)
TABLE 26 ROW: AI (CHIPSETS) MARKET FOR HEALTHCARE, BY REGION, 2020–2026 (USD MILLION)
TABLE 27 AI (CHIPSETS) MARKET FOR HEALTHCARE, BY TECHNOLOGY, 2017–2019 (USD MILLION)
TABLE 28 AI (CHIPSETS) MARKET FOR HEALTHCARE, BY TECHNOLOGY, 2020–2026 (USD MILLION)
TABLE 29 MACHINE LEARNING IN HEALTHCARE AI (CHIPSETS) MARKET HEALTHCARE, BY SUBTYPE, 2017–2019 (USD MILLION)
TABLE 30 MACHINE LEARNING IN HEALTHCARE AI (CHIPSETS) MARKET HEALTHCARE, BY SUBTYPE, 2020–2026 (USD MILLION)
TABLE 31 AI (CHIPSETS) MARKET FOR HEALTHCARE, BY APPLICATION, 2017–2019 (USD MILLION)
TABLE 32 AI (CHIPSETS) MARKET FOR HEALTHCARE, BY APPLICATION, 2020–2026 (USD MILLION)
9.2.1.1 Patient data & risk analysis
9.2.1.2 Lifestyle management & monitoring
9.2.1.3 Precision medicine
9.2.1.4 Inpatient care & hospital management
9.2.1.5 Medical imaging & diagnostics
9.2.1.6 Drug discovery
9.2.1.7 Virtual assistant
9.2.1.8 Wearables
9.2.1.9 Research
9.2.1.10 Healthcare assistance robots
9.2.1.11 Emergency room & surgery
9.2.1.12 Mental health
9.2.1.13 Cybersecurity
9.3 MANUFACTURING
9.3.1 INDUSTRY 4.0 IS THE DRIVING FACTOR FOR AI ADOPTION IN MANUFACTURING
TABLE 33 AI (CHIPSETS) MARKET FOR MANUFACTURING, BY REGION, 2017–2019 (USD MILLION)
TABLE 34 AI (CHIPSETS) MARKET FOR MANUFACTURING, BY REGION, 2020–2026 (USD MILLION)
TABLE 35 NORTH AMERICA: AI (CHIPSETS) MARKET FOR MANUFACTURING, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 36 NORTH AMERICA: AI (CHIPSETS) MARKET FOR MANUFACTURING, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 37 EUROPE: AI (CHIPSETS) MARKET FOR MANUFACTURING, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 38 EUROPE: AI (CHIPSETS) MARKET FOR MANUFACTURING, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 39 APAC: AI (CHIPSETS) MARKET FOR MANUFACTURING, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 40 APAC: AI (CHIPSETS) MARKET FOR MANUFACTURING, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 41 ROW: AI (CHIPSETS) MARKET FOR MANUFACTURING, BY REGION, 2017–2019 (USD MILLION)
TABLE 42 ROW: AI (CHIPSETS) MARKET FOR MANUFACTURING, BY REGION, 2020–2026 (USD MILLION)
TABLE 43 AI (CHIPSETS) MARKET FOR MANUFACTURING, BY TECHNOLOGY, 2017–2019 (USD MILLION)
TABLE 44 AI (CHIPSETS) MARKET FOR MANUFACTURING, BY TECHNOLOGY, 2020–2026 (USD MILLION)
TABLE 45 MACHINE LEARNING IN MANUFACTURING AI (CHIPSETS) MARKET, BY SUBTYPE, 2017–2019 (USD MILLION)
TABLE 46 MACHINE LEARNING IN MANUFACTURING AI (CHIPSETS) MARKET, BY SUBTYPE, 2020–2026 (USD MILLION)
FIGURE 23 PREDICTIVE MAINTENANCE AND MACHINERY INSPECTION APPLICATION EXPECTED TO HOLD THE LARGEST SHARE OF THE AI (CHIPSETS) MARKET FOR MANUFACTURING DURING THE FORECAST PERIOD
TABLE 47 AI (CHIPSETS) MARKET FOR MANUFACTURING, BY APPLICATION, 2017–2019 (USD MILLION)
TABLE 48 AI (CHIPSETS) MARKET FOR MANUFACTURING, BY APPLICATION, 2020–2026 (USD MILLION)
9.3.1.1 Material movement
9.3.1.2 Predictive maintenance and machinery inspection
9.3.1.3 Production planning
9.3.1.4 Field services
9.3.1.5 Reclamation
9.3.1.6 Quality control
9.4 AUTOMOTIVE
9.4.1 AUTOMATED DRIVING USING AI IS THE TREND IN THIS INDUSTRY
FIGURE 24 NORTH AMERICA TO HOLD THE LARGEST SHARE OF THE AI (CHIPSETS) MARKET FOR AUTOMOTIVE DURING THE FORECAST PERIOD
TABLE 49 AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY REGION, 2017–2019 (USD MILLION)
TABLE 50 AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY REGION, 2020–2026 (USD MILLION)
