Artificial Intelligence (chipset) Market forecast to 2034

Q: Which is the Top Chip Type in the Market?

CPU is the top chip type, dominating the market. Read Report

Artificial Intelligence (chipset) Market Outlook from 2024 to 2034

The artificial intelligence (chipset) market is projected to be valued at US$ 27.6 billion in 2024. It is expected to rise to US$ 287.0 billion by 2034. The demand for artificial intelligence chipsets is expected to grow at a CAGR of 26.4% over the forecast period.

The market is driven by the increasing demand for artificial intelligence applications across industries, the proliferation of data-intensive tasks, and advancements in semiconductor technology, fostering innovation and competition among key industry players.

Key Market Drivers

The increasing demand for artificial intelligence-powered devices and applications across various industries is driving the growth of the market.
Artificial intelligence chipsets offer faster processing speeds and better power efficiency, improving the performance of artificial intelligence applications.
The development of advanced artificial intelligence algorithms and models drives the demand for artificial intelligence chipsets that can handle complex computations and large datasets.
Integrating artificial intelligence with other technologies, such as the Internet of Things (IoT) and 5G, drives the demand for artificial intelligence chipsets that can handle high-speed data processing and communication.
The growing demand for edge computing and autonomous devices drives the demand for artificial intelligence chipsets that can handle real-time processing and decision-making.
Governments, research organizations, and technology companies are increasing their investments in artificial intelligence chipsets, driving market expansion.

Attributes	Key Statistics
Artificial Intelligence (Chipset) Market Value (2024)	US$ 27.6 billion
Anticipated Forecast Value (2034)	US$ 287.0 billion
Estimated CAGR (2024 to 2034)	26.4%

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Consumption Analysis of the Artificial Intelligence (Chipset) Market

The increasing adoption of artificial intelligence across various industries drives the demand for artificial intelligence chipsets.
The healthcare industry is adopting artificial intelligence chipsets to improve patient outcomes through personalized treatment plans and medical image analysis.
The automotive industry is adopting artificial intelligence chipsets for advanced driver assistance systems, autonomous vehicles, and predictive maintenance.
The consumer electronics industry is adopting artificial intelligence chipsets for voice assistants, smart home devices, and gaming applications.
The adoption of artificial intelligence chipsets for fraud detection, customer service, and predictive maintenance is also increasing in the finance, retail, and manufacturing industries.
The versatility and scalability of artificial intelligence chipsets and their ability to handle complex computations and large datasets have made them increasingly popular across various industries.

Factors Adversely Affecting the Artificial Intelligence (Chipset) Market

The market is anticipated to surpass a valuation of US$ 287.0 billion by 2034, expanding at a CAGR of 26.4% through 2034. While it is expected to experience tremendous growth, several restraining factors can adversely affect its development and expansion.

The high cost of artificial intelligence chipsets may deter budget-constrained businesses and consumers from adopting this technology.
A shortage of skilled professionals with expertise in artificial intelligence and chip design may hinder the effective deployment and maintenance of AI chipsets, slowing market growth.
The increasing concerns regarding artificial intelligence's ethical and privacy implications may lead to regulatory challenges and limit the adoption of AI chipsets.
Integrating artificial intelligence chipsets with existing systems and devices may require substantial modifications, posing challenges for organizations seeking a seamless transition to artificial intelligence-enhanced systems.
The competition among artificial intelligence chipset manufacturers and the rapid technological advancements may lead to a shorter product lifecycle and increased R&D expenses.

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Category-wise Insights

CPU’s Versatility and Widespread Adoption in Various Computing Applications

Attributes	Details
Top Chip Type	CPU
CAGR (2024 to 2034)	26.2%

Based on the chip type, the CPU segment dominates the market, growing at a 26.2% CAGR through 2034. This rising popularity of the segment is attributed to the following reasons:

CPUs can handle various tasks, making them suitable for diverse artificial intelligence workloads.
CPU manufacturers have been incorporating artificial intelligence-specific features and optimizations into their designs, significantly enhancing their performance in machine learning tasks.
The existing infrastructure and software ecosystems are well-established around CPU architectures, making it easier for developers to leverage these resources for artificial intelligence applications.
CPUs' compatibility with traditional software development tools allows for seamless integration of artificial intelligence capabilities into existing systems.

