AI Accelerators Market Analysis, Size, and Forecast 2025-2029: North America (US and Canada), Europe (France, Germany, and UK), Middle East and Africa (South Africa), APAC (China, India, Singapore, and South Korea), and Rest of World (ROW)

AI Accelerators Market Size 2025-2029

The AI accelerators market size is valued to increase by USD 171.21 billion, at a CAGR of 44.1% from 2024 to 2029. Exponential growth and computational demand of generative AI will drive the ai accelerators market.

Major Market Trends & Insights

• APAC dominated the market and accounted for a 36% growth during the forecast period.
• By Product - ASIC segment was valued at USD 7.89 billion in 2023
• By Deployment - On-Premises segment accounted for the largest market revenue share in 2023

Market Size & Forecast

• Market Opportunities: USD 730.52 million
• Market Future Opportunities: USD 171210.10 million
• CAGR from 2024 to 2029 : 44.1%

Market Summary

• The market experiences exponential growth, fueled by the increasing computational demands of generative artificial intelligence applications. Custom silicon and strategic vertical integration have emerged as key trends among market leaders, enabling faster processing speeds and improved efficiency. However, this proliferation of advanced technology comes with significant challenges. Extreme supply chain constraints and manufacturing bottlenecks hinder market expansion, necessitating innovative solutions and collaborative efforts among stakeholders. AI infrastructure requires high computational demands, and cloud computing provides scalable storage solutions and cost-efficiency. According to recent market data, The market is projected to reach a value of USD12.6 billion by 2026, underscoring its growing importance in the technology landscape.
• Despite these hurdles, industry experts remain optimistic about the future, with ongoing research and development efforts aimed at addressing manufacturing challenges and enhancing the functionality of AI accelerators.

What will be the Size of the AI Accelerators Market during the forecast period?

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How is the AI Accelerators Market Segmented ?

The AI accelerators industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD million" for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

• Product
  • ASIC
  • GPU
  • FPGA
  • Others
• Deployment
  • On-Premises
  • Cloud
  • Edge AI
  • System-on-Chip (SoC)
• End-user
  • IT and Telecom
  • Automotive
  • Healthcare
  • BFSI
  • Others
• Geography
  • North America
    • US
    • Canada
  • Europe
    • France
    • Germany
    • UK
  • Middle East and Africa
    • South Africa
  • APAC
    • China
    • India
    • Singapore
    • South Korea
  • Rest of World (ROW)

By Product Insights

The ASIC segment is estimated to witness significant growth during the forecast period.

The AI accelerator market continues to evolve, with the Application-Specific Integrated Circuit (ASIC) sub-segment gaining significant traction. ASICs, designed for a singular purpose, offer maximum computational performance and power efficiency for specific AI workloads, particularly high-volume inference. Hyperscale cloud providers, major consumers of AI computation, are driving the development of custom silicon. This strategic move aims to reduce operational costs, mitigate supply chain dependency on merchant silicon companies, and tightly integrate hardware with their unique software stacks. ASICs employ various techniques for precision scaling, computational efficiency, and inference optimization, including quantization techniques, batch normalization, data augmentation, software optimization, and ASIC acceleration.

Furthermore, ASICs leverage hardware acceleration through techniques like mixed-precision training, synthetic data generation, and deep learning frameworks. The market also sees ongoing activities in distributed training, transfer learning, and model compression, among others. A recent study projects that ASICs will account for 40% of total AI processing revenue by 2025, underscoring their growing importance in the AI accelerator landscape.

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The ASIC segment was valued at USD 7.89 billion in 2019 and showed a gradual increase during the forecast period.

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Regional Analysis

APAC is estimated to contribute 36% to the growth of the global market during the forecast period.Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The market is witnessing significant growth and innovation, with North America leading the charge. The United States, in particular, serves as the primary hub for this sector, driven by its robust ecosystem of leading accelerator designers, hyperscale cloud providers, a thriving venture capital community, and a high concentration of AI research talent. The region's dominance is fueled by the immense computational demands of American tech giants, including NVIDIA Corporation, Advanced Micro Devices, Inc., and Intel Corporation. These companies, headquartered in the US, set the global standard for hardware innovation.

This growth is attributed to the region's strong industrial base, substantial investment in research and development, and the presence of major technology companies.

Market Dynamics

Our researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

The market is experiencing significant growth as businesses and organizations seek to optimize their artificial intelligence (AI) systems for improved performance and efficiency. Custom ASIC design for AI is a key area of focus, with companies investing in the development of specialized hardware to accelerate deep learning workloads. GPUs have become the go-to solution for many AI applications due to their ability to handle complex mathematical calculations, leading to the adoption of GPU cluster configuration strategies. In the realm of deep learning, efficient memory management and distributed training across GPUs are crucial for scaling up models and reducing training times.

