Global Artificial Intelligence Chip Market Size By End-User (Healthcare, Manufacturing, Automotive, Retail), By Technology (Machine Learning, Predictive Analysis), By Geographic Scope And Forecast

Artificial Intelligence Chip Market Size And Forecast

Artificial Intelligence Chip Market size was valued at USD 10.25 Billion in 2021 and is projected to reach USD 309.53 Billion by 2030, growing at a CAGR of 46.03% from 2023 to 2030.

The demand for more effective systems to tackle mathematical and computational issues, the advent of , and the expanding use of in robotics are anticipated to propel the development of the global artificial intelligence (AI) chip market.The Global Artificial Intelligence Chip Market report provides a holistic evaluation of the market. The report offers a comprehensive analysis of key segments, trends, drivers, restraints, competitive landscape, and factors that are playing a substantial role in the market.

Global Artificial Intelligence Chip Market Definition

Artificial Intelligence (AI) Chips are silicon chips that combine AI technology to handle computational and mathematical issues while minimizing human mistakes. These AI processors can successfully manage massive and parallel systems. The increased use of social media and platforms has resulted in a tremendous increase in data volume, necessitating more efficient processors for the faster completion of machine learning tasks. Because of enabling , AI-based processors solve the need for quicker processing.

AI chips are constructed from 16 NVIDIA V100 Tensor Core GPUs. The NVIDIA DGX A100 is New Zealand’s first computer and the world’s most sophisticated machine for supporting general AI tasks. People’s daily interactions with programs that require training include Facebook photographs and Google translate. Artificial intelligence is classified into four typesself-awareness, limited memory, reactive machines, and theory of mind. AI chips are tens or even thousands of times quicker and more efficient than CPUs for training and inference of AI algorithms due to their unique properties.

Customer preference for Internet of Things devices is one of the primary causes driving tech firms to build high-speed CPUs. AI chips may potentially be embedded into mobile devices like smartphones. These processors have several advantages, including increased speed, usability, and data privacy and security. Intelligent robotics, speech recognition, , and smart hardware are some of the uses of AI chips.

Global Artificial Intelligence Chip Market Overview

The AI investment landscape witnessed another year of solid growth in 2019, with the US taking the lead, reaching a record USD 22.70 billion. Despite many headwinds and realignment of interest and priorities that can breed uncertainty, the market did not suffer any fatigue. Enterprises are increasingly warming up to the AI value. Not only are enterprises actively adopting automation to automate repetitive processes, ensure compliance, and enhance customer experience, but also they are partnering with machine learning platforms and acquiring AI startups and talent to build data pipelines, create proprietary AI models, and manage their machine learning development and operation lifecycle.

Different key players have been innovating to develop a dedicated platform, for instance, Mythic’s platform has the advantage of processing digital/analog calculations in memory, resulting in enhanced performance, accuracy, and power life. Furthermore, the surge in the need to integrate & AI and the rise in government spending for solutions integrated with real-time analytics & AI are anticipated to boost the growth of the artificial intelligence chip. Hence, the increase in investments in AI startups drives the global Artificial Intelligence Chip Market growth.

Quantum computing devices work based on quantum bits or qubits. A qubit can be both 0 and 1 at the same time. Quantum computers take seconds to complete a calculation that would otherwise take thousands of years; Some of the quantum computer advancements in recent years, by IBM in 2017 announcing a 50 qubit chip, Intel announcing a 48 qubit chip, and Google Bristlecone with a 72 qubit chip. Quantum computers are the innovative transformation of artificial intelligence, , and machine learning. Quantum computing will impact the world, which would allow much faster database searches and simulations as the world is growing exponentially.

Quantum computing will make a lot of impossible things possible in the future. Therefore, the emergence of quantum computing fuels the Artificial Intelligence Chip Market growth. However, there are relatively higher prices of AI chips and a scarcity of skilled workforce with knowledge of AI-based systems, especially in developing economies. These may adversely impact the global Artificial Intelligence Chip Market growth. The upsurge in research and development investments, increased use of autonomous robotics at industry verticals, and high-tech product launches shall create new global Artificial Intelligence Chip Market growth opportunities.

Global Artificial Intelligence Chip Market Segmentation Analysis

The Global Artificial Intelligence Chip Market is segmented based on End-User, Technology, And Geography.

Artificial Intelligence Chip Market, By End-User

• Healthcare
• Manufacturing
• Automotive
• Retail
• Cybersecurity
• Others

Based on End-User, the market is segmented into Healthcare, Manufacturing, Automotive, Retail, Cybersecurity, and Others. The cybersecurity industry holds the largest size of the global Artificial Intelligence Chip Market due to the growing implementation of antivirus and antimalware solutions as cybersecurity attacks worldwide continue to rise. Increasing the use of mobile devices for a wide range of applications, like e-mails, , remote monitoring, , and storage, increases hacking risks, thereby making networks more vulnerable to threats. The rapid adoption of cloud-based services and user-friendly antivirus and antimalware solutions drives the Artificial Intelligence Chip Market.

