AI 가속기 시장 규모, 점유율, 성장 및 산업 분석 : 유형별, 용도별, 지역별 인사이트 및 예측(2026-2034년)

Growth Factors of AI accelerator Market

The global AI accelerator market was valued at USD 33.69 billion in 2025 and is projected to grow to USD 43.75 billion in 2026, reaching USD 309.23 billion by 2034, registering a strong CAGR of 30.7% during the forecast period.

Asia Pacific dominated the market with a 40.70% share in 2025, supported by strong semiconductor manufacturing ecosystems and rapid AI infrastructure expansion. The region recorded USD 13.7 billion in 2025 and increased to USD 17.76 billion in 2026.

AI accelerators are specialized hardware components designed to handle complex AI computations efficiently. These processors support AI model training, inference, deep learning, and high-performance computing workloads. Increasing demand for AI chips by hyperscalers and cloud providers is significantly driving growth. Industry analysts estimate that data center and AI-related hardware could reach USD 1.4 trillion by 2027.

The COVID-19 pandemic initially disrupted supply chains and created chip shortages; however, companies such as NVIDIA secured early production capacity, strengthening their competitive position during the AI hardware surge.

Impact of Generative AI

Generative AI is transforming accelerator architecture and chip design. According to ISG 2024, spending on Gen AI initiatives is expected to increase by 50% in 2025 compared to 2024. AI-powered design tools such as Synopsys.ai Copilot integrate LLMs into chip workflows to optimize architecture innovation.

Industry experts project that chips powering generative AI will reach USD 50 billion by the end of 2025, with projections rising to approximately USD 700 billion by 2027, indicating massive demand for high-performance accelerators.

Impact of Reciprocal Tariffs

Reciprocal tariffs significantly affect the AI accelerator ecosystem due to its globally distributed manufacturing network. Increased import-export costs elevate data center infrastructure expenses and delay shipments. Companies are shifting production strategies or localizing supply chains to mitigate tariff-related risks.

Market Dynamics

Market Drivers

The growing need for high-performance computing (HPC) in AI workloads is a primary growth driver. GPUs, originally designed for gaming, have become essential for AI training due to their parallel processing capabilities. As AI models increase in complexity, demand for specialized accelerators rises accordingly.

Market Restraints

High implementation costs remain a key challenge. Infrastructure setup, integration with existing systems, and hardware procurement require significant capital investment, limiting adoption among smaller enterprises.

Market Opportunities

The rise of quantum computing accelerators presents strong long-term opportunities. Integrating quantum processors with AI acceleration capabilities could enhance computational efficiency in areas such as material science, cryptography, and drug discovery.

Key Market Trend

Energy Efficiency Focus

There is growing emphasis on designing energy-efficient AI accelerators to reduce power consumption in AI data centers. Advanced chip architectures are being developed to balance performance with sustainability goals while lowering operational expenses.

Segmentation Analysis

By Type

GPUs dominated with a 30.07% share in 2026, driven by their superior parallel processing capabilities.

ASICs are projected to grow at the highest CAGR, as hyperscalers such as Google, Amazon, and Meta deploy custom-designed chips for improved efficiency and lower total silicon costs.

By Technology

The cloud-based segment led with 59.21% share in 2026, reflecting strong demand from hyperscale data centers.

Edge AI is expected to grow fastest, driven by real-time processing needs in IoT devices, smartphones, and autonomous vehicles.

By Application

The fraud detection segment accounted for 32.89% share in 2026, supported by rising cybercrime and financial transaction monitoring needs. Mastercard's AI platform processes 159 billion transactions annually, improving fraud detection rates by up to 300%.

Autonomous vehicles are projected to witness the highest CAGR, fueled by advancements in ADAS and real-time perception systems.

By End-Use

The IT & telecom segment dominated in 2024, supported by high data traffic and virtualization requirements.

The automotive sector is expected to grow fastest due to increased adoption of EVs, V2X communication, and self-driving technologies.

Regional Outlook

Asia Pacific

Asia Pacific led with USD 13.7 billion in 2025 and USD 17.76 billion in 2026.

China is projected to reach USD 6.46 billion in 2026, Japan USD 3.9 billion, and India USD 2.43 billion. India has attracted over USD 40 billion in data center investments, with 950 MW installed capacity and an additional 850 MW planned by 2026.

North America

North America is expected to register the highest CAGR during the forecast period. The U.S. market is projected to reach USD 10.23 billion in 2026, driven by strong AI adoption and major technology players.

Europe

Europe is projected to experience strong growth, supported by automotive and industrial AI adoption. The UK market is expected to reach USD 1.64 billion in 2026, and Germany USD 1.48 billion.

