AI Chipsets Market Size, Share, Forecast, & Trends Analysis by Offering (Hardware and Software), Technology (Machine Learning, Natural Language Processing, Context-aware Processing), Vertical (Automotive & Transportation, Consumer Electronics, Healthcare) - Global Forecast to 2031

AI Chipsets Market Size & Forecast

The AI Chipsets Market is expected to reach $260.2 billion by 2031, at a CAGR of 27.2% from 2024–2031. The growth of the AI chipsets market is driven by the rapid advancements in AI technology, growing demand for edge computing, and the rise of autonomous systems and robotics. Furthermore, the increasing demand for AI-enabled devices and the development of smart robots are expected to offer significant growth opportunities for players operating in the AI chipsets market.

AI Chipsets Market Growth Drivers

Rapid Advancements in AI Technology

Rapid advancements in AI technology are a significant driver behind the growth of the AI chipset market. As AI applications become more complex and widespread, there's a growing need for specialized hardware that can handle the intense computational requirements of AI algorithms. AI chipsets are designed to efficiently perform the matrix operations and neural network computations that power machine learning models. The rapid pace of innovation in semiconductor technology has led to the development of increasingly powerful and efficient AI chipsets. Moreover, advances in AI algorithms and software frameworks also play a crucial role in driving the adoption of AI chipsets. As developers create more sophisticated models and algorithms, there's a growing demand for hardware that can accelerate their execution. In April 2024, Meta Platforms, Inc.,  (U.S) launched the latest version of its custom artificial intelligence chip, the Meta Training and Inference Accelerator(MTIA). The new chip is already being used in Meta’s data centers for AI applications and is expected to be improved to meet the scope of generative AI workloads. In February 2023, South Korean startup Rebellions Inc. launched an artificial intelligence (AI) chip to win government contracts as Seoul seeks a place for local companies in the exploding AI industry.

Growing Demand for Edge Computing

Edge computing involves processing data closer to its source rather than relying solely on centralized data centers or cloud services. This approach reduces latency and enables real-time processing, which is crucial for applications such as autonomous vehicles, industrial automation, and smart cities. AI chipsets are essential for executing complex AI algorithms at the edge, allowing devices to make intelligent decisions locally without relying on distant servers. Edge computing also enhances data privacy and security by keeping sensitive information localized and reducing exposure to potential cyber threats. AI chipsets enable on-device processing of sensitive data, minimizing the need for data to be transmitted over potentially insecure networks. Additionally, by processing data locally, edge devices can adhere to privacy regulations and compliance requirements more effectively. Such factors help to drive the growth of the market.

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AI Chipsets Market Opportunity

Increasing Demand for AI-enabled Devices

AI technology is being integrated into a wide range of devices across various industries, including smartphones, wearables, smart home devices, automotive systems, and industrial machinery, among others. These AI-enabled devices rely on specialized chipsets to perform tasks such as image recognition, natural language processing, autonomous navigation, and predictive analytics. AI capabilities also enhance the functionality and user experience of devices by enabling features such as voice assistants, facial recognition, gesture control, personalized recommendations, and predictive maintenance. As consumers increasingly expect smarter and more intuitive devices, manufacturers are incorporating AI chipsets to deliver these enhanced capabilities.

Moreover, the growing ecosystem of AI software frameworks, development tools, and libraries simplifies the integration of AI capabilities into devices, due to which manufacturers can leverage pre-trained models, software APIs, and developer resources to accelerate the development of AI-enabled products. This expanding ecosystem facilitates the adoption of AI chipsets and fosters innovation in AI-powered devices. Such factors provide lucrative growth opportunities in the development of the market.

Development of Smart Robots

AI chipsets play a crucial role in motion control and actuation systems, allowing robots to execute precise and coordinated movements. These chipsets drive motor controllers, servo drives, and other electromechanical components with high accuracy and responsiveness. By optimizing motion planning and control algorithms, AI chipsets enable robots to perform tasks with skill, agility, and efficiency.

Smart robots require advanced perception and sensing capabilities to understand and interact with their environment effectively. AI chipsets enable robots to process sensor data, such as visual information from cameras, depth data from LiDAR sensors, and spatial information from inertial measurement units (IMUs), in real time. These chipsets power computer vision algorithms, object detection, simultaneous localization and mapping (SLAM), and other AI-driven perception tasks, allowing robots to navigate autonomously and perform complex tasks in dynamic environments.

