Market Size (2017)
2017
$3.64B
Vertical: SEMIBase Year: 20179 Sections
Market Size (2017)
2017
$3.64B
Projected (2023)
2023
$16.66B
CAGR (2017–2023)
28.8%
28.8%Key Players
108+
This report covers AI Chipset Market with forecasts from 2017 to 2023. 108 key companies are profiled.
The AI Chipset Market market is projected to grow at a CAGR of 28.8% from 2017 to 2023.
Historical performance and future projections (2020–2030, USD Billion)
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View Subscription PlansArtificial intelligence (AI) chipsets are silicon-based chips powered with the AI technologies, such as machine learning, deep learning, natural language processing, and neural network processing. These chipsets are designed such that they consume low power and offer high computing capabilities to smart devices, such as smartphones, laptops, and smart wearables. These chipsets increase the operational performance of the device with advanced augment reality (AR), virtual reality (VR), and analytical functions and enhance the user experience.
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View Subscription PlansThis report applies a rigorous multi-stage research process combining primary interviews, secondary data sources, and bottom-up market modelling to ensure accuracy and completeness across all segments and geographies.
Base Year
2017
Historical Period
2017 – 2017
Forecast Period
2017 – 2023
Primary Interviews
150+
Historical data (2017–2017) and forecast period (2017–2023)
Our research process spans primary interviews with industry stakeholders combined with comprehensive secondary data analysis, validated through triangulation across multiple independent sources.
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View Subscription PlansMarket estimates by geography (2023)
InsightNorth America leads with $6.83B by 2023, while Asia Pacific is projected to grow fastest at a 30.8% CAGR.
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View Subscription Plans| REGION | 2017 | 2017 | 2023 | CAGR | SHARE |
|---|---|---|---|---|---|
| Asia Pacific | $1.18B | $2.24B | $5.91B | 30.8% | 35% |
| Rest of the World | $117.10M | $189.60M | $427.40M | 24.1% | 3% |
| Europe | $889.10M | $1.49B | $3.48B | 25.6% | 21% |
| North America | $1.46B | $2.68B | $6.83B | 29.4% | 41% |
| Total | $3.64B | $6.60B | $16.66B | 28.8% | 100% |
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View Subscription PlansTotal Market Size
$16.66B
| APPLICATION | REVENUE ($B) | GROWTH RATE | MARKET PENETRATION |
|---|---|---|---|
| Hardware | $13.87B | 28.8% | 89% |
| Software | $2.79B | 28.8% | 89% |
* Revenue projections based on 2025 estimates. Growth rates represent CAGR 2024–2030. Market penetration indicates current adoption rate within addressable market segments.
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Analytical insights on AI Chipset Market covering market dynamics, competitive landscape, and strategic outlook.
The AI Chipset Market market is projected to reach $16.66B by 2023, growing at 28.8% CAGR. The Hardware segment holds the largest share.
AI is making its way into nearly every application including surgery, medical diagnoses, smart homes and gadgets, criminal identification, water quality monitoring, self-driving cars, drug discovery, and image processing. AI applications require compatible hardware and software components with high computational power and low energy consumption. AI chipsets such as GPUs, FPGAs, and ASICs provide high levels of computing power to enable the operation of applications on various devices. With the advent and demand for AI applications, AI chipset manufacturers are introducing new AI processors. On 9 August 2016, Intel Corporation acquired Nervana Systems, an artificial intelligence software provider, to enhance its deep learning portfolio of cloud services. Post this acquisition, on 6 December 2017, Intel Corporation announced the launch of the Intel Nervana neural network processor (NNP) architecture allowing developers to easily test and deploy AI models. With NNP, designers are able to quickly iterate various neural networks with large datasets. It also allows software the flexibility to manage data locally, reducing data movement to and from external memory, which further saves power. The training of deep learning networks involves the movement of data which is simplified by the Nervana Engine chip that utilizes new memory technology—high bandwidth memory (HBM) offering 32 GB of on-chip storage and access speeds of up to 8 TB/s. Additionally, the Nervana NNP does not come with a hierarchy of cache memories and the on-chip memory management is performed by the software, enabling, the faster training time for deep learning models. The Intel Nervana NNP facilitates bi-directional data transfer and large network computations on a single chip with less power consumption per computation.