Demanding Computational Tasks Involved in Training AI Models

Attributes	Details
Top Workload Domain	Training
CAGR (2024 to 2034)	25.9%

Based on its workload domain, the training segment dominates the artificial intelligence (chipset) market. It is expected to grow at a 25.9% CAGR through 2034.

Specialized AI chips such as GPUs and TPUs have emerged as a solution to accelerate the training phase of artificial intelligence models.
With the increasing complexity of artificial intelligence models, like those in natural language processing and image recognition, organizations and researchers require high-performance chipsets to stay competitive in the artificial intelligence space.
The ever-growing demand for computational power to train more sophisticated artificial intelligence models drives the dominance of the training workload domain in the AI chipset market.

Country-wise Insights

The section analyzes the artificial intelligence (chipset) market by country, including the United States, the United Kingdom, China, Japan, and South Korea. The table presents the CAGR for each country, indicating the expected market growth in that country through 2034.

Countries	CAGR (2024 to 2034)
United States	26.5%
United Kingdom	28.0%
China	27.2%
Japan	28.2%
South Korea	27.6%

The United States’s thriving Ecosystem of Technology Companies, Research Institutions, and Innovation Hubs

The United States dominates the artificial intelligence (chipset) market in the North American region. It is expected to exhibit an annual growth rate of 26.5% until 2034.

Silicon Valley, in particular, is a global hub for artificial intelligence development, home to leading companies and startups specializing in semiconductor technology and artificial intelligence applications.
The United States has a culture of entrepreneurship, significant investments in R&D, and a strong focus on cutting-edge technologies, all of which position it at the forefront of the artificial intelligence (chipset) market.

World-class Research Institutions and Rapidly Growing Tech Industry of the United Kingdom

The United Kingdom is the leading European country in the artificial intelligence (chipset) market. The market is predicted to register an annual growth rate of 28.0% through 2034.

The United Kingdom strongly emphasizes artificial intelligence research and development, leading to algorithm and application breakthroughs.
British companies play a critical role in developing artificial intelligence chipsets, and the country's focus on fostering innovation and collaboration in the tech sector enhances its standing in the market.

Strategic Investments in Technological Developments in China

China is another Asian country in the artificial intelligence (chipset) market, which is anticipated to register a CAGR of 27.2% through 2034.

The Chinese government has prioritized artificial intelligence nationally, leading to substantial funding and initiatives to drive its development and adoption.
Backed by significant resources, Chinese companies have emerged as key players in manufacturing artificial intelligence chipsets, contributing to the country's dominance in this crucial market segment.

Japanese Long-standing Reputation for Technological Innovation

Japan is another Asian country leading the artificial intelligence (chipset) market. The Japanese market is anticipated to register a CAGR of 28.2% through 2034.

Japanese companies are renowned for their contributions to semiconductor technology, and the country's commitment to research and development has resulted in cutting-edge advancements in artificial intelligence chip design.
Japan's strong industrial base and collaborations between academia and industry contribute to its prominence in the global artificial intelligence chipset landscape.

Powerhouse Technology Companies Actively Support Development of Artificial Intelligence in South Korea

South Korea is one of the leading Asian countries in the artificial intelligence (chipset) market. The Korean artificial intelligence (chipset) market is expected to grow annually at 27.6% until 2034.

South Korean companies excel in semiconductor manufacturing, focusing on producing high-performance chips for artificial intelligence applications.
South Korea's commitment to fostering a tech-savvy environment and robust research and development initiatives positions South Korea as a key player in the global artificial intelligence (chipset) market.