TABLE 51 NORTH AMERICA: AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 52 NORTH AMERICA: AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 53 EUROPE: AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 54 EUROPE: AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 55 APAC: AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 56 APAC: AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 57 ROW: AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY REGION, 2017–2019 (USD MILLION)
TABLE 58 ROW: AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY REGION, 2020–2026 (USD MILLION)
TABLE 59 AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY TECHNOLOGY, 2017–2019 (USD MILLION)
TABLE 60 AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY TECHNOLOGY, 2020–2026 (USD MILLION)
TABLE 61 MACHINE LEARNING IN AUTOMOTIVE AI (CHIPSETS) MARKET, BY SUBTYPE, 2017–2019 (USD MILLION)
TABLE 62 MACHINE LEARNING IN AUTOMOTIVE AI (CHIPSETS) MARKET, BY SUBTYPE, 2020–2026 (USD MILLION)
TABLE 63 AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY APPLICATION, 2017–2019 (USD MILLION)
TABLE 64 AI (CHIPSETS) MARKET FOR AUTOMOTIVE, BY APPLICATION, 2020–2026 (USD MILLION)
9.4.1.1 Autonomous driving
9.4.1.2 Human–machine interface
9.4.1.3 Semi-autonomous driving
9.5 AGRICULTURE
9.5.1 ADOPTION OF AI TECHNOLOGIES SUCH AS ML AND COMPUTER VISION IS DRIVING THE MARKET
TABLE 65 AI (CHIPSETS) MARKET FOR AGRICULTURE, BY REGION, 2017–2019 (USD MILLION)
TABLE 66 AI (CHIPSETS) MARKET FOR AGRICULTURE, BY REGION, 2020–2026 (USD MILLION)
TABLE 67 NORTH AMERICA: AI (CHIPSETS) MARKET FOR AGRICULTURE, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 68 NORTH AMERICA: AI (CHIPSETS) MARKET FOR AGRICULTURE, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 69 EUROPE: AI (CHIPSETS) MARKET FOR AGRICULTURE, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 70 EUROPE: AI (CHIPSETS) MARKET FOR AGRICULTURE, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 71 APAC: AI (CHIPSETS) MARKET FOR AGRICULTURE, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 72 APAC: AI (CHIPSETS) MARKET FOR AGRICULTURE, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 73 ROW: AI (CHIPSETS) MARKET FOR AGRICULTURE, BY REGION, 2017–2019 (USD MILLION)
TABLE 74 ROW: AI (CHIPSETS) MARKET FOR AGRICULTURE, BY REGION, 2020–2026 (USD MILLION)
FIGURE 25 MACHINE LEARNING TECHNOLOGY TO DOMINATE THE AI (CHIPSETS) MARKET FOR AGRICULTURE DURING THE FORECAST PERIOD
TABLE 75 AI (CHIPSETS) MARKET FOR AGRICULTURE, BY TECHNOLOGY, 2017–2019 (USD MILLION)
TABLE 76 AI (CHIPSETS) MARKET FOR AGRICULTURE, BY TECHNOLOGY, 2020–2026 (USD MILLION)
TABLE 77 MACHINE LEARNING IN AGRICULTURE AI (CHIPSETS) MARKET, BY SUBTYPE, 2017–2019 (USD MILLION)
TABLE 78 MACHINE LEARNING IN AGRICULTURE AI (CHIPSETS) MARKET, BY SUBTYPE, 2020–2026 (USD MILLION)
TABLE 79 AI (CHIPSETS) MARKET FOR AGRICULTURE, BY APPLICATION, 2017–2019 (USD MILLION)
TABLE 80 AI (CHIPSETS) MARKET FOR AGRICULTURE, BY APPLICATION, 2020–2026 (USD MILLION)
9.5.1.1 Precision farming
9.5.1.2 Livestock monitoring
9.5.1.3 Drone analytics
9.5.1.4 Agricultural robots
9.5.1.5 Labor management
9.5.1.6 Others
9.6 RETAIL
9.6.1 ENHANCED CUSTOMER EXPERIENCE DUE TO AI IS DRIVING ITS ADOPTION IN RETAIL
TABLE 81 AI (CHIPSETS) MARKET FOR RETAIL, BY REGION, 2017–2019 (USD MILLION)
TABLE 82 AI (CHIPSETS) MARKET FOR RETAIL, BY REGION, 2020–2026 (USD MILLION)
TABLE 83 NORTH AMERICA: AI (CHIPSETS) MARKET FOR RETAIL, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 84 NORTH AMERICA: AI (CHIPSETS) MARKET FOR RETAIL, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 85 EUROPE: AI (CHIPSETS) MARKET FOR RETAIL, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 86 EUROPE: AI (CHIPSETS) MARKET FOR RETAIL, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 87 APAC: AI (CHIPSETS) MARKET FOR RETAIL, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 88 APAC: AI (CHIPSETS) MARKET FOR RETAIL, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 89 ROW: AI (CHIPSETS) MARKET FOR RETAIL, BY REGION, 2017–2019 (USD MILLION)
