Artificial Intelligence chipsets market size was valued at USD 29.8 billion in 2031, growing at a CAGR of 30.7% during the forecast period. For instance, in December 2019, according to the National AI R&D Strategic Plan, the U.S. government raised the fundamental AI R&D investments by USD 25 billion. This enables an increase in the adoption of AI chipsets within the region.
Edge AI means that AI algorithms are processed locally on a hardware device. The algorithms are using sensor data or signals that are created on the device. The artificial intelligence chips address the need for faster processing due to enabled machine learning. Furthermore, it offers a broad range of traits that include speed, usability, data privacy, and security, among others.
|Market Size||USD 29.8 billion In 2031|
|Fastest Growing Market||Asia-Pacific|
|Largest Market||North America|
|Report Coverage||Revenue Forecast, Competitive Landscape, Growth Factors, Environment & Regulatory Landscape and Trends|
Deep learning is a subset of machine learning and artificial intelligence (AI). Deep learning has witnessed substantial growth over the past few decades on account of the increasing adoption of robots in industry verticals such as healthcare, manufacturing, and IT, among others. Furthermore, growing trends in human-machine interaction also lead to the adoption of deep learning and neural networks. Additionally, increasing investment in innovative products such as Cortana, GoogleNow, and Alexa also paves the way for the adoption of deep learning and neural networks. Thus, the above trends escalate the adoption of artificial intelligence chips to enhance consumers' experiences in speech recognition, multi-language chatbots, and image recognition, among others.
The surge in adoption of deep learning and neural networks, the increasing usage of social media and e-commerce platforms, and the increasing focus on human-aware AI systems are the factors fueling market growth. However, a lack of an artificial intelligence (AI) workforce hinders market growth.
North America holds higher CAGR in AI chipsets market and is anticipated to witness growth during the forecast period. The growth is owing to presence of major players in the region offering AI chipsets such as; NVIDIA, Intel Corporation, Google, and Microsoft among others. Moreover, increasing investment by the government to focus on in-house AI applications production and continuous investments in artificial intelligence-related technologies is also one of the factors