Competitive Landscape

The artificial intelligence (AI) chipset market has grown significantly in recent years, and several major companies have contributed to this trend.

NVIDIA, a leading graphics processing unit (GPU) manufacturer, has emerged as a key player among these companies. Its GPUs, including the NVIDIA Tesla and NVIDIA A100, are widely used in artificial intelligence applications due to their parallel processing capabilities.

NVIDIA's acquisition of ARM, a major player in semiconductor design, has further solidified the company's position as a key influencer in the artificial intelligence (chipset) market.

Another major market player is Intel, a semiconductor giant that heavily invests in artificial intelligence-related technologies. Intel's portfolio includes CPUs and specialized accelerators like the Intel Nervana Neural Network Processors, which cater to diverse needs in the growing market. Intel aims to provide a comprehensive range of hardware solutions for artificial intelligence applications.

Recent Developments

On November 7, 2023, it was reported that Huawei has planned to challenge Nvidia. US restrictions on Nvidia's AI chip sales to China allowed Huawei to gain higher market share.
On January 30, 2024, the startup Rebellions launched its ATOM chip in South Korea. The chip aims to compete with Nvidia Corp, positioning itself as the latest Korean artificial intelligence technology hardware contender.
On September 20, 2023, Intel announced its inaugural artificial intelligence-equipped chipset for personal computers, marking the USA chipmaker's entry into the artificial intelligence-powered PC competition. The move aimed to revitalize the PC market and reclaim global semiconductor industry leadership.
On June 14, 2023, Amazon Web Services (AWS) reportedly considered employing artificial intelligence (AI) chips from Advanced Micro Devices (AMD) after rejecting Nvidia. The move aimed to enhance AWS's cloud computing services.

Key Companies in the Market

Nvidia Corporation
Intel Corporation
Xilinx Inc.
Samsung Electronics Co., Ltd
Micron Technology
Qualcomm Technologies
IBM Corporation
Google Inc.
Microsoft Corporation
Apple Inc.
Amazon Web Services (AWS)
Advanced Micro Devices, Inc.
Graphcore
General Vision
Mellanox Technologies
Huawei Technologies Co. Ltd
Fujitsu
Wave Computing
Mythic Inc.
Adapteva
Koniku
Tenstorrent

Key Market Segmentation

By Chip Type:

CPU
GPU
FPGA
ASIC
Others

By Workload Domain:

Training
Inference

By Computing Technology:

Cloud AI Computing
Edge AI Computing

By Vertical:

Healthcare
Manufacturing
Automotive
Retail & E-Commerce
Marketing
Consumer Electronics

By Region:

Asia Pacific
Europe
North America
Middle East & Africa
Latin America

Frequently Asked Questions

How Big is the Artificial Intelligence (Chipset) Market in 2024?

The artificial intelligence (chipset) market is predicted to be worth US$ 27.6 billion in 2024.

What is the Sales Forecast for Artificial Intelligence Chipsets through 2034?

The artificial intelligence (AI) chipset market is expected to reach US$ 287.0 billion by 2034.

At What Rate is the Artificial Intelligence (chipset) Market Expected to Grow?

The artificial intelligence (chipset market) is expected to grow at a CAGR of 26.4% from 2024 to 2034.

Which are the Key Companies in the Market?

Some key players in the market are Nvidia Corporation, Intel Corporation, Xilinx Inc., Samsung Electronics Co., Ltd, Micron Technology, Qualcomm Technologies, IBM Corporation, Google Inc., Microsoft Corporation, Apple Inc., and Amazon Web Services (AWS).

Which is the Top Chip Type in the Market?

CPU is the top chip type, dominating the market.