TABLE 90 ROW: AI (CHIPSETS) MARKET FOR RETAIL, BY REGION, 2020–2026 (USD MILLION)
TABLE 91 AI (CHIPSETS) MARKET FOR RETAIL, BY TECHNOLOGY, 2017–2019 (USD MILLION)
TABLE 92 AI (CHIPSETS) MARKET FOR RETAIL, BY TECHNOLOGY, 2020–2026 (USD MILLION)
TABLE 93 MACHINE LEARNING IN RETAIL AI (CHIPSETS) MARKET, BY SUBTYPE, 2017–2019 (USD MILLION)
TABLE 94 MACHINE LEARNING IN RETAIL AI (CHIPSETS) MARKET, BY SUBTYPE, 2020–2026 (USD MILLION)
FIGURE 26 RETAIL AI (CHIPSETS) MARKET FOR VISUAL SEARCH TO GROW AT THE HIGHEST CAGR FROM 2020 TO 2026
TABLE 95 AI (CHIPSETS) MARKET FOR RETAIL, BY APPLICATION, 2017–2019 (USD MILLION)
TABLE 96 AI (CHIPSETS) MARKET FOR RETAIL, BY APPLICATION, 2020–2026 (USD MILLION)
9.6.1.1 Product recommendation and planning
9.6.1.2 Customer relationship management
9.6.1.3 Visual search
9.6.1.4 Virtual assistant
9.6.1.5 Price optimization
9.6.1.6 Payment services management
9.6.1.7 Supply chain management and demand planning
9.6.1.8 Others
9.7 CYBERSECURITY
9.7.1 INCREASED NUMBER OF CYBERSECURITY THREATS IS LEADING TO THE ADOPTION OF AI IN THIS INDUSTRY
TABLE 97 AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY REGION, 2017–2019 (USD MILLION)
TABLE 98 AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY REGION, 2020–2026 (USD MILLION)
TABLE 99 NORTH AMERICA: AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 100 NORTH AMERICA: AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 101 EUROPE: AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 102 EUROPE: AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 103 APAC: AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 104 APAC: AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 105 ROW: AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY REGION, 2017–2019 (USD MILLION)
TABLE 106 ROW: AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY REGION, 2020–2026 (USD MILLION)
TABLE 107 AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY TECHNOLOGY, 2017–2019 (USD MILLION)
TABLE 108 AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY TECHNOLOGY, 2020–2026 (USD MILLION)
TABLE 109 MACHINE LEARNING IN CYBERSECURITY AI (CHIPSETS) MARKET, BY SUBTYPE, 2017–2019 (USD MILLION)
TABLE 110 MACHINE LEARNING IN CYBERSECURITY AI (CHIPSETS) MARKET, BY SUBTYPE, 2020–2026 (USD MILLION)
FIGURE 27 ANTIVIRUS/ANTIMALWARE TO HOLD THE LARGEST SHARE OF THE AI (CHIPSETS) MARKET FOR CYBERSECURITY IN 2020
TABLE 111 AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY APPLICATION, 2017–2019 (USD MILLION)
TABLE 112 AI (CHIPSETS) MARKET FOR CYBERSECURITY, BY APPLICATION, 2020–2026 (USD MILLION)
9.7.1.1 Identity and access management (IAM)
9.7.1.2 Risk and compliance management
9.7.1.3 Encryption
9.7.1.4 Data loss prevention
9.7.1.5 Unified threat management
9.7.1.6 Antivirus/antimalware
9.7.1.7 Intrusion detection/prevention systems
9.7.1.8 Others
9.8 HUMAN RESOURCES
9.8.1 AI ADOPTION IN HR IS RESHAPING HOW COMPANIES OPERATE
TABLE 113 AI (CHIPSETS) MARKET FOR HR, BY REGION, 2017–2019 (USD MILLION)
TABLE 114 AI (CHIPSETS) MARKET FOR HR, BY REGION, 2020–2026 (USD MILLION)