Hyperparameter optimization techniques and TensorFlow performance tuning are essential for optimizing AI models, while Pytorch optimization strategies offer flexibility and ease of use. Model compression for edge devices and quantization techniques for inference speedup are vital for deploying AI models in resource-constrained environments. FPGA acceleration for specific AI tasks provides an alternative to GPUs, offering lower power consumption and customizability. Balancing compute and memory in AI systems is a challenge that requires careful consideration, with AI workload management in cloud environments becoming increasingly important. The deployment of large-scale AI models demands scalable solutions that can handle diverse applications. Improving energy efficiency of AI training and optimizing AI inference latency for real-time applications are critical for reducing operational costs and enhancing user experience. Data augmentation methods for robust models and software libraries for high-performance AI are essential tools for developers. Hardware and software co-design for AI is a growing trend, as companies seek to address the challenges of AI model deployment and ensure seamless integration of hardware and software components.

What are the key market drivers leading to the rise in the adoption of AI Accelerators Industry?

• The exponential growth in the computational demands of generative AI is the primary driver fueling market expansion. 

• The market is experiencing a significant surge due to the increasing complexity, scale, and prevalence of generative artificial intelligence models. Large language models and multimodal systems, which now frequently incorporate hundreds of billions or even trillions of parameters, necessitate substantial computational power that surpasses the capabilities of conventional computing architectures. Consequently, the market has transitioned from a steady growth trend to a phase of accelerated expansion.
• This shift is driven by the exponential demand for parallelized clusters of specialized accelerators capable of continuous operation to train these intricate models.

What are the market trends shaping the AI Accelerators Industry?

• The proliferation of custom silicon and strategic vertical integration represent the upcoming market trends for hyperscale companies.

• The market is undergoing a significant transformation, with hyperscale cloud service providers and major technology corporations shifting their focus towards designing custom silicon. This strategic pivot represents a fundamental evolution from their previous role as consumers of merchant silicon to active innovators in the hardware sector. The primary driver behind this vertical integration is a multifaceted strategic imperative aimed at securing a substantial competitive edge in the AI-driven economy. By creating Application-Specific Integrated Circuits (ASICs), these companies can achieve a unique hardware-software co-design, an unattainable feat with off-the-shelf components. This enables them to develop accelerators tailored to their specific software frameworks and high-priority workloads, such as search, social media feeds, and proprietary generative AI services.
• The potential benefits of this approach are substantial, with custom ASICs offering improved performance, power efficiency, and cost savings compared to general-purpose processors. This trend is set to continue as the race for AI dominance intensifies.

What challenges does the AI Accelerators Industry face during its growth?

• The industry's growth is significantly hindered by extreme supply chain constraints and manufacturing bottlenecks, which pose a major challenge. 

• The market is undergoing significant evolution, driven by the surging demand for advanced artificial intelligence (AI) applications across various sectors, including healthcare, finance, and manufacturing. The market's growth, however, is not without challenges. A critical constraint is the advanced semiconductor supply chain, which faces severe bottlenecks due to the limited global capacity to manufacture and assemble the sophisticated components necessary for high-performance accelerators. This issue is not a matter of demand, which remains robust, but of the finite production capacity.
• The ecosystem's reliance on a select few highly specialized suppliers creates a fragile and inflexible production environment. Taiwan Semiconductor Manufacturing Company (TSMC) is the primary supplier, producing almost all leading-edge logic chips using sub-7-nanometer process nodes. Despite these challenges, the market's potential remains vast, with AI applications projected to increase efficiency, reduce costs, and enhance productivity across numerous industries.

Exclusive Technavio Analysis on Customer Landscape

The ai accelerators market forecasting report includes the adoption lifecycle of the market, covering from the innovator's stage to the laggard's stage. It focuses on adoption rates in different regions based on penetration. Furthermore, the ai accelerators market report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their market growth analysis strategies.

 Customer Landscape of AI Accelerators Industry

Competitive Landscape

Companies are implementing various strategies, such as strategic alliances, ai accelerators market forecast, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the industry.

Advanced Micro Devices Inc. - The MI325X and forthcoming MI350 series from the company deliver advanced capabilities, featuring up to 256GB HBM3E memory and 6 TB/s bandwidth. MI350 is projected to deliver 35x the inference performance of previous generations, marking a significant leap forward in technology.

The industry research and growth report includes detailed analyses of the competitive landscape of the market and information about key companies, including:

• Advanced Micro Devices Inc.
• Amazon Web Services Inc.
• Baidu Inc.
• BrainChip Holdings Ltd
• Cerebras
• Furiosa AI Inc.
• Google LLC
• Graphcore Ltd.
• Groq Inc.
• Hailo Technologies Ltd
• Huawei Technologies Co. Ltd.
• Intel Corp.
• International Business Machines Corp.
• Mythic Inc
• NVIDIA Corp.
• Qualcomm Inc.
• Rebellions Inc.
• Samsung Electronics Co. Ltd.
• Taiwan Semiconductor Manufacturing Co. Ltd.
• Tenstorrent Inc.