Table of Content

1. Executive Summary

1.1. Global Market Outlook

1.2. Demand-side Trends

1.3. Supply-side Trends

1.4. Technology Roadmap Analysis

1.5. Analysis and Recommendations

2. Market Overview

2.1. Market Coverage / Taxonomy

2.2. Market Definition / Scope / Limitations

3. Market Background

3.1. Market Dynamics

3.1.1. Drivers

3.1.2. Restraints

3.1.3. Opportunity

3.1.4. Trends

3.2. Scenario Forecast

3.2.1. Demand in Optimistic Scenario

3.2.2. Demand in Likely Scenario

3.2.3. Demand in Conservative Scenario

3.3. Opportunity Map Analysis

3.4. Product Life Cycle Analysis

3.5. Supply Chain Analysis

3.5.1. Supply Side Participants and their Roles

3.5.1.1. Producers

3.5.1.2. Mid-Level Participants (Traders/ Agents/ Brokers)

3.5.1.3. Wholesalers and Distributors

3.5.2. Value Added and Value Created at Node in the Supply Chain

3.5.3. List of Raw Material Suppliers

3.5.4. List of Existing and Potential Buyer’s

3.6. Investment Feasibility Matrix

3.7. Value Chain Analysis

3.7.1. Profit Margin Analysis

3.7.2. Wholesalers and Distributors

3.7.3. Retailers

3.8. PESTLE and Porter’s Analysis

3.9. Regulatory Landscape

3.9.1. By Key Regions

3.9.2. By Key Countries

3.10. Regional Parent Market Outlook

3.11. Production and Consumption Statistics

3.12. Import and Export Statistics

4. Global Market Analysis 2019 to 2023 and Forecast, 2024 to 2034

4.1. Historical Market Size Value (US$ Million) & Volume (Units) Analysis, 2019 to 2023

4.2. Current and Future Market Size Value (US$ Million) & Volume (Units) Projections, 2024 to 2034

4.2.1. Y-o-Y Growth Trend Analysis

4.2.2. Absolute $ Opportunity Analysis

5. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Chip Type

5.1. Introduction / Key Findings

5.2. Historical Market Size Value (US$ Million) & Volume (Units) Analysis By Chip Type, 2019 to 2023

5.3. Current and Future Market Size Value (US$ Million) & Volume (Units) Analysis and Forecast By Chip Type, 2024 to 2034

5.3.1. CPU

5.3.2. GPU

5.3.3. FPGA

5.3.4. ASIC

5.3.5. Others

5.4. Y-o-Y Growth Trend Analysis By Chip Type, 2019 to 2023

5.5. Absolute $ Opportunity Analysis By Chip Type, 2024 to 2034

6. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Workload Domain

6.1. Introduction / Key Findings

6.2. Historical Market Size Value (US$ Million) & Volume (Units) Analysis By Workload Domain, 2019 to 2023

6.3. Current and Future Market Size Value (US$ Million) & Volume (Units) Analysis and Forecast By Workload Domain, 2024 to 2034

6.3.1. Training

6.3.2. Inference

6.4. Y-o-Y Growth Trend Analysis By Workload Domain, 2019 to 2023

6.5. Absolute $ Opportunity Analysis By Workload Domain, 2024 to 2034

7. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Computing Technology

7.1. Introduction / Key Findings

7.2. Historical Market Size Value (US$ Million) & Volume (Units) Analysis By Computing Technology, 2019 to 2023

7.3. Current and Future Market Size Value (US$ Million) & Volume (Units) Analysis and Forecast By Computing Technology, 2024 to 2034

