Artificial Intelligence Chip Market Growth, Trends, and Analysis by 2027

The artificial intelligence chip market was valued at US$ 5658.1 million in 2018 and is projected to reach US$ 83,252.7 million by 2027; it is expected to grow at a CAGR of 35.0% during 2019–2027.

With the availability of enormous amount of data and vast scalability of cloud-based compute power, artificial intelligence has become a massive trend across industries in these past few years. In today’s digital world, information is the key for enterprises to be successful and to maintain sustainable growth. Most industries especially service sector rely deeply on analytics to provide them with useful business insights and enable them to remain competitive in the market. Enterprises have been continuously automating their business processes that were earlier conducted either programmatically or manually. With advancement in AI chips and introduction of application-specific custom chips, enterprises now have the capability to collect real-time analytics and to transform data into actionable insights. There are numerous use cases available in the Artificial Intelligence Chip market of AI being successfully implemented across various verticals.

The major artificial intelligence applications for which AI chips are being used include Machine Learning (ML), Natural Language Processing (NLP), Expert Systems, Automated Speech Recognition, AI Planning, and Computer Vision.

Artificial Intelligence Chip Market: Strategic Insights

Market Insights– Artificial Intelligence Chip Market

Increasing Investments in AI Chip Start-Ups will Fuel the Market during the forecast period

Artificial intelligence and its applications such as machine learning and deep learning have been growing tremendously over the last few years. AI is being utilized extensively in numerous areas ranging from cloud computing applications to digital assistants and self-driving/autonomous vehicles. With ever increasing use cases of AI and the evolving market landscape, the advancements in present chips have become a necessity. AI is majorly used in data center training market where NVIDIA is a market leader. However, the demand for application-specific custom AI chips and inference on edge and data center are the fast-growing segments in AI chip market, and many new startups are coming up to tap this market

Segment Insights

Based on segment, the artificial intelligence chip market is bifurcated into Data center/Cloud and edge applications. The Data Center accounted for the largest share in the global market share in 2018. Presently, the major application of artificial chips is in data center/cloud applications. AI chips in data centers are used for both training and inference purposes. Training is a process in which AI algorithms analyze the data, learn and then use that information to respond to real-world problems. Huge amount of data is analyzed by AI algorithms during the training process. In order to help developers in shortening their AI technology development processes, chip manufacturers should not only focus on increasing processor performance but to provide an entire ecosystem that includes hardware, framework and other supportive tools

Type Insights

Based on type, the artificial intelligence chip market is bifurcated into CPU, ASIC, GPU, FPGA and others. The GPU type segment accounted for the largest share in the global market share in 2018. Presently in artificial intelligence applications, Graphics Processing Units or GPUs are the most widely used hardware. High parallelism and memory bandwidth of GPUs make them the most viable option for machine and deep learning applications especially in training. GPUs were initially used to accelerate large number of multiply and add calculations executed in graphics rendering. With increase in demand of high performance graphics, the demand of powerful GPUs also grew.

The market players focus on new product innovations and developments by integrating advanced technologies and features in their products to compete with the competitors.

• In March 2019, AMD entered into a partnership with ScaleMP enable AMD server OEMs to create systems with 4, 8, and up to 128 processor sockets, up to 8,192 CPUs and 256 terabytes of shared memory.
• In July 2018, Google unveiled tiny new AI chips, Edge TPU, for on-device machine learning. Edge TPU is Google’s purpose-built application-specific integrated circuit (ASIC) designed to run AI at the edge. It delivers high performance in a small physical and power footprint, enabling the deployment of high-accuracy AI at the edge.

Artificial Intelligence Chip Market Players Density: Understanding Its Impact on Business Dynamics

The Artificial Intelligence Chip Market is growing rapidly, driven by increasing end-user demand due to factors such as evolving consumer preferences, technological advancements, and greater awareness of the product's benefits. As demand rises, businesses are expanding their offerings, innovating to meet consumer needs, and capitalizing on emerging trends, which further fuels market growth.

The Global Artificial Intelligence Chip Market has been Segmented as Follows:

Artificial Intelligence Chip Market– by Segment

• Data Center
• Edge

Artificial Intelligence Chip Market – by Type

• CPU
• GPU
• ASIC
• FPGA
• Others

Artificial Intelligence Chip Market – by Industry Vertical

• BFSI
• Retail
• IT & Telecom
• Automotive & Transportation
• Healthcare
• Media & Entertainment
• Others

Artificial Intelligence Market –by Geography

• North America
  • US
  • Canada
  • Mexico
• Europe
  • France
  • Germany
  • Italy
  • Russia
  • UK
  • Rest of Europe
• Asia Pacific (APAC)
  • South Korea
  • China
  • India
  • Australia
  • Japan
  • Rest of Asia Pacific
• Middle East & Africa (MEA)
  • Saudi Arabia
  • UAE
  • South Africa
  • Rest of MEA
• South America (SAM)
  • Brazil
  • Argentina
  • Rest of South America (SAM)

Artificial Intelligence Chip Market –Companies Profiles

• Advanced Micro Devices, Inc.
• Google, Inc.
• Huawei Technologies Co., Ltd
• IBM
• Intel Corporation
• Micron Technology, Inc.
• NVIDIA Corporation
• QUALCOMM Incorporated
• Samsung Electronics Co., Ltd.
• Xilinx, Inc.