AI chipsets are also used in smartphones to provide capabilities such as image stabilization and performance improvement. For instance, Apple Inc. launched augmented reality and facial recognition features in its iPhone X series using the A11 Bionic chip. Such applications across various industries are driving the growth of the global artificial intelligence (AI) chipset market.
Edge computing is used to make critical decisions closer to the source data while AI is used to create intelligent machines. Both have great potential in the development of IoT systems and various other applications. The integration of AI with edge computing can find application in autonomous vehicles and predictive maintenance to improve the output of IoT systems. Microsoft Corporation and Spektacom are developing a system to gain insight into the batting styles of different batsmen during a cricket match. This product uses IoT edge devices and AI-powered analytics to offer the required data. Such integration of AI with edge computing provides lucrative opportunities for the players in the global artificial intelligence (AI) chipset market.
The demand for AI is growing day-by-day due to its advantages such as improved efficiency and cost reduction. AI applications require AI chipsets to optimal functioning. However, the designing and manufacturing processes for AI chipsets require a high level of skilled expertise as they are highly complex. There is a distinct lack of technical experts for both software and hardware development in the field. According to Tencent, there are just around 300,000 AI practitioners and researchers globally while the demand for AI skilled human resources is in the millions. This hampers the entry of new players, thereby, restraining the growth of the global artificial intelligence (AI) chipset market.
The other issues faced by the manufacturers of AI chipsets are product compatibility and acceptability. Start-ups in the market are especially affected by the lack of standards for the production and distribution of AI chipsets. Customer adoption also suffers as they prefer products that adhere to globally accepted standards. This lack of standards is expected to hamper the growth of the market to an extent.
Recent advancements in AI systems such as face and speech recognition utilize neural networks that consist of extremely dense and interconnected meshes of processors for the high volumes of information that the system learns from the training data sets. These neural networks are large, complex, and require high computational power. AI chipsets provide the necessary computational power and hardware complexity for these neural networks which are energy-intensive. There have been increasing investments by various market players such as Google Inc., Microsoft Corporation, and IBM Corporation in the development of processor architecture to build cost-effective and power-efficient AI processors. These processors are still in the development phase due to which the high-power consumption of AI chipsets acts a challenge.
Near-term growth will likely concentrate in modular bioreactor lines and closed-system media workflows that shorten validation cycles while preserving batch traceability.
Partnerships between CDMOs and instrumentation vendors should accelerate standard datasets for comparability across sites, improving forecasting models used in capacity planning.
Longer horizon, organoid and microphysiological adoption may reshape segment mix; teams that invest early in assay interoperability and cloud QC hooks are better positioned to capture upside without fragmenting their analytics stack.
Profiles of 108 companies operating in the AI Chipset Market market, including revenue, employee count, and market positioning where available.
Showing 108 of 108 companies
Huawei Technologies Co. Ltd.
Company Headquarters: China Founded: 1987 Workforce: ~180,000 Company Overview: Huawei Technologies Co. Ltd (Huawei) is one of the leading providers of global information and communications technology (ICT) solutions. The company offers competitive solutions, Components, and services to telecom service providers, enterprises, and consumers. It operates through four business divisions — carrier business, enterprise business, consumer business, and Huawei cloud. The carrier segment covers Components and services in 5G networks, NB-IoT, and all cloud networks covering NFV and SDN contracts. Additionally, the carrier business offers testing for 5G and all-cloud networks and digital operation & maintenance (O&M) systems for data centers. The enterprise segment offers various solutions for the cloud, big data, campus networks, data centers, and IoT domains. The consumer business segment includes high-tech Components that offer a premium user experience in various end-use applications. Huawei cloud is the newest segment included in the company’s portfolio that offers customers with stable, reliable, secure, and trustworthy cloud services for various industry verticals, such as manufacturing, healthcare, e-commerce, connected vehicles, high-performance computing, IoT, and SAP. The company operates in Europe, the Middle East & Africa, Asia-Pacific, and the Americas.