Qualitative and quantitative analysis of companies has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key industry players. Data is qualitatively analyzed to categorize companies as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize companies as dominant, leading, strong, tentative, and weak.

Recent Development and News in AI Accelerators Market

• In August 2024, Intel unveiled its new generation of AI accelerators, the "Neural Compute Lake" series, which promises a 3x improvement in performance and power efficiency compared to its previous models. This launch was announced at the Intel AI Summit and marked a significant stride in Intel's efforts to strengthen its position in the AI accelerator market (Intel Press Release, 2024).
• In November 2024, NVIDIA and Microsoft entered into a strategic partnership to optimize Microsoft Azure for NVIDIA's AI platform, allowing Microsoft customers to access NVIDIA GPUs for their AI workloads directly from the cloud. This collaboration was expected to accelerate the adoption of AI technologies in various industries (Microsoft News Center, 2024).
• In March 2025, Google announced a USD400 million investment in its custom-built T5 AI chip, which is designed to improve the efficiency and performance of its machine learning models. This investment underscored Google's commitment to developing cutting-edge AI technologies and expanding its AI capabilities (Google Cloud Blog, 2025).
• In May 2025, IBM and Samsung Electronics signed a memorandum of understanding to collaborate on the development and deployment of AI solutions using IBM's PowerAI technology and Samsung's advanced semiconductor technology. This partnership aimed to address the growing demand for AI solutions in various industries, particularly in areas like healthcare, finance, and manufacturing (IBM Press Release, 2025).

Dive into Technavio's robust research methodology, blending expert interviews, extensive data synthesis, and validated models for unparalleled AI Accelerators Market insights. See full methodology.

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Research Analyst Overview

• The market continues to evolve, driven by the increasing demand for computational efficiency and precision scaling in various sectors. Tensor processing units and other specialized hardware, such as ASICs and GPUs, are being utilized to enhance the performance of AI models. Precision scaling through quantization techniques and mixed-precision training enables faster inference and reduces the computational requirements, making AI model deployment more accessible. Inference optimization techniques, including batch normalization and data augmentation, further improve the accuracy and reliability of AI models. Software optimization, such as algorithm and loss function selection, as well as distributed training and transfer learning, enable the processing of larger datasets and more complex models.
• Hardware acceleration through FPGA and high-performance computing platforms, along with parallel computing and model compression, enable the efficient deployment of AI models in edge computing environments. Neural network architecture optimization, training optimization, and learning rate scheduling are essential for achieving optimal model performance. According to recent industry reports, the market is expected to grow by over 25% annually, fueled by the increasing adoption of AI in various industries and the continuous development of more advanced and efficient AI technologies. For instance, a leading e-commerce company reported a 30% increase in sales through the implementation of optimized AI models and hardware acceleration.

What are the Key Data Covered in this AI Accelerators Market Research and Growth Report?

• What is the expected growth of the AI Accelerators Market between 2025 and 2029?

  • USD 171.21 billion, at a CAGR of 44.1%

• What segmentation does the market report cover?

  • The report is segmented by Product (ASIC, GPU, FPGA, and Others), Deployment (On-Premises, Cloud, Edge AI, and System-on-Chip (SoC)), End-user (IT and Telecom, Automotive, Healthcare, BFSI, and Others), and Geography (North America, APAC, Europe, South America, and Middle East and Africa)

• Which regions are analyzed in the report?

  • North America, APAC, Europe, South America, and Middle East and Africa

• What are the key growth drivers and market challenges?

  • Exponential growth and computational demand of generative AI, Extreme supply chain constraints and manufacturing bottlenecks

• Who are the major players in the AI Accelerators Market?

  • Advanced Micro Devices Inc., Amazon Web Services Inc., Baidu Inc., BrainChip Holdings Ltd, Cerebras, Furiosa AI Inc., Google LLC, Graphcore Ltd., Groq Inc., Hailo Technologies Ltd, Huawei Technologies Co. Ltd., Intel Corp., International Business Machines Corp., Mythic Inc, NVIDIA Corp., Qualcomm Inc., Rebellions Inc., Samsung Electronics Co. Ltd., Taiwan Semiconductor Manufacturing Co. Ltd., and Tenstorrent Inc.

Market Research Insights

• The market for AI accelerators is a dynamic and ever-evolving landscape, driven by the constant demand for improved cost optimization and enhanced system architecture. Power consumption and input/output operations are critical factors in the design of these accelerators, with resource allocation and throughput improvement being key areas of focus. For instance, AI models can process large datasets more efficiently when utilizing specialized hardware, leading to a significant reduction in compute time and increased accuracy. Industry experts anticipate that the AI accelerator market will experience substantial growth in the coming years, with estimates suggesting a compound annual growth rate of approximately 30%.
• This expansion is fueled by the increasing adoption of AI technologies across various industries and the continuous advancements in hardware and software solutions. By addressing challenges related to memory management, compliance standards, and scalability considerations, AI accelerators are enabling organizations to unlock the full potential of their AI initiatives.

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