Moreover, AI chipsets enable smart robots to make intelligent decisions based on their sensory inputs and contextual information. These chipsets implement machine learning algorithms, such as deep reinforcement learning and decision trees, to analyze data, infer patterns, and generate optimal actions. Smart robots can adapt to changing conditions, learn from experience, and optimize their behavior over time, enhancing their autonomy and versatility in various applications. Such factors provide lucrative growth opportunities in the development of the market.

AI Chipsets Market Challenges

High Power Consumption of AI Chipsets

High power consumption is indeed a concern associated with some AI chipsets, particularly those designed for high-performance computing tasks like training deep neural networks. High power consumption in AI chipsets can lead to increased heat dissipation, which may require more sophisticated thermal management solutions to prevent overheating and maintain reliability. AI workloads often require high memory bandwidth to meet the demands of data-intensive computations. Accessing data from memory at high speeds consumes more power, especially in systems with large caches and high-speed interconnects between processing units and memory modules.

Additionally, high-performance AI chipsets typically operate at high clock frequencies and voltage levels to achieve fast computation speeds. However, higher clock frequencies and voltage levels result in increased power consumption, as more energy is required to switch transistors on and off rapidly. Such factors create challenges in the development of the market.

AI Chipsets Market Analysis: Key Findings

By Offering: In 2024, the Hardware Segment to Dominate the AI Chipsets Market

Based on offering, the global AI chipsets market is segmented into hardware and software. Further, the hardware market is segmented into processor, memory, and network. The processor segment is subsegmented into graphics processing units, field-programmable gate arrays, application-specific integrated circuits, central processing units, and digital signal processors. In 2024, the hardware segment is expected to account for the larger share of 76.0% of the global AI chipsets market. In 2024, the graphics processing units segment is expected to account for the largest share of 47.0% of the global AI chipsets processor market. The growth of the AI chipsets hardware market is attributed to the growing integration of AI in various sectors such as healthcare, automotive, retail, and manufacturing is propelling the demand for AI chipsets. These chipsets are essential for processing the large volumes of data required for AI algorithms to function effectively. The proliferation of AI-driven devices such as smartphones, smart speakers, autonomous vehicles, and smart cameras is fueling the demand for AI chipsets. These devices require specialized hardware to deliver AI-powered features and functionalities effectively.

Furthermore, various key players are launching various AI chipsets. For instance:

• In March  2024, NVIDIA Corporation (U.S.) launched its latest generation of AI chips and software designed to power AI models.
• In March  2024, Cerebras Systems Inc. (U.S.) launched a third-generation AI processor. The WSE-3 chip doubles the performance of its predecessor, 56 times larger than the largest GPU, and features 1.2 trillion transistors and 400,000 computing cores, making it the fastest and largest AI chip.

Additionally, the same segment is projected to register the highest CAGR during the forecast period.

By Technology: In 2024, the Machine Learning Segment to Dominate the AI Chipsets Market

Based on technology, the global AI chipsets market is segmented into machine learning, natural language processing, context-aware processing, computer vision, predictive analysis, and other technologies. Further, the machine learning market is segmented into deep learning, supervised learning, unsupervised learning, reinforcement learning, and other machine learning types. In 2024, the machine learning segment is expected to account for the largest share of 53.0% of the global AI chipsets market. Machine learning enables AI chipsets to adapt to changing workloads and environments. Through techniques like dynamic voltage and frequency scaling (DVFS) or adaptive clocking, chipsets can adjust their operating parameters in real time based on workload characteristics, leading to improved performance and power efficiency. Also, machine learning algorithms can be used to detect and mitigate hardware faults in AI chipsets. By analyzing sensor data and performance metrics, machine learning models can identify signs of hardware degradation or failure and take proactive measures to ensure reliability and uptime.

However, the natural language processing segment is projected to register the highest CAGR during the forecast period. Integrating NLP into AI chipsets supports edge computing architectures, where data processing occurs locally on devices rather than in centralized data centers. This reduces reliance on cloud services and minimizes latency, making NLP applications more responsive and efficient. Moreover, AI chipsets with embedded NLP capabilities can operate effectively in diverse environmental conditions, including situations with limited resources or challenging operating environments. This robustness ensures reliable performance across various use cases and deployment scenarios.