TABLE 115 NORTH AMERICA: AI (CHIPSETS) MARKET FOR HR, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 116 NORTH AMERICA: AI (CHIPSETS) MARKET FOR HR, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 117 EUROPE: AI (CHIPSETS) MARKET FOR HR, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 118 EUROPE: AI (CHIPSETS) MARKET FOR HR, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 119 APAC: AI (CHIPSETS) MARKET FOR HR, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 120 APAC: AI (CHIPSETS) MARKET FOR HR, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 121 ROW: AI (CHIPSETS) MARKET FOR HR, BY REGION, 2017–2019 (USD MILLION)
TABLE 122 ROW: AI (CHIPSETS) MARKET FOR HR, BY REGION, 2020–2026 (USD MILLION)
TABLE 123 AI (CHIPSETS) MARKET FOR HR, BY TECHNOLOGY, 2017–2019 (USD MILLION)
TABLE 124 AI (CHIPSETS) MARKET FOR HR, BY TECHNOLOGY, 2020–2026 (USD MILLION)
TABLE 125 MACHINE LEARNING IN HR AI (CHIPSETS) MARKET, BY SUBTYPE, 2017–2019 (USD MILLION)
TABLE 126 MACHINE LEARNING IN HR AI (CHIPSETS) MARKET, BY SUBTYPE, 2020–2026 (USD MILLION)
FIGURE 28 APPLICANT TRACKING & ASSESSMENT TO GROW AT THE HIGHEST CAGR IN THE AI (CHIPSETS) MARKET FOR HR THROUGHOUT THE FORECAST PERIOD
TABLE 127 AI (CHIPSETS) MARKET FOR HR, BY APPLICATION, 2017–2019 (USD MILLION)
TABLE 128 AI (CHIPSETS) MARKET FOR HR, BY APPLICATION, 2020–2026 (USD MILLION)
9.8.1.1 Virtual assistant
9.8.1.2 Sentiment analysis
9.8.1.3 Scheduling group meetings and interviews
9.8.1.4 Personalized learning and development
9.8.1.5 Applicant tracking & assessment
9.8.1.6 Employee engagement
9.8.1.7 Resume analysis
9.9 MARKETING
9.9.1 AI HAS MAJOR APPLICATIONS IN MARKETING
TABLE 129 AI (CHIPSETS) MARKET FOR MARKETING, BY REGION, 2017–2019 (USD MILLION)
TABLE 130 AI (CHIPSETS) MARKET FOR MARKETING, BY REGION, 2020–2026 (USD MILLION)
TABLE 131 NORTH AMERICA: AI (CHIPSETS) MARKET FOR MARKETING, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 132 NORTH AMERICA: AI (CHIPSETS) MARKET FOR MARKETING, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 133 EUROPE: AI (CHIPSETS) MARKET FOR MARKETING, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 134 EUROPE: AI (CHIPSETS) MARKET FOR MARKETING, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 135 APAC: AI (CHIPSETS) MARKET FOR MARKETING, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 136 APAC: AI (CHIPSETS) MARKET FOR MARKETING, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 137 ROW: AI (CHIPSETS) MARKET FOR MARKETING, BY REGION, 2017–2019 (USD MILLION)
TABLE 138 ROW: AI (CHIPSETS) MARKET FOR MARKETING, BY REGION, 2020–2026 (USD MILLION)
TABLE 139 AI (CHIPSETS) MARKET FOR MARKETING, BY TECHNOLOGY, 2017–2019 (USD MILLION)
TABLE 140 AI (CHIPSETS) MARKET FOR MARKETING, BY TECHNOLOGY, 2020–2026 (USD MILLION)
TABLE 141 MACHINE LEARNING IN MARKETING AI (CHIPSETS) MARKET, BY SUBTYPE, 2017–2019 (USD MILLION)
TABLE 142 MACHINE LEARNING IN MARKETING AI (CHIPSETS) MARKET, BY SUBTYPE, 2020–2026 (USD MILLION)
FIGURE 29 AI (CHIPSETS) MARKET FOR VIRTUAL ASSISTANT TO GROW AT THE HIGHEST CAGR BETWEEN 2020 AND 2026
TABLE 143 AI (CHIPSETS) MARKET FOR MARKETING, BY APPLICATION, 2017–2019 (USD MILLION)
TABLE 144 AI (CHIPSETS) MARKET FOR MARKETING, BY APPLICATION, 2020–2026 (USD MILLION)
9.9.1.1 Social media advertising
9.9.1.2 Search advertising
9.9.1.3 Dynamic pricing
9.9.1.4 Virtual assistant
9.9.1.5 Content curation
9.9.1.6 Sales & marketing automation
9.9.1.7 Analytics platform
9.9.1.8 Others
9.10 LAW
9.10.1 AI IS BEING USED IN LAW TO INCREASE PRODUCTIVITY AND MARGINS
TABLE 145 AI (CHIPSETS) MARKET FOR LAW, BY REGION, 2017–2019 (USD MILLION)
TABLE 146 AI (CHIPSETS) MARKET FOR LAW, BY REGION, 2020–2026 (USD MILLION)
