Artificial Intelligence Chipset Market Size, Share & Trends Analysis Report by Offerings (GPU, CPU, FPGA, NPU, TPU, Trainium, Inferentia, T-head, Athena ASIC, MTIA, LPU), by Memory (DRAM (HBM, DDR)), by Network (NIC/Network Adapters, Interconnects)), by Function (Training, Inference), by End-user Industry (Consumers, Data centers, government organizations), Region And Segment Forecasts, 2025-2034

Report Id: 1897 Pages: 180 Last Updated: 16 April 2025 Format: PDF / PPT / Excel / Power BI
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Segmentation of Artificial Intelligence Chipset Market-

Artificial Intelligence Chipset Market By Offering:

  • GPU
  • CPU
  • FPGA
  • NPU
  • TPU
  • Dojo & FSD
  • Trainium & Inferentia
  • Athena ASIC
  • T-head
  • MTIA
  • LPU
  • Other ASIC

ai chipset

 

Artificial Intelligence Chipset Market By Memory:

  • HBM
  • DDR

Artificial Intelligence Chipset Market By Network:

  • NIC/Network Adapters
    • Infiniband
    • Ethernet
  • Interconnects

Artificial Intelligence Chipset Market By Function

  • Training
  • Inference

Artificial Intelligence Chipset Market By Technology

  • Generative AI
    • Rule Based Models
    • Statistical Models
    • Deep Learning
    • Generative Adversarial Networks (GANs)
    • Autoencoders
    • Convolutional Neural Networks (CNNs)
    • Transformer Models
  • Machine Learning
  • Natural Language Processing
  • Computer Vision

Artificial Intelligence Chipset Market By End-User

  • Consumer
  • Data Center
    • CSP
    • Enterprises
      • Healthcare
      • BFSI
      • Automotive
      • Retail & E-Commerce
      • Media & Entertainment
      • Others
  • Government Organizations

Artificial Intelligence Chipset Market By Region-

North America-

  • The US
  • Canada

Europe-

  • Germany
  • The UK
  • France
  • Italy
  • Spain
  • Rest of Europe

Asia-Pacific-

  • China
  • Japan
  • India
  • South Korea
  • South East Asia
  • Rest of Asia Pacific

Latin America-

  • Brazil
  • Mexico
  • Argentina
  • Rest of Latin America

 Middle East & Africa-

  • GCC Countries
  • South Africa
  • Rest of Middle East and Africa

Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global AI Chip Market Snapshot

Chapter 4. Global AI Chip Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: by Offering Estimates & Trend Analysis
5.1. by Offering & Market Share, 2024 & 2034
5.2. Market Size (Value (US$ Mn) & Volume (Unit)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Offering:

5.2.1. GPU
5.2.2. CPU
5.2.3. FPGA
5.2.4. NPU
5.2.5. TPU
5.2.6. Dojo & FSD
5.2.7. Trainium & Inferentia
5.2.8. Athena ASIC
5.2.9. T-head
5.2.10. MTIA
5.2.11. LPU
5.2.12. Other ASIC

Chapter 6. Market Segmentation 2: by Memory Estimates & Trend Analysis
6.1. by Memory & Market Share, 2024 & 2034
6.2. Market Size (Value (US$ Mn) & Volume (Unit)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Memory:

6.2.1. HBM
6.2.2. DDR

Chapter 7. Market Segmentation 3: by Network Estimates & Trend Analysis
7.1. by Network & Market Share, 2024 & 2034
7.2. Market Size (Value (US$ Mn) & Volume (Unit)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Network:

7.2.1. NIC/Network Adapters
7.2.1.1. Infiniband
7.2.1.2. Ethernet
7.2.2. Interconnects

Chapter 8. Market Segmentation 4: by Technology Estimates & Trend Analysis
8.1. by Technology & Market Share, 2024 & 2034
8.2. Market Size (Value (US$ Mn) & Volume (Unit)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Technology:

8.2.1. Generative AI
8.2.1.1. Rule Based Models
8.2.1.2. Statistical Models
8.2.1.3. Deep Learning
8.2.1.4. Generative Adversarial Networks (GANs)
8.2.1.5. Autoencoders
8.2.1.6. Convolutional Neural Networks (CNNs)
8.2.1.7. Transformer Models
8.2.2. Machine Learning
8.2.3. Natural Language Processing
8.2.4. Computer Vision