South America & Middle East & Africa

These regions show gradual expansion, supported by government AI initiatives such as Saudi Arabia's Vision 2030 and UAE AI strategies.

Conclusion

The AI accelerator market is set to expand from USD 33.69 billion in 2025 to USD 309.23 billion by 2034, driven by generative AI demand, hyperscale cloud expansion, energy-efficient architectures, and increasing adoption across IT, finance, and automotive industries. Asia Pacific leads in market share, while North America is projected to record the fastest growth. Continuous innovation in ASICs, edge AI, and quantum integration will shape the competitive landscape through 2034.

Segmentation By Type

• Graphics Processing Units (GPUs)
• Tensor Processing Units (TPUs)
• Central Processing Units (CPUs)
• Application-Specific Integrated Circuits (ASICs)
• Field-Programmable Gate Arrays (FPGAs)

By Technology

• Cloud-Based
• Edge AI

By Application

• Fraud Detection
• Customer Experience Management
• Predictive Analytics
• Autonomous Vehicles
• Intelligent Virtual Assistants
• Others (Cost Optimization, etc.)

By End-Use

• IT & Telecom
• BFSI
• Retail
• Automotive
• Healthcare
• Others (Media and Entertainment, etc.)

By Region

• North America (By Type, Technology, Application, End-Use, and Country)
  • U.S. (By End-Use)
  • Canada (By End-Use)
  • Mexico (By End-Use)
• South America (By Type, Technology, Application, End-Use, and Country)
  • Brazil (By End-Use)
  • Argentina (By End-Use)
  • Rest of South America
• Europe (By Type, Technology, Application, End-Use, and Country)
  • U.K. (By End-Use)
  • Germany (By End-Use)
  • France (By End-Use)
  • Italy (By End-Use)
  • Spain (By End-Use)
  • Russia (By End-Use)
  • Benelux (By End-Use)
  • Nordics (By End-Use)
  • Rest of Europe
• Middle East & Africa (By Type, Technology, Application, End-Use, and Country)
  • Turkey (By End-Use)
  • Israel (By End-Use)
  • GCC (By End-Use)
  • North Africa (By End-Use)
  • South Africa (By End-Use)
  • Rest of the Middle East & Africa
• Asia Pacific (By Type, Technology, Application, End-Use, and Country)
  • China (By End-Use)
  • Japan (By End-Use)
  • India (By End-Use)
  • South Korea (By End-Use)
  • ASEAN (By End-Use)
  • Oceania (By End-Use)
  • Rest of Asia Pacific

Companies Profiled in the Report Nvidia Corporation (U.S.)

AMD (Advanced Micro Devices) (U.S.)

Intel Corporation (U.S.)

TSMC (Taiwan Semiconductor Manufacturing Co.) (Taiwan)

Samsung Electronics (South Korea)

Apple Inc. (U.S.)

Google LLC (U.S.)

Meta (U.S.)

Qualcomm Incorporated (U.S.)

IBM Corporation (U.S.)

Table of Content

1. Introduction

• 1.1. Definition, By Segment
• 1.2. Research Methodology/Approach
• 1.3. Data Sources

2. Executive Summary

3. Market Dynamics

• 3.1. Macro and Micro Economic Indicators
• 3.2. Drivers, Restraints, Opportunities and Trends
• 3.3. Impact of Generative AI
• 3.4. Impact of Reciprocal Tariffs on AI Accelerator Market

4. Competition Landscape

• 4.1. Business Strategies Adopted by Key Players
• 4.2. Consolidated SWOT Analysis of Key Players
• 4.3. Global AI Accelerator Key Players (Top 3 - 5) Market Share/Ranking, 2025

5. Global AI Accelerator Market Size Estimates and Forecasts, By Segments, 2021-2034

• 5.1. Key Findings
• 5.2. By Type (USD)
  • 5.2.1. Graphics Processing Units (GPUs)
  • 5.2.2. Tensor Processing Units (TPUs)
  • 5.2.3. Central Processing Units (CPUs)
  • 5.2.4. Application-Specific Integrated Circuits (ASICs)
  • 5.2.5. Field-Programmable Gate Arrays (FPGAs)
• 5.3. By Technology (USD)
  • 5.3.1. Cloud-Based
  • 5.3.2. Edge AI
• 5.4. By Application (USD)
  • 5.4.1. Fraud Detection
  • 5.4.2. Customer Experience Management
  • 5.4.3. Predictive Analytics
  • 5.4.4. Autonomous Vehicles
  • 5.4.5. Intelligent Virtual Assistants
  • 5.4.6. Others (Cost Optimization, etc.)
• 5.5. By End-Use (USD)
  • 5.5.1. IT & Telecom
  • 5.5.2. BFSI
  • 5.5.3. Retail
  • 5.5.4. Automotive
  • 5.5.5. Healthcare
  • 5.5.6. Others (Media and Entertainment, etc.)
• 5.6. By Region (USD)
  • 5.6.1. North America
  • 5.6.2. South America
  • 5.6.3. Europe
  • 5.6.4. Middle East & Africa
  • 5.6.5. Asia Pacific