By Vertical: In 2024, the Consumer Electronics Segment to Dominate the AI Chipsets Market

Based on vertical, the global AI chipsets market is segmented into automotive & transportation, smart factories, smart cities, smart retail, consumer electronics, healthcare, and other verticals.  In 2024, the consumer electronics segment is expected to account for the largest share of 59.0% of the global AI chipsets market. The growth of this segment is attributed to the proliferation of IoT devices and connected ecosystems that drive the demand for AI chipsets in consumer electronics. These chipsets enable devices to analyze sensor data, communicate with other devices, and make intelligent decisions autonomously, contributing to the growth of smart homes, wearables, and other connected solutions. AI chipsets enable consumer electronics products to offer personalized and immersive user experiences, and by analyzing user behavior, preferences, and contextual data, these chipsets can tailor product functionalities, recommendations, and interactions to individual users, enhancing satisfaction and engagement.

However, the healthcare segment is projected to register the highest CAGR during the forecast period. AI chipsets support the advancement of precision medicine and genomics by analyzing vast genomic datasets and identifying genetic variations associated with diseases and treatment responses. These chipsets enable healthcare providers to tailor medical treatments and interventions to individual patients based on their genetic profiles, leading to more personalized and effective care. Moreover, AI chipsets accelerate the drug discovery and development process by analyzing molecular structures, predicting drug interactions, and identifying potential drug candidates. These chipsets enable pharmaceutical companies to expedite the drug discovery pipeline, reduce development costs, and bring new therapies to market more quickly, addressing unmet medical needs.

Geographical Analysis

In 2024, North America is expected to account for the largest share of 46.0% of the global AI chipsets market. In the U.S., there are various semiconductor companies, research institutions, and technology giants present. These companies have established themselves as pioneers in AI chip development and have made significant contributions to the field. Their expertise and research initiatives have propelled the growth of the market in North America. Moreover, companies in North America invest heavily in research and development (R&D) to maintain their competitive edge in the global AI chipsets market. These investments fuel innovation in semiconductor design, manufacturing processes, and AI algorithms, leading to the development of more advanced and efficient chipsets.

However, the market in Asia-Pacific is projected to register the highest CAGR of 30.0% during the forecast period. The Asia-Pacific region has a large and diverse market with increasing demand for AI-powered applications in sectors such as healthcare, automotive, manufacturing, finance, retail, and consumer electronics. Asia-Pacific region has a vibrant startup ecosystem with a growing number of AI startups specializing in chip design, semiconductor manufacturing, and AI applications. These startups drive innovation, competition, and collaboration in the AI chipsets market, contributing to market growth.

Moreover, various state & regional governments and private enterprises in the Asia-Pacific region are investing heavily in AI research, development, and infrastructure. Initiatives such as China's "Made in China 2025", India’s “India AI Mission,” and Japan's "Society 5.0" aim to accelerate the adoption of AI technologies, including AI chipsets, across various industries.

AI Chipsets Market: Key Companies

The report offers a competitive analysis based on an extensive assessment of the product portfolios and geographic presence of leading market players and the key growth strategies adopted by them over the past 3–4 years. Some of the key players operating in the AI chipsets market are Advanced Micro Devices, Inc. (U.S.), Amazon.com, Inc. (U.S.), Baidu, Inc. (China), Broadcom Inc. (U.S.), Google LLC (U.S.), International Business Machines Corporation (U.S.), MediaTek Inc. (Taiwan), Intel Corporation (U.S.), Micron Technology, Inc. (U.S.), Microsoft Corporation (U.S.), NVIDIA Corporation (U.S.), QUALCOMM Incorporated (U.S.), Samsung Securities Co., Ltd. (South Korea), Toshiba Corporation (Japan), and SoftBank Group Corp. (Japan).

AI Chipsets Industry Overview: Latest Developments from Key Industry Players

• In April 2024, Intel Corporation (U.S.) launched its latest AI hardware, the Gaudi 3 chip. The launch marks a significant move in Intel’s battle against Nvidia’s dominance in the semiconductor industry, especially in AI. This announcement comes amidst the increasing demand for AI chips while tech giants are seeking alternatives to address the scarcity in supply.

• In February 2024, the Japanese government funded a range of projects, from research to advanced chip manufacturing, making a USD 67 billion bid to reclaim a central role in the semiconductor industry. The Japanese government backed research group developing semiconductors will partner with US startup Tenstorrent Inc. (U.S.) on the design of its first advanced AI chip.

• In November 2023, Microsoft (U.S.) launched its custom AI chip and CPU for its Azure cloud services. The company announced that these chips will enable it to train large language models and run cloud AI workloads more efficiently and cost-effectively.

AI Chipsets Market Research Summary:

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