Chapter 9. Market Segmentation 5: by Function Estimates & Trend Analysis
9.1. by Function & Market Share, 2024 & 2034
9.2. Market Size (Value (US$ Mn) & Volume (Unit)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Function:

9.2.1. Training
9.2.2. Inference

Chapter 10. Market Segmentation 6: by End User Estimates & Trend Analysis
10.1. by End User & Market Share, 2024 & 2034
10.2. Market Size (Value (US$ Mn) & Volume (Unit)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by End User:

10.2.1. Consumer
10.2.2. Data Center
10.2.2.1. CSP
10.2.2.2. Enterprises
10.2.2.2.1. Healthcare
10.2.2.2.2. BFSI
10.2.2.2.3. Automotive
10.2.2.2.4. Retail & E-Commerce
10.2.2.2.5. Media & Entertainment
10.2.2.2.6. Others
10.2.3. Government Organizations

Chapter 11. AI Chip Market Segmentation 7: Regional Estimates & Trend Analysis
11.1. North America
11.1.1. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Offering, 2021-2034
11.1.2. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Memory, 2021-2034
11.1.3. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Network, 2021-2034
11.1.4. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Technology, 2021-2034
11.1.5. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Function, 2021-2034
11.1.6. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by End User, 2021-2034
11.1.7. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by country, 2021-2034
11.2. Europe
11.2.1. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Offering, 2021-2034
11.2.2. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Memory, 2021-2034
11.2.3. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Network, 2021-2034
11.2.4. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Technology, 2021-2034
11.2.5. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Function, 2021-2034
11.2.6. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by End User, 2021-2034
11.2.7. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by country, 2021-2034
11.3. Asia Pacific
11.3.1. Asia Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Offering, 2021-2034
11.3.2. Asia Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Memory, 2021-2034
11.3.3. Asia Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Network, 2021-2034
11.3.4. Asia Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Technology, 2021-2034
11.3.5. Asia-Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Function, 2021-2034
11.3.6. Asia-Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by End User, 2021-2034
11.3.7. Asia Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by country, 2021-2034
11.4. Latin America
11.4.1. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Offering, 2021-2034
11.4.2. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Memory, 2021-2034
11.4.3. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Network, 2021-2034
11.4.4. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Technology, 2021-2034
11.4.5. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Function, 2021-2034
11.4.6. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by End User, 2021-2034
11.4.7. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by country, 2021-2034
11.5. Middle East & Africa
11.5.1. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Offering, 2021-2034
11.5.2. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Memory, 2021-2034
11.5.3. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Network, 2021-2034
11.5.4. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Technology, 2021-2034
11.5.5. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Function, 2021-2034
11.5.6. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by End User, 2021-2034
11.5.7. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by country, 2021-2034

Chapter 12. Competitive Landscape
12.1. Major Mergers and Acquisitions/Strategic Alliances
12.2. Company Profiles

12.2.1. Advanced Micro Devices, Inc. (AMD)
12.2.2. Alibaba Group Holding Limited
12.2.3. Alphabet Inc. (Google LLC)
12.2.4. Amazon Web Services (AWS)
12.2.5. Fujitsu Limited
12.2.6. General Vision, Inc.
12.2.7. Graphcore Limited
12.2.8. GreenWaves Technologies
12.2.9. Huawei Technologies Co., Ltd.
12.2.10. Intel Corporation
12.2.11. International Business Machines Corporation (IBM)
12.2.12. Kalray Corporation
12.2.13. Kneron
12.2.14. Koniku Inc
12.2.15. MediaTek Inc.
12.2.16. Micron Technology, Inc.
12.2.17. Microsoft Corporation
12.2.18. Mythic Inc.
12.2.19. NVIDIA Corporation
12.2.20. Qualcomm Technologies, Inc.
12.2.21. SambaNova Systems Inc
12.2.22. Samsung Electronics Co., Ltd.
12.2.23. Tenstorrent Inc.
12.2.24. Wave Computing, Inc.
12.2.25. Xilinx, Inc.
12.2.26. XMOS Limited
12.2.27. Other Prominent Players

Research Design and Approach

This study employed a multi-step, mixed-method research approach that integrates:

  • Secondary research
  • Primary research
  • Data triangulation
  • Hybrid top-down and bottom-up modelling
  • Forecasting and scenario analysis

This approach ensures a balanced and validated understanding of both macro- and micro-level market factors influencing the market.