6. North America AI Accelerator Market Size Estimates and Forecasts, By Segments, 2021-2034

• 6.1. Key Findings
• 6.2. By Type (USD)
  • 6.2.1. Graphics Processing Units (GPUs)
  • 6.2.2. Tensor Processing Units (TPUs)
  • 6.2.3. Central Processing Units (CPUs)
  • 6.2.4. Application-Specific Integrated Circuits (ASICs)
  • 6.2.5. Field-Programmable Gate Arrays (FPGAs)
• 6.3. By Technology (USD)
  • 6.3.1. Cloud-Based
  • 6.3.2. Edge AI
• 6.4. By Application (USD)
  • 6.4.1. Fraud Detection
  • 6.4.2. Customer Experience Management
  • 6.4.3. Predictive Analytics
  • 6.4.4. Autonomous Vehicles
  • 6.4.5. Intelligent Virtual Assistants
  • 6.4.6. Others (Cost Optimization, etc.)
• 6.5. By End-Use (USD)
  • 6.5.1. IT & Telecom
  • 6.5.2. BFSI
  • 6.5.3. Retail
  • 6.5.4. Automotive
  • 6.5.5. Healthcare
  • 6.5.6. Others (Media and Entertainment, etc.)
• 6.6. By Country (USD)
  • 6.6.1. U.S.
    • 6.6.1.1. By End-Use
  • 6.6.2. Canada
    • 6.6.2.1. By End-Use
  • 6.6.3. Mexico
    • 6.6.3.1. By End-Use

7. South America AI Accelerator Market Size Estimates and Forecasts, By Segments, 2021-2034

• 7.1. Key Findings
• 7.2. By Type (USD)
  • 7.2.1. Graphics Processing Units (GPUs)
  • 7.2.2. Tensor Processing Units (TPUs)
  • 7.2.3. Central Processing Units (CPUs)
  • 7.2.4. Application-Specific Integrated Circuits (ASICs)
  • 7.2.5. Field-Programmable Gate Arrays (FPGAs)
• 7.3. By Technology (USD)
  • 7.3.1. Cloud-Based
  • 7.3.2. Edge AI
• 7.4. By Application (USD)
  • 7.4.1. Fraud Detection
  • 7.4.2. Customer Experience Management
  • 7.4.3. Predictive Analytics
  • 7.4.4. Autonomous Vehicles
  • 7.4.5. Intelligent Virtual Assistants
  • 7.4.6. Others (Cost Optimization, etc.)
• 7.5. By End-Use (USD)
  • 7.5.1. IT & Telecom
  • 7.5.2. BFSI
  • 7.5.3. Retail
  • 7.5.4. Automotive
  • 7.5.5. Healthcare
  • 7.5.6. Others (Media and Entertainment, etc.)
• 7.6. By Country (USD)
  • 7.6.1. Brazil
    • 7.6.1.1. By End-Use
  • 7.6.2. Argentina
    • 7.6.2.1. By End-Use
  • 7.6.3. Rest of South America