TABLE 147 NORTH AMERICA: AI (CHIPSETS) MARKET FOR LAW, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 148 NORTH AMERICA: AI (CHIPSETS) MARKET FOR LAW, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 149 EUROPE: AI (CHIPSETS) MARKET FOR LAW, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 150 EUROPE: AI (CHIPSETS) MARKET FOR LAW, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 151 APAC: AI (CHIPSETS) MARKET FOR LAW, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 152 APAC: AI (CHIPSETS) MARKET FOR LAW, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 153 ROW: AI (CHIPSETS) MARKET FOR LAW, BY REGION, 2017–2019 (USD MILLION)
TABLE 154 ROW: AI (CHIPSETS) MARKET FOR LAW, BY REGION, 2020–2026 (USD MILLION)
TABLE 155 AI (CHIPSETS) MARKET FOR LAW, BY TECHNOLOGY, 2017–2019 (USD MILLION)
TABLE 156 AI (CHIPSETS) MARKET FOR LAW, BY TECHNOLOGY, 2020–2026 (USD MILLION)
TABLE 157 MACHINE LEARNING IN LAW AI (CHIPSETS) MARKET, BY SUBTYPE, 2017–2019 (USD MILLION)
TABLE 158 MACHINE LEARNING IN LAW AI (CHIPSETS) MARKET, BY SUBTYPE, 2020–2026 (USD MILLION)
FIGURE 30 LEGAL RESEARCH TO HOLD THE LARGEST MARKET SHARE IN 2020
TABLE 159 AI (CHIPSETS) MARKET FOR LAW, BY APPLICATION, 2017–2019 (USD MILLION)
TABLE 160 AI (CHIPSETS) MARKET FOR LAW, BY APPLICATION, 2020–2026 (USD MILLION)
9.10.1.1 Ediscovery
9.10.1.2 Legal research
9.10.1.3 Contract analysis
9.10.1.4 Case prediction
9.10.1.5 Compliance
9.10.1.6 Others
9.11 FINTECH
9.11.1 AI IS USED IN FINTECH COMPANIES TO DESIGN INVESTMENT STRATEGIES
TABLE 161 AI (CHIPSETS) MARKET FOR FINTECH, BY REGION, 2017–2019 (USD MILLION)
TABLE 162 AI (CHIPSETS) MARKET FOR FINTECH, BY REGION, 2020–2026 (USD MILLION)
TABLE 163 NORTH AMERICA: AI (CHIPSETS) MARKET FOR FINTECH, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 164 NORTH AMERICA: AI (CHIPSETS) MARKET FOR FINTECH, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 165 EUROPE: AI (CHIPSETS) MARKET FOR FINTECH, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 166 EUROPE: AI (CHIPSETS) MARKET FOR FINTECH, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 167 APAC: AI (CHIPSETS) MARKET FOR FINTECH, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 168 APAC: AI (CHIPSETS) MARKET FOR FINTECH, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 169 ROW: AI (CHIPSETS) MARKET FOR FINTECH, BY REGION, 2017–2019 (USD MILLION)
TABLE 170 ROW: AI (CHIPSETS) MARKET FOR FINTECH, BY REGION, 2020–2026 (USD MILLION)
TABLE 171 AI (CHIPSETS) MARKET FOR FINTECH, BY TECHNOLOGY, 2017–2019 (USD MILLION)
TABLE 172 AI (CHIPSETS) MARKET FOR FINTECH, BY TECHNOLOGY, 2020–2026 (USD MILLION)
TABLE 173 MACHINE LEARNING IN FINTECH AI (CHIPSETS) MARKET, BY SUBTYPE, 2017–2019 (USD MILLION)
TABLE 174 MACHINE LEARNING IN FINTECH AI (CHIPSETS) MARKET, BY SUBTYPE, 2020–2026 (USD MILLION)
FIGURE 31 VIRTUAL ASSISTANT PROJECTED TO WITNESS THE FASTEST GROWTH BETWEEN 2020 AND 2026
TABLE 175 AI (CHIPSETS) MARKET FOR FINTECH, BY APPLICATION, 2017–2019 (USD MILLION)
TABLE 176 AI (CHIPSETS) MARKET FOR FINTECH, BY APPLICATION, 2020–2026 (USD MILLION)
9.11.1.1 Virtual assistant
9.11.1.2 Business analytics and reporting
9.11.1.3 Customer behavior analytics
9.11.1.4 Others
9.12 GOVERNMENT
9.12.1 GOVERNMENT BODIES ARE ADOPTING AI TO TACKLE CYBERTERRORISM
TABLE 177 AI (CHIPSETS) MARKET FOR GOVERNMENT, BY REGION, 2017–2019 (USD MILLION)
TABLE 178 AI (CHIPSETS) MARKET FOR GOVERNMENT, BY REGION, 2020–2026 (USD MILLION)
TABLE 179 NORTH AMERICA: AI (CHIPSETS) MARKET FOR GOVERNMENT, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 180 NORTH AMERICA: AI (CHIPSETS) MARKET FOR GOVERNMENT, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 181 EUROPE: AI (CHIPSETS) MARKET FOR GOVERNMENT, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 182 EUROPE: AI (CHIPSETS) MARKET FOR GOVERNMENT, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 183 APAC: AI (CHIPSETS) MARKET FOR GOVERNMENT, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 184 APAC: AI (CHIPSETS) MARKET FOR GOVERNMENT, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 185 ROW: AI (CHIPSETS) MARKET FOR GOVERNMENT, BY REGION, 2017–2019 (USD MILLION)