Secondary Research

Secondary research for this study involved the collection, review, and analysis of publicly available and paid data sources to build the initial fact base, understand historical market behaviour, identify data gaps, and refine the hypotheses for primary research.

Sources Consulted

Secondary data for the market study was gathered from multiple credible sources, including:

  • Government databases, regulatory bodies, and public institutions
  • International organizations (WHO, OECD, IMF, World Bank, etc.)
  • Commercial and paid databases
  • Industry associations, trade publications, and technical journals
  • Company annual reports, investor presentations, press releases, and SEC filings
  • Academic research papers, patents, and scientific literature
  • Previous market research publications and syndicated reports

These sources were used to compile historical data, market volumes/prices, industry trends, technological developments, and competitive insights.

Secondary Research

Primary Research

Primary research was conducted to validate secondary data, understand real-time market dynamics, capture price points and adoption trends, and verify the assumptions used in the market modelling.

Stakeholders Interviewed

Primary interviews for this study involved:

  • Manufacturers and suppliers in the market value chain
  • Distributors, channel partners, and integrators
  • End-users / customers (e.g., hospitals, labs, enterprises, consumers, etc., depending on the market)
  • Industry experts, technology specialists, consultants, and regulatory professionals
  • Senior executives (CEOs, CTOs, VPs, Directors) and product managers

Interview Process

Interviews were conducted via:

  • Structured and semi-structured questionnaires
  • Telephonic and video interactions
  • Email correspondences
  • Expert consultation sessions

Primary insights were incorporated into demand modelling, pricing analysis, technology evaluation, and market share estimation.

Data Processing, Normalization, and Validation

All collected data were processed and normalized to ensure consistency and comparability across regions and time frames.

The data validation process included:

  • Standardization of units (currency conversions, volume units, inflation adjustments)
  • Cross-verification of data points across multiple secondary sources
  • Normalization of inconsistent datasets
  • Identification and resolution of data gaps
  • Outlier detection and removal through algorithmic and manual checks
  • Plausibility and coherence checks across segments and geographies

This ensured that the dataset used for modelling was clean, robust, and reliable.

Market Size Estimation and Data Triangulation

Bottom-Up Approach

The bottom-up approach involved aggregating segment-level data, such as:

  • Company revenues
  • Product-level sales
  • Installed base/usage volumes
  • Adoption and penetration rates
  • Pricing analysis

This method was primarily used when detailed micro-level market data were available.

Bottom Up Approach

Top-Down Approach

The top-down approach used macro-level indicators:

  • Parent market benchmarks
  • Global/regional industry trends
  • Economic indicators (GDP, demographics, spending patterns)
  • Penetration and usage ratios

This approach was used for segments where granular data were limited or inconsistent.

Hybrid Triangulation Approach

To ensure accuracy, a triangulated hybrid model was used. This included:

  • Reconciling top-down and bottom-up estimates
  • Cross-checking revenues, volumes, and pricing assumptions
  • Incorporating expert insights to validate segment splits and adoption rates

This multi-angle validation yielded the final market size.

Forecasting Framework and Scenario Modelling

Market forecasts were developed using a combination of time-series modelling, adoption curve analysis, and driver-based forecasting tools.

Forecasting Methods

  • Time-series modelling
  • S-curve and diffusion models (for emerging technologies)
  • Driver-based forecasting (GDP, disposable income, adoption rates, regulatory changes)
  • Price elasticity models
  • Market maturity and lifecycle-based projections

Scenario Analysis

Given inherent uncertainties, three scenarios were constructed:

  • Base-Case Scenario: Expected trajectory under current conditions
  • Optimistic Scenario: High adoption, favourable regulation, strong economic tailwinds
  • Conservative Scenario: Slow adoption, regulatory delays, economic constraints

Sensitivity testing was conducted on key variables, including pricing, demand elasticity, and regional adoption.

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Frequently Asked Questions

Artificial Intelligence Chipset Market Size is valued at USD 122.5 billion in 2024 and is predicted to reach USD 790.44 billion by the year 2034

Artificial Intelligence Chipset Market expected to grow at a 20.7% CAGR during the forecast period for 2025-2034

Intel Corporation (US), Nvidia Corporation (US), Qualcomm Technologies Inc. (US), Micron Technology, Inc. (US), Advanced Micro Devices, Inc. (US), Sam

Artificial Intelligence Chipset market is segmented on the basis of offering, technology, memory, network, function, and end user.

North American region is leading the Artificial Intelligence Chipset market.

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