7.3.1. Cloud AI Computing

7.3.2. Edge AI Computing

7.4. Y-o-Y Growth Trend Analysis By Computing Technology, 2019 to 2023

7.5. Absolute $ Opportunity Analysis By Computing Technology, 2024 to 2034

8. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Vertical

8.1. Introduction / Key Findings

8.2. Historical Market Size Value (US$ Million) & Volume (Units) Analysis By Vertical, 2019 to 2023

8.3. Current and Future Market Size Value (US$ Million) & Volume (Units) Analysis and Forecast By Vertical, 2024 to 2034

8.3.1. Healthcare

8.3.2. Manufacturing

8.3.3. Automotive

8.3.4. Retail & E-Commerce

8.3.5. Marketing

8.3.6. Consumer Electronics

8.3.7. BFSI

8.3.8. Others

8.4. Y-o-Y Growth Trend Analysis By Vertical, 2019 to 2023

8.5. Absolute $ Opportunity Analysis By Vertical, 2024 to 2034

9. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Region

9.1. Introduction

9.2. Historical Market Size Value (US$ Million) & Volume (Units) Analysis By Region, 2019 to 2023

9.3. Current Market Size Value (US$ Million) & Volume (Units) Analysis and Forecast By Region, 2024 to 2034

9.3.1. North America

9.3.2. Latin America

9.3.3. Western Europe

9.3.4. Eastern Europe

9.3.5. South Asia and Pacific

9.3.6. East Asia

9.3.7. Middle East and Africa

9.4. Market Attractiveness Analysis By Region

10. North America Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country

10.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2019 to 2023

10.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2024 to 2034

10.2.1. By Country

10.2.1.1. USA

10.2.1.2. Canada

10.2.2. By Chip Type

10.2.3. By Workload Domain

10.2.4. By Computing Technology

10.2.5. By Vertical

10.3. Market Attractiveness Analysis

10.3.1. By Country

10.3.2. By Chip Type

10.3.3. By Workload Domain

10.3.4. By Computing Technology

10.3.5. By Vertical

10.4. Key Takeaways

11. Latin America Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country

11.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2019 to 2023

11.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2024 to 2034

11.2.1. By Country

11.2.1.1. Brazil

11.2.1.2. Mexico

11.2.1.3. Rest of Latin America

11.2.2. By Chip Type

11.2.3. By Workload Domain

11.2.4. By Computing Technology

11.2.5. By Vertical

11.3. Market Attractiveness Analysis

11.3.1. By Country

11.3.2. By Chip Type

11.3.3. By Workload Domain

11.3.4. By Computing Technology

11.3.5. By Vertical

11.4. Key Takeaways

12. Western Europe Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country

12.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2019 to 2023

12.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2024 to 2034

12.2.1. By Country

12.2.1.1. Germany

12.2.1.2. UK

12.2.1.3. France

12.2.1.4. Spain

12.2.1.5. Italy

12.2.1.6. Rest of Western Europe

12.2.2. By Chip Type

12.2.3. By Workload Domain

12.2.4. By Computing Technology

12.2.5. By Vertical

12.3. Market Attractiveness Analysis

12.3.1. By Country

12.3.2. By Chip Type

12.3.3. By Workload Domain

12.3.4. By Computing Technology

12.3.5. By Vertical

12.4. Key Takeaways

13. Eastern Europe Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country

13.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2019 to 2023

13.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2024 to 2034

13.2.1. By Country