TABLE 186 ROW: AI (CHIPSETS) MARKET FOR GOVERNMENT, BY REGION, 2020–2026 (USD MILLION)
TABLE 187 AI (CHIPSETS) MARKET FOR GOVERNMENT, BY TECHNOLOGY, 2017–2019 (USD MILLION)
TABLE 188 AI (CHIPSETS) MARKET FOR GOVERNMENT, BY TECHNOLOGY, 2020–2026 (USD MILLION)
TABLE 189 MACHINE LEARNING IN GOVERNMENT AI (CHIPSETS) MARKET, BY SUBTYPE, 2017–2019 (USD MILLION)
TABLE 190 MACHINE LEARNING IN GOVERNMENT AI (CHIPSETS) MARKET, BY SUBTYPE, 2020–2026 (USD MILLION)
10 ARTIFICIAL INTELLIGENCE (CHIPSETS) MARKET, BY REGION (Page No. - 181)
10.1 INTRODUCTION
FIGURE 32 RAPIDLY GROWING MARKETS SUCH AS CHINA, JAPAN, GERMANY, AND INDIA EMERGING AS NEW HOTSPOTS IN AI (CHIPSETS) MARKET
FIGURE 33 AI (CHIPSETS) MARKET IN APAC TO GROW AT HIGHEST CAGR FROM 2020 TO 2026
TABLE 191 AI (CHIPSETS) MARKET, BY REGION, 2017–2019 (USD MILLION)
TABLE 192 AI (CHIPSETS) MARKET, BY REGION, 2020–2026 (USD MILLION)
10.2 NORTH AMERICA
FIGURE 34 MARKET SNAPSHOT: NORTH AMERICA
TABLE 193 AI (CHIPSETS) MARKET IN NORTH AMERICA, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 194 AI (CHIPSETS) MARKET IN NORTH AMERICA, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 195 AI (CHIPSETS) MARKET IN NORTH AMERICA, BY END-USER INDUSTRY, 2017–2019 (USD MILLION)
TABLE 196 AI (CHIPSETS) MARKET IN NORTH AMERICA, BY END-USER INDUSTRY, 2020–2026 (USD MILLION)
10.2.1 US
10.2.1.1 US is among the frontrunners in terms of adoption of AI in various end-user industries
10.2.2 CANADA
10.2.2.1 Government funding and extensive startup activities, especially in AI, are supporting the growth of AI in the region
10.2.3 MEXICO
10.2.3.1 Increase in productivity and reduction in cost are leading to the adoption of AI in various end-use industries in Mexico
10.3 EUROPE
FIGURE 35 MARKET SNAPSHOT: EUROPE
TABLE 197 AI (CHIPSETS) MARKET IN EUROPE, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 198 AI (CHIPSETS) MARKET IN EUROPE, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 199 AI (CHIPSETS) MARKET IN EUROPE, BY END-USER INDUSTRY, 2017–2019 (USD MILLION)
TABLE 200 AI (CHIPSETS) MARKET IN EUROPE, BY END-USER INDUSTRY, 2020–2026 (USD MILLION)
10.3.1 UK
10.3.1.1 Increasing demand in healthcare is driving the market for AI chipsets in the UK
10.3.2 GERMANY
10.3.2.1 Implementation of big data in manufacturing plants has resulted in the adoption of AI-based solutions in Germany
10.3.3 FRANCE
10.3.3.1 Increased funding and rising AI startups are expected to proliferate AI in France
10.3.4 ITALY
10.3.4.1 Cybersecurity threats are driving the adoption of AI
10.3.5 SPAIN
10.3.5.1 Cybersecurity is among emerging trends of AI in Spain
10.3.6 REST OF EUROPE
10.4 APAC
FIGURE 36 MARKET SNAPSHOT: ASIA PACIFIC
TABLE 201 AI (CHIPSETS) MARKET IN APAC, BY COUNTRY, 2017–2019 (USD MILLION)
TABLE 202 AI (CHIPSETS) MARKET IN APAC, BY COUNTRY, 2020–2026 (USD MILLION)
TABLE 203 AI (CHIPSETS) MARKET IN APAC, BY END-USER INDUSTRY, 2017–2019 (USD MILLION)
TABLE 204 AI (CHIPSETS) MARKET IN APAC, BY END-USER INDUSTRY, 2020–2026 (USD MILLION)
10.4.1 CHINA
10.4.1.1 The manufacturing sector in China is growing rapidly, resulting in the introduction of new robotics and big data technologies
10.4.2 JAPAN
10.4.2.1 Federal initiatives and presence of world-leading manufacturing companies are expected to boost the market in Japan
10.4.3 SOUTH KOREA
10.4.3.1 Increased spending on AI infrastructure is driving the market in South Korea