Fujitsu Ltd
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NVIDIA Corporation
Company Headquarters: US Founded: 1993 Workforce: ~13,277 Company Working: NVIDIA Corporation (NVIDIA) is one of the leading visual computing companies. The company focuses on PC graphics. It has invented graphics processing units (GPU) that solve the most complex problems in computer science. It operates in two business segments, namely the GPU and Tegra Processor. The GPU segment consists of products such as GeForce for mainstream PCs and PC gaming; GeForce Now for cloud-based game-streaming services; Quadro for professional designing such as video editing and computer-aided designs (CAD); Tesla for deep learning and accelerated computing; GRID for cloud and data centers; and DGX for AI scientists, developers, and researchers. The Tegra Processor segment consists of products such as Tegra processors, DRIVE, SHIELD, and Jetson TX2. The company serves its products to the gaming, professional visualization, data center, and automotive markets. The company operates across North America, Asia-Pacific, Europe, and the rest of the world.
Qualcomm Technologies Inc.
Company Headquarters: US Founded: 1985 Workforce: ~41,000 Company Working: Qualcomm Technologies Inc. (Qualcomm) is one of the global leaders in the commercialization and development of foundational technologies and products used in mobile devices and wireless products, including broadband gateway equipment, network equipment, and consumer electronics devices. The company conducts its business primarily through three operating segments—Qualcomm CDMA Technologies (QCT), Qualcomm Technology Licensing (QTL), and Qualcomm Strategic Initiatives (QSI). QCT develops and supplies integrated circuits and system software based on CDMA, OFDMA, and other technologies for data communications, End-User processing, global positioning systems, and multimedia products. QCTs integrated circuits are used in laptops, tablets, data modules, gaming devices, data cards, and other consumer electronics systems. The Qualcomm Snapdragon mobile processors and platforms provide graphics, advanced End-User, and AI-processing capabilities to various devices. The company offers Vision-Enhanced Precise Positioning software, which combines the output of multiple currently implemented automotive sensors such as GNSS, IMU, and wheel sensors to deliver accurate and cost-effective global vehicle positioning. The company operates globally in China, the US, and South Korea.
Xilinx Inc.
Company Headquarters: US Founded: 1984 Workforce: ~4,200 Company Overview: Xilinx Inc. is a manufacturer and inventor of field-programmable gate array (FPGA), programmable system-on-chip (SoC), and adaptive compute acceleration platform (ACAP). The company designs and develops programmable devices and associated technologies, including a programmable system on chips (SoCs), 3D ICs, programmable logic devices (PLDs), printed circuit boards (PCBs), software design tools, and intellectual property (IP). Apart from its programming platforms, the company provides design services, customer training, field engineering, and technical support. The company’s products have solutions in a wide range of industries including aerospace and defense, automotive, broadcast and pro a/v, consumer electronics, data center, emulation and prototyping, high-performance computing, industrial, medical, test and measurement, and wired and wireless communications. The company has over 4000 patents and more than 60 industry-first inventions to its name.
Samsung Electronics Co. Ltd
Company Headquarters: South Korea Founded: 1938 Workforce: ~308,745 Company Overview: Samsung Electronics Co Ltd is a South Korean multinational conglomerate. The company has its footprint in almost all the segments, including food processing, textiles, electronics, securities, retail, engineering, construction, and entertainment. The core values of the company are its people, change, excellence, integrity, and co-prosperity. It has around 220 operation hubs worldwide and operates majorly in Korea, Europe, North America, Africa, and Southeast Asia. Its ambitious marketing strategies have played an important role in lifting Samsung’s image from a low-end manufacturer to a global leader in digital technology. It has a powerful influence on South Korea's economic development, politics, media, and culture. Its affiliated companies produce around a fifth of South Korea's total exports.
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AI Chipset Market