13.2.1.1. Poland

13.2.1.2. Russia

13.2.1.3. Czech Republic

13.2.1.4. Romania

13.2.1.5. Rest of Eastern Europe

13.2.2. By Chip Type

13.2.3. By Workload Domain

13.2.4. By Computing Technology

13.2.5. By Vertical

13.3. Market Attractiveness Analysis

13.3.1. By Country

13.3.2. By Chip Type

13.3.3. By Workload Domain

13.3.4. By Computing Technology

13.3.5. By Vertical

13.4. Key Takeaways

14. South Asia and Pacific Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country

14.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2019 to 2023

14.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2024 to 2034

14.2.1. By Country

14.2.1.1. India

14.2.1.2. Bangladesh

14.2.1.3. Australia

14.2.1.4. New Zealand

14.2.1.5. Rest of South Asia and Pacific

14.2.2. By Chip Type

14.2.3. By Workload Domain

14.2.4. By Computing Technology

14.2.5. By Vertical

14.3. Market Attractiveness Analysis

14.3.1. By Country

14.3.2. By Chip Type

14.3.3. By Workload Domain

14.3.4. By Computing Technology

14.3.5. By Vertical

14.4. Key Takeaways

15. East Asia Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country

15.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2019 to 2023

15.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2024 to 2034

15.2.1. By Country

15.2.1.1. China

15.2.1.2. Japan

15.2.1.3. South Korea

15.2.2. By Chip Type

15.2.3. By Workload Domain

15.2.4. By Computing Technology

15.2.5. By Vertical

15.3. Market Attractiveness Analysis

15.3.1. By Country

15.3.2. By Chip Type

15.3.3. By Workload Domain

15.3.4. By Computing Technology

15.3.5. By Vertical

15.4. Key Takeaways

16. Middle East and Africa Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country

16.1. Historical Market Size Value (US$ Million) & Volume (Units) Trend Analysis By Market Taxonomy, 2019 to 2023

16.2. Market Size Value (US$ Million) & Volume (Units) Forecast By Market Taxonomy, 2024 to 2034

16.2.1. By Country

16.2.1.1. GCC Countries

16.2.1.2. South Africa

16.2.1.3. Israel

16.2.1.4. Rest of MEA

16.2.2. By Chip Type

16.2.3. By Workload Domain

16.2.4. By Computing Technology

16.2.5. By Vertical

16.3. Market Attractiveness Analysis

16.3.1. By Country

16.3.2. By Chip Type

16.3.3. By Workload Domain

16.3.4. By Computing Technology

16.3.5. By Vertical

16.4. Key Takeaways

17. Key Countries Market Analysis

17.1. USA

17.1.1. Pricing Analysis

17.1.2. Market Share Analysis, 2023

17.1.2.1. By Chip Type

17.1.2.2. By Workload Domain

17.1.2.3. By Computing Technology

17.1.2.4. By Vertical

17.2. Canada

17.2.1. Pricing Analysis

17.2.2. Market Share Analysis, 2023

17.2.2.1. By Chip Type

17.2.2.2. By Workload Domain

17.2.2.3. By Computing Technology

17.2.2.4. By Vertical

17.3. Brazil

17.3.1. Pricing Analysis

17.3.2. Market Share Analysis, 2023

17.3.2.1. By Chip Type

17.3.2.2. By Workload Domain

17.3.2.3. By Computing Technology

17.3.2.4. By Vertical

17.4. Mexico

17.4.1. Pricing Analysis

17.4.2. Market Share Analysis, 2023

17.4.2.1. By Chip Type

17.4.2.2. By Workload Domain

17.4.2.3. By Computing Technology

17.4.2.4. By Vertical

17.5. Germany

17.5.1. Pricing Analysis

17.5.2. Market Share Analysis, 2023

17.5.2.1. By Chip Type

17.5.2.2. By Workload Domain

17.5.2.3. By Computing Technology

17.5.2.4. By Vertical

17.6. UK

17.6.1. Pricing Analysis