10.4.4 INDIA
10.4.4.1 India is one of the promising regions for AI-based start-ups
10.4.5 REST OF APAC
10.5 REST OF THE WORLD
FIGURE 37 MARKET SNAPSHOT: REST OF THE WORLD
TABLE 205 AI (CHIPSETS) MARKET IN ROW, BY REGION, 2017–2019 (USD MILLION)
TABLE 206 AI (CHIPSETS) MARKET IN ROW, BY REGION, 2020–2026 (USD MILLION)
TABLE 207 AI (CHIPSETS) MARKET IN ROW, BY END-USER INDUSTRY, 2017–2019 (USD MILLION)
TABLE 208 AI (CHIPSETS) MARKET IN ROW, BY END-USER INDUSTRY, 2020–2026 (USD MILLION)
10.5.1 MIDDLE EAST AND AFRICA
10.5.1.1 Increased investment in information and communication technologies is driving the market in MEA
10.5.2 SOUTH AMERICA
10.5.2.1 South America invests heavily in IT services
11 COMPETITIVE LANDSCAPE (Page No. - 207)
11.1 OVERVIEW
FIGURE 38 COMPANIES ADOPTED NEW PRODUCT DEVELOPMENTS AS THE KEY GROWTH STRATEGY BETWEEN 2017 AND 2020
11.2 MARKET RANKING ANALYSIS: AI (CHIPSETS) MARKET
TABLE 209 RANKING OF THE KEY COMPANIES IN THE AI (CHIPSETS) MARKET, 2019
11.3 MARKET SHARE ANALYSIS
TABLE 210 AI (CHIPSETS) MARKET SHARE ANALYSIS, 2019
11.4 COMPETITIVE LEADERSHIP MAPPING
11.4.1 VISIONARY LEADERS
11.4.2 DYNAMIC DIFFERENTIATORS
11.4.3 INNOVATORS
11.4.4 EMERGING COMPANIES
FIGURE 39 AI (CHIPSETS) MARKET (GLOBAL) COMPETITIVE LEADERSHIP MAPPING, 2019
11.5 COMPETITIVE SITUATION AND TRENDS
FIGURE 40 BATTLE FOR MARKET SHARE: NEW PRODUCT DEVELOPMENTS WERE A KEY STRATEGY BETWEEN 2017 AND 2020
11.5.1 NEW PRODUCT DEVELOPMENTS AND LAUNCHES
TABLE 211 NEW PRODUCT LAUNCHES AND DEVELOPMENTS, 2017–2020
11.5.2 COLLABORATIONS AND PARTNERSHIPS
TABLE 212 COLLABORATIONS AND PARTNERSHIPS, 2017–2020
11.5.3 ACQUISITIONS
TABLE 213 ACQUISITIONS, 2017–2020
12 COMPANY PROFILES (Page No. - 223)
12.1 KEY PLAYERS
(Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View)*
12.1.1 NVIDIA
FIGURE 41 NVIDIA: COMPANY SNAPSHOT
12.1.2 INTEL
FIGURE 42 INTEL: COMPANY SNAPSHOT
12.1.3 XILINX
FIGURE 43 XILINX: COMPANY SNAPSHOT
12.1.4 SAMSUNG
FIGURE 44 SAMSUNG: COMPANY SNAPSHOT
12.1.5 MICRON
FIGURE 45 MICRON: COMPANY SNAPSHOT
12.1.6 QUALCOMM TECHNOLOGIES
FIGURE 46 QUALCOMM TECHNOLOGIES: COMPANY SNAPSHOT
12.1.7 IBM
FIGURE 47 IBM CORPORATION: COMPANY SNAPSHOT
12.1.8 GOOGLE
FIGURE 48 GOOGLE: COMPANY SNAPSHOT
12.1.9 MICROSOFT
FIGURE 49 MICROSOFT: COMPANY SNAPSHOT
12.1.10 AMAZON WEB SERVICES (AWS)
FIGURE 50 AWS: COMPANY SNAPSHOT
* Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View might not be captured in case of unlisted companies.
12.2 OTHER COMPANIES
12.2.1 AMD
12.2.2 GENERAL VISION
12.2.3 GRAPHCORE
12.2.4 MEDIATEK
12.2.5 HUAWEI TECHNOLOGIES
12.2.6 FUJITSU
12.2.7 WAVE COMPUTING
12.2.8 MYTHIC
12.2.9 ZERO ASIC
12.2.10 KONIKU
12.2.11 TENSTORRENT
12.2.12 SAMBANOVA
12.2.13 KALRAY
12.2.14 XMOS
12.2.15 GREENWAVES TECHNOLOGIES
13 APPENDIX (Page No. - 279)
13.1 INSIGHTS FROM INDUSTRY EXPERTS
13.2 DISCUSSION GUIDE
13.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
13.4 AVAILABLE CUSTOMIZATIONS
13.5 RELATED REPORTS
13.6 AUTHOR DETAILS
The study involved the estimation of the current size of the Artificial Intelligence (AI) (chipsets) market. Exhaustive secondary research was conducted to collect information on the market, its peer markets, and its parent market. This was followed by the validation of these findings, assumptions, and sizing with the industry experts identified across the value chain through primary research. Both top-down and bottom-up approaches were employed to estimate the overall size of the market. It was followed by the market breakdown and data triangulation procedures, which were used to estimate the size of the market based on different segments and subsegments.