8. Europe AI Accelerator Market Size Estimates and Forecasts, By Segments, 2021-2034

• 8.1. Key Findings
• 8.2. By Type (USD)
  • 8.2.1. Graphics Processing Units (GPUs)
  • 8.2.2. Tensor Processing Units (TPUs)
  • 8.2.3. Central Processing Units (CPUs)
  • 8.2.4. Application-Specific Integrated Circuits (ASICs)
  • 8.2.5. Field-Programmable Gate Arrays (FPGAs)
• 8.3. By Technology (USD)
  • 8.3.1. Cloud-Based
  • 8.3.2. Edge AI
• 8.4. By Application (USD)
  • 8.4.1. Fraud Detection
  • 8.4.2. Customer Experience Management
  • 8.4.3. Predictive Analytics
  • 8.4.4. Autonomous Vehicles
  • 8.4.5. Intelligent Virtual Assistants
  • 8.4.6. Others (Cost Optimization, etc.)
• 8.5. By End-Use (USD)
  • 8.5.1. IT & Telecom
  • 8.5.2. BFSI
  • 8.5.3. Retail
  • 8.5.4. Automotive
  • 8.5.5. Healthcare
  • 8.5.6. Others (Media and Entertainment, etc.)
• 8.6. By Country (USD)
  • 8.6.1. U.K.
    • 8.6.1.1. By End-Use
  • 8.6.2. Germany
    • 8.6.2.1. By End-Use
  • 8.6.3. France
    • 8.6.3.1. By End-Use
  • 8.6.4. Italy
    • 8.6.4.1. By End-Use
  • 8.6.5. Spain
    • 8.6.5.1. By End-Use
  • 8.6.6. Russia
    • 8.6.6.1. By End-Use
  • 8.6.7. Benelux
    • 8.6.7.1. By End-Use
  • 8.6.8. Nordics
    • 8.6.8.1. By End-Use
  • 8.6.9. Rest of Europe

9. Middle East & Africa AI Accelerator Market Size Estimates and Forecasts, By Segments, 2021-2034

• 9.1. Key Findings
• 9.2. By Type (USD)
  • 9.2.1. Graphics Processing Units (GPUs)
  • 9.2.2. Tensor Processing Units (TPUs)
  • 9.2.3. Central Processing Units (CPUs)
  • 9.2.4. Application-Specific Integrated Circuits (ASICs)
  • 9.2.5. Field-Programmable Gate Arrays (FPGAs)
• 9.3. By Technology (USD)
  • 9.3.1. Cloud-Based
  • 9.3.2. Edge AI
• 9.4. By Application (USD)
  • 9.4.1. Fraud Detection
  • 9.4.2. Customer Experience Management
  • 9.4.3. Predictive Analytics
  • 9.4.4. Autonomous Vehicles
  • 9.4.5. Intelligent Virtual Assistants
  • 9.4.6. Others (Cost Optimization, etc.)
• 9.5. By End-Use (USD)
  • 9.5.1. IT & Telecom
  • 9.5.2. BFSI
  • 9.5.3. Retail
  • 9.5.4. Automotive
  • 9.5.5. Healthcare
  • 9.5.6. Others (Media and Entertainment, etc.)
• 9.6. By Country (USD)
  • 9.6.1. Turkey
    • 9.6.1.1. By End-Use
  • 9.6.2. Israel
    • 9.6.2.1. By End-Use
  • 9.6.3. GCC
    • 9.6.3.1. By End-Use
  • 9.6.4. North Africa
    • 9.6.4.1. By End-Use
  • 9.6.5. South Africa
    • 9.6.5.1. By End-Use
  • 9.6.6. Rest of Middle East & Africa

10. Asia Pacific AI Accelerator Market Size Estimates and Forecasts, By Segments, 2021-2034

• 10.1. Key Findings
• 10.2. By Type (USD)
  • 10.2.1. Graphics Processing Units (GPUs)
  • 10.2.2. Tensor Processing Units (TPUs)
  • 10.2.3. Central Processing Units (CPUs)
  • 10.2.4. Application-Specific Integrated Circuits (ASICs)
  • 10.2.5. Field-Programmable Gate Arrays (FPGAs)
• 10.3. By Technology (USD)
  • 10.3.1. Cloud-Based
  • 10.3.2. Edge AI
• 10.4. By Application (USD)
  • 10.4.1. Fraud Detection
  • 10.4.2. Customer Experience Management
  • 10.4.3. Predictive Analytics
  • 10.4.4. Autonomous Vehicles
  • 10.4.5. Intelligent Virtual Assistants
  • 10.4.6. Others (Cost Optimization, etc.)
• 10.5. By End-Use (USD)
  • 10.5.1. IT & Telecom
  • 10.5.2. BFSI
  • 10.5.3. Retail
  • 10.5.4. Automotive
  • 10.5.5. Healthcare
  • 10.5.6. Others (Media and Entertainment, etc.)
• 10.6. By Country (USD)
  • 10.6.1. China
    • 10.6.1.1. By End-Use
  • 10.6.2. Japan
    • 10.6.2.1. By End-Use
  • 10.6.3. India
    • 10.6.3.1. By End-Use
  • 10.6.4. South Korea
    • 10.6.4.1. By End-Use
  • 10.6.5. ASEAN
    • 10.6.5.1. By End-Use
  • 10.6.6. Oceania
    • 10.6.6.1. By End-Use
  • 10.6.7. Rest of Asia Pacific