17.6.2. Market Share Analysis, 2023

17.6.2.1. By Chip Type

17.6.2.2. By Workload Domain

17.6.2.3. By Computing Technology

17.6.2.4. By Vertical

17.7. France

17.7.1. Pricing Analysis

17.7.2. Market Share Analysis, 2023

17.7.2.1. By Chip Type

17.7.2.2. By Workload Domain

17.7.2.3. By Computing Technology

17.7.2.4. By Vertical

17.8. Spain

17.8.1. Pricing Analysis

17.8.2. Market Share Analysis, 2023

17.8.2.1. By Chip Type

17.8.2.2. By Workload Domain

17.8.2.3. By Computing Technology

17.8.2.4. By Vertical

17.9. Italy

17.9.1. Pricing Analysis

17.9.2. Market Share Analysis, 2023

17.9.2.1. By Chip Type

17.9.2.2. By Workload Domain

17.9.2.3. By Computing Technology

17.9.2.4. By Vertical

17.10. Poland

17.10.1. Pricing Analysis

17.10.2. Market Share Analysis, 2023

17.10.2.1. By Chip Type

17.10.2.2. By Workload Domain

17.10.2.3. By Computing Technology

17.10.2.4. By Vertical

17.11. Russia

17.11.1. Pricing Analysis

17.11.2. Market Share Analysis, 2023

17.11.2.1. By Chip Type

17.11.2.2. By Workload Domain

17.11.2.3. By Computing Technology

17.11.2.4. By Vertical

17.12. Czech Republic

17.12.1. Pricing Analysis

17.12.2. Market Share Analysis, 2023

17.12.2.1. By Chip Type

17.12.2.2. By Workload Domain

17.12.2.3. By Computing Technology

17.12.2.4. By Vertical

17.13. Romania

17.13.1. Pricing Analysis

17.13.2. Market Share Analysis, 2023

17.13.2.1. By Chip Type

17.13.2.2. By Workload Domain

17.13.2.3. By Computing Technology

17.13.2.4. By Vertical

17.14. India

17.14.1. Pricing Analysis

17.14.2. Market Share Analysis, 2023

17.14.2.1. By Chip Type

17.14.2.2. By Workload Domain

17.14.2.3. By Computing Technology

17.14.2.4. By Vertical

17.15. Bangladesh

17.15.1. Pricing Analysis

17.15.2. Market Share Analysis, 2023

17.15.2.1. By Chip Type

17.15.2.2. By Workload Domain

17.15.2.3. By Computing Technology

17.15.2.4. By Vertical

17.16. Australia

17.16.1. Pricing Analysis

17.16.2. Market Share Analysis, 2023

17.16.2.1. By Chip Type

17.16.2.2. By Workload Domain

17.16.2.3. By Computing Technology

17.16.2.4. By Vertical

17.17. New Zealand

17.17.1. Pricing Analysis

17.17.2. Market Share Analysis, 2023

17.17.2.1. By Chip Type

17.17.2.2. By Workload Domain

17.17.2.3. By Computing Technology

17.17.2.4. By Vertical

17.18. China

17.18.1. Pricing Analysis

17.18.2. Market Share Analysis, 2023

17.18.2.1. By Chip Type

17.18.2.2. By Workload Domain

17.18.2.3. By Computing Technology

17.18.2.4. By Vertical

17.19. Japan

17.19.1. Pricing Analysis

17.19.2. Market Share Analysis, 2023

17.19.2.1. By Chip Type

17.19.2.2. By Workload Domain

17.19.2.3. By Computing Technology

17.19.2.4. By Vertical

17.20. South Korea

17.20.1. Pricing Analysis

17.20.2. Market Share Analysis, 2023

17.20.2.1. By Chip Type

17.20.2.2. By Workload Domain

17.20.2.3. By Computing Technology

17.20.2.4. By Vertical

17.21. GCC Countries

17.21.1. Pricing Analysis

17.21.2. Market Share Analysis, 2023

17.21.2.1. By Chip Type

17.21.2.2. By Workload Domain

17.21.2.3. By Computing Technology

17.21.2.4. By Vertical

17.22. South Africa

17.22.1. Pricing Analysis

17.22.2. Market Share Analysis, 2023

17.22.2.1. By Chip Type

17.22.2.2. By Workload Domain

17.22.2.3. By Computing Technology

17.22.2.4. By Vertical

17.23. Israel

17.23.1. Pricing Analysis