Secondary Research
In the secondary research process, various secondary sources were referred to for the identification and collection of relevant information for this study on AI (chipsets) market. Secondary sources included annual reports, press releases, and investor presentations of companies; white papers; journals and certified publications; and articles by recognized authors, websites, directories, and databases. Secondary research was conducted to obtain the key information regarding the supply chain and value chain of the industry, total pool of key players, market segmentation according to industry trends (to the bottom-most level), geographic markets, and key developments from the market- and technology-oriented perspectives. Secondary data was collected and analyzed to arrive at the overall size of the AI (chipsets) market and from executives of various key companies and organizations operating in the market.
Primary Research
Extensive primary research was conducted after understanding and analyzing the AI (chipsets) market through secondary research. Several primary interviews (with a key focus on COVID-19 impact) )were conducted with key opinion leaders from both demand- and supply-side vendors across four major regions—North America, Europe, APAC, and RoW. RoW comprises the Middle East & Africa and South America. Approximately 25% of the primary interviews were conducted with the demand side and 75% with the supply side.
Primary data has been collected through questionnaires, emails, and telephonic interviews. In the canvassing of primaries, various departments within organizations, such as sales, operations, and administration, were covered to provide a holistic viewpoint in our report.
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
Top-down and bottom-up approaches were implemented to estimate and validate the total size of the AI (chipsets) market.
Bottom-up approach
The bottom-up approach has been employed to arrive at the overall size of the AI (chipsets) market from the revenue of key players and their share in this market. The overall market size was calculated based on the revenue of key players identified for this market.
- Identifying various end-user industries using or expected to implement AI technology
- Analyzing each end-user industry and applications, along with major related companies and AI chipset manufacturers, and identifying service providers for the implementation of AI
- Estimating the AI (chipset) market for end-users
- Understanding the demand generated by companies operating across different end-use applications
- Tracking the ongoing and upcoming implementation of projects based on AI by end-user industries and forecasting the market based on these developments and other critical parameters
- Carrying out multiple discussions with key opinion leaders to understand the type of AI technology-based products and services, and software designed and developed by end-user industries. This information would help analyze the breakdown of the scope of work carried out by each major company in the AI (chipsets) market and also assess the COVID-19 impact on the market
- Arriving at the market estimates by analyzing AI chipset companies as per their countries, and subsequently combining this information to arrive at the market estimates by region
- Verifying and cross-checking the estimates at every level through discussions with key opinion leaders, including CXOs, directors, and operations managers, and finally with domain experts at MarketsandMarkets
- Studying various paid and unpaid sources of information, such as annual reports, press releases, white papers, and databases
Global AI (chipsets) Market Bottom-up Approach
Top-down Approach
In the top-down approach, the overall market size has been used to estimate the size of the individual markets (mentioned in the market segmentation) through percentage splits from secondary and primary research.
- Focusing on top-line investments and expenditures being made in the ecosystems of various end-user industries. Additionally, listing key developments, analyzing updated technology and software in the marketplace, as well as evaluating the market by further splitting it into various AI technologies
- Building and developing the information related to the market revenue generated by key AI chipset manufacturers
- Conducting multiple on-field discussions with key opinion leaders involved in the development of AI chipsets and products in various end-user industries
- Estimating geographic splits using secondary sources based on various factors, such as the number of players in a specific country and region, the type of AI chipsets, and the level of services offered in end-user industries
- Impact of COVID-19 on the steps mentioned above has also been considered
Data Triangulation
After arriving at the overall market size from the market size estimation process explained earlier, the total market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics for all the segments and subsegments, the data triangulation and market breakdown procedures have been employed, wherever applicable. The data has been triangulated by studying various factors and trends from both the demand and supply sides. Along with this, the AI (chipsets) market has been validated using both top-down and bottom-up approaches.
Report Objectives
- To define, describe, and forecast the artificial intelligence (chipsets) market, in terms of value, segmented based on technology, hardware, function, end-user industry, and geography
- To provide detailed information regarding the major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the growth of the market
- To strategically analyze the micromarkets1 with respect to individual growth trends, prospects, and contributions to the total market
- To forecast the market size of the various segments with respect to four main regions: North America, Europe, APAC, and RoW
- To profile key players and comprehensively analyze their market rankings and core competencies2, and detail the competitive landscape for market leaders
- To analyze competitive developments such as joint ventures, collaborations, agreements, contracts, partnerships, mergers & acquisitions, new product developments, and R&D in the AI (chipsets) market
Available Customizations
MarketsandMarkets offers the following customizations for this report:
- Country-wise breakdown of various geographies, including North America, Europe,
Asia Pacific (APAC), and Rest of the World (RoW) - Market segmentation of various end-user industries into application segments
- Comprehensive coverage of regulations followed in each region (North America, APAC, Europe, and RoW)
Growth opportunities and latent adjacency in Artificial Intelligence (Chipsets) Market