11. Company Profiles for Top 10 Players (Based on data availability in public domain and/or on paid databases)

• 11.1. Nvidia Corporation
  • 11.1.1. Overview
    • 11.1.1.1. Key Management
    • 11.1.1.2. Headquarters
    • 11.1.1.3. Offerings/Business Segments
  • 11.1.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.1.2.1. Employee Size
    • 11.1.2.2. Past and Current Revenue
    • 11.1.2.3. Geographical Share
    • 11.1.2.4. Business Segment Share
    • 11.1.2.5. Recent Developments
• 11.2. AMD (Advanced Micro Devices)
  • 11.2.1. Overview
    • 11.2.1.1. Key Management
    • 11.2.1.2. Headquarters
    • 11.2.1.3. Offerings/Business Segments
  • 11.2.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.2.2.1. Employee Size
    • 11.2.2.2. Past and Current Revenue
    • 11.2.2.3. Geographical Share
    • 11.2.2.4. Business Segment Share
    • 11.2.2.5. Recent Developments
• 11.3. Intel Corporation
  • 11.3.1. Overview
    • 11.3.1.1. Key Management
    • 11.3.1.2. Headquarters
    • 11.3.1.3. Offerings/Business Segments
  • 11.3.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.3.2.1. Employee Size
    • 11.3.2.2. Past and Current Revenue
    • 11.3.2.3. Geographical Share
    • 11.3.2.4. Business Segment Share
    • 11.3.2.5. Recent Developments
• 11.4. TSMC (Taiwan Semiconductor Manufacturing Co.)
  • 11.4.1. Overview
    • 11.4.1.1. Key Management
    • 11.4.1.2. Headquarters
    • 11.4.1.3. Offerings/Business Segments
  • 11.4.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.4.2.1. Employee Size
    • 11.4.2.2. Past and Current Revenue
    • 11.4.2.3. Geographical Share
    • 11.4.2.4. Business Segment Share
    • 11.4.2.5. Recent Developments
• 11.5. Samsung Electronics
  • 11.5.1. Overview
    • 11.5.1.1. Key Management
    • 11.5.1.2. Headquarters
    • 11.5.1.3. Offerings/Business Segments
  • 11.5.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.5.2.1. Employee Size
    • 11.5.2.2. Past and Current Revenue
    • 11.5.2.3. Geographical Share
    • 11.5.2.4. Business Segment Share
    • 11.5.2.5. Recent Developments
• 11.6. Apple Inc.
  • 11.6.1. Overview
    • 11.6.1.1. Key Management
    • 11.6.1.2. Headquarters
    • 11.6.1.3. Offerings/Business Segments
  • 11.6.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.6.2.1. Employee Size
    • 11.6.2.2. Past and Current Revenue
    • 11.6.2.3. Geographical Share
    • 11.6.2.4. Business Segment Share
    • 11.6.2.5. Recent Developments
• 11.7. Google LLC
  • 11.7.1. Overview
    • 11.7.1.1. Key Management
    • 11.7.1.2. Headquarters
    • 11.7.1.3. Offerings/Business Segments
  • 11.7.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.7.2.1. Employee Size
    • 11.7.2.2. Past and Current Revenue
    • 11.7.2.3. Geographical Share
    • 11.7.2.4. Business Segment Share
    • 11.7.2.5. Recent Developments
• 11.8. Meta
  • 11.8.1. Overview
    • 11.8.1.1. Key Management
    • 11.8.1.2. Headquarters
    • 11.8.1.3. Offerings/Business Segments
  • 11.8.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.8.2.1. Employee Size
    • 11.8.2.2. Past and Current Revenue
    • 11.8.2.3. Geographical Share
    • 11.8.2.4. Business Segment Share
    • 11.8.2.5. Recent Developments
• 11.9. Qualcomm Incorporated
  • 11.9.1. Overview
    • 11.9.1.1. Key Management
    • 11.9.1.2. Headquarters
    • 11.9.1.3. Offerings/Business Segments
  • 11.9.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.9.2.1. Employee Size
    • 11.9.2.2. Past and Current Revenue
    • 11.9.2.3. Geographical Share
    • 11.9.2.4. Business Segment Share
    • 11.9.2.5. Recent Developments
• 11.10. IBM Corporation
  • 11.10.1. Overview
    • 11.10.1.1. Key Management
    • 11.10.1.2. Headquarters
    • 11.10.1.3. Offerings/Business Segments
  • 11.10.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.10.2.1. Employee Size
    • 11.10.2.2. Past and Current Revenue
    • 11.10.2.3. Geographical Share
    • 11.10.2.4. Business Segment Share
    • 11.10.2.5. Recent Developments

12. Key Takeaways