17.23.2. Market Share Analysis, 2023

17.23.2.1. By Chip Type

17.23.2.2. By Workload Domain

17.23.2.3. By Computing Technology

17.23.2.4. By Vertical

18. Market Structure Analysis

18.1. Competition Dashboard

18.2. Competition Benchmarking

18.3. Market Share Analysis of Top Players

18.3.1. By Regional

18.3.2. By Chip Type

18.3.3. By Workload Domain

18.3.4. By Computing Technology

18.3.5. By Vertical

19. Competition Analysis

19.1. Competition Deep Dive

19.1.1. Intel Corporation

19.1.1.1. Overview

19.1.1.2. Product Portfolio

19.1.1.3. Profitability by Market Segments

19.1.1.4. Sales Footprint

19.1.1.5. Strategy Overview

19.1.1.5.1. Marketing Strategy

19.1.1.5.2. Product Strategy

19.1.1.5.3. Channel Strategy

19.1.2. Advanced Micro Devices Inc

19.1.2.1. Overview

19.1.2.2. Product Portfolio

19.1.2.3. Profitability by Market Segments

19.1.2.4. Sales Footprint

19.1.2.5. Strategy Overview

19.1.2.5.1. Marketing Strategy

19.1.2.5.2. Product Strategy

19.1.2.5.3. Channel Strategy

19.1.3. Baidu Inc

19.1.3.1. Overview

19.1.3.2. Product Portfolio

19.1.3.3. Profitability by Market Segments

19.1.3.4. Sales Footprint

19.1.3.5. Strategy Overview

19.1.3.5.1. Marketing Strategy

19.1.3.5.2. Product Strategy

19.1.3.5.3. Channel Strategy

19.1.4. Google Inc

19.1.4.1. Overview

19.1.4.2. Product Portfolio

19.1.4.3. Profitability by Market Segments

19.1.4.4. Sales Footprint

19.1.4.5. Strategy Overview

19.1.4.5.1. Marketing Strategy

19.1.4.5.2. Product Strategy

19.1.4.5.3. Channel Strategy

19.1.5. Qualcomm Technologies, Inc

19.1.5.1. Overview

19.1.5.2. Product Portfolio

19.1.5.3. Profitability by Market Segments

19.1.5.4. Sales Footprint

19.1.5.5. Strategy Overview

19.1.5.5.1. Marketing Strategy

19.1.5.5.2. Product Strategy

19.1.5.5.3. Channel Strategy

19.1.6. Graphcore

19.1.6.1. Overview

19.1.6.2. Product Portfolio

19.1.6.3. Profitability by Market Segments

19.1.6.4. Sales Footprint

19.1.6.5. Strategy Overview

19.1.6.5.1. Marketing Strategy

19.1.6.5.2. Product Strategy

19.1.6.5.3. Channel Strategy

19.1.7. Apple Inc

19.1.7.1. Overview

19.1.7.2. Product Portfolio

19.1.7.3. Profitability by Market Segments

19.1.7.4. Sales Footprint

19.1.7.5. Strategy Overview

19.1.7.5.1. Marketing Strategy

19.1.7.5.2. Product Strategy

19.1.7.5.3. Channel Strategy

19.1.8. Huawei Technologies Co., Ltd

19.1.8.1. Overview

19.1.8.2. Product Portfolio

19.1.8.3. Profitability by Market Segments

19.1.8.4. Sales Footprint

19.1.8.5. Strategy Overview

19.1.8.5.1. Marketing Strategy

19.1.8.5.2. Product Strategy

19.1.8.5.3. Channel Strategy

19.1.9. Mythic

19.1.9.1. Overview

19.1.9.2. Product Portfolio

19.1.9.3. Profitability by Market Segments

19.1.9.4. Sales Footprint

19.1.9.5. Strategy Overview

19.1.9.5.1. Marketing Strategy

19.1.9.5.2. Product Strategy

19.1.9.5.3. Channel Strategy

19.1.10. Xilinx Inc

19.1.10.1. Overview

19.1.10.2. Product Portfolio

19.1.10.3. Profitability by Market Segments

19.1.10.4. Sales Footprint

19.1.10.5. Strategy Overview

19.1.10.5.1. Marketing Strategy

19.1.10.5.2. Product Strategy

19.1.10.5.3. Channel Strategy

20. Assumptions & Acronyms Used

21. Research Methodology

Artificial Intelligence (chipset) Market

Artificial Intelligence (chipset) Market Forecast by Cloud AI Computing and Edge AI Computing from 2024 to 2034