Artificial Intelligence Chip Market, By Technology

• Machine Learning
• Predictive Analysis
• Natural Language Processing
• Others

Based on Technology, the market is segmented into Machine Learning, Predictive Analysis, , and Others. Deep learning technology is expected to be adopted extensively during the forecast period. Deep learning is a class of machine learning based on multiple algorithms to create relationships among data. It uses artificial neural networks to learn multiple levels of data, like texts, images, and sounds. Its algorithms help to identify patterns from a set of unstructured data. Moreover, The growing application of algorithms is a major driving force for the Artificial Intelligence Chip Market. Deep learning technology is currently used in , fraud detection, voice search, , , , and motion detection.

Artificial Intelligence Chip Market, By Geography

• North America
• Europe
• Asia Pacific
• Rest of the world

On the basis of Geography, the Global Artificial Intelligence Chip Market is classified into North America, Europe, Asia Pacific, and the Rest of the world. North America holds a major market share of the global Artificial Intelligence Chip Market. This is due to the prominent presence of tech giants in the US. The region is also seeing extensive investments in Artificial Intelligence-related technologies and the use of AI chips in security applications. The Asia Pacific region is expected to grow at a significant pace owing to the presence of developing countries such as China and India, which are seeing technological advancements and large-scale implementation of AI processor-enabled systems.

Key Players

The “Global Artificial Intelligence Chip Market” study report will provide valuable insight with an emphasis on the global market including some of the major players such as NVIDIA Corporation, Qualcomm Technologies Inc, Advanced Micro Devices Inc, Alphabet Inc., Intel Corporation, Apple Inc., Mythic Ltd., Baidu, Samsung Electronics Co. Ltd., and MediaTek Inc.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

Key Developments

• In December 2022, Samsung Electronics announced a partnership with internet portal giant Naver Corporation to create next-generation artificial intelligence (AI) chips as part of efforts to increase the efficiency of processing huge AI data sets.
• In October 2022, IBM announced system-on-chip AI hardware. The AIU is a full system-on-chip board that connects to servers using an industry-standard PCIe interface. The IBM Tellum microprocessor, which drives the IBM z16 series mainframes, including the LinuxOne Emperor 4, contains an AI core that serves as the AIU’s basis. The Tellum processor’s AI cores are 7nm, whereas the AIUs have 32 cores apiece and were designed using a 5nm (nanometer) technology.
• In may 2022, Intel Corp. launched a new chip termed Gaudi2 aimed at artificial intelligence computing, as the chipmaker expands its presence in the AI chip industry. Gaudi2 is the second generation processor by Habana Labs, an Israeli AI chip business acquired by Intel in late 2019 for around $2 billion. AI chip firms have received significant funding in recent years, as AI computing is one of the fastest-growing sectors of data centre activity.
• In August 2020, Kneron, a leading full-stack edge AI solutions provider, launched its advanced AI chipset – “Kneron KL 720 SoC”. The goal is to offer a complete and cost-effective AI chipsets suite for devices all around the world.
• In May 2020, Nvidia Corporation, a global corporation that manufactures graphics processors, mobile technologies, and desktop computers, expanded its EGX Edge AI platform by launching the new EGX Jetson Xavier NX and EGX A100. The aim is to offer secured AI processing and high-performance at the edge.
• In September 2019, Alibaba Group Holding Limited launched an AI-based chipset – “Hanguang 800” that offers advanced computing capability on the cloud. This chip can accelerate machine learning tasks and improves the customer experience.
• In September 2019, Apple Inc. built its A11, A12, and A13 Bionic Chips for the high-performance processors that consist of core CPUs integrated with GPUs as accelerators.
• In December 2019, Intel Corporation acquired Habana labs for $2 billion. Intel Corporation advanced its AI strategy with this acquisition by providing customers with solutions that fit their needs.
• In August 2019, NVIDIA Corporation partnered with VMware and Amazon to accelerate AI tasks. With this partnership, NVIDIA Corporation released GPU technology for the VMware Cloud on AWS. This also helped joint customers of NVIDIA Corporation and VMware to streamline their workflow.
• In March 2019, AMD partnered with ScaleMP to enable AMD server OEMs to create systems with 4, 8, and up to 128 processor sockets, 8,192 CPUs, and 256 terabytes of shared memory.

Ace Matrix Analysis

The Ace Matrix provided in the report would help to understand how the major key players involved in this industry are performing as we provide a ranking for these companies based on various factors such as service features & innovations, scalability, innovation of services, industry coverage, industry reach, and growth roadmap. Based on these factors, we rank the companies into four categories as Active, Cutting Edge, Emerging, and Innovators.

Market Attractiveness

The image of market attractiveness provided would further help to get information about the region that is majorly leading in the global Artificial Intelligence Chip market. We cover the major impacting factors that are responsible for driving the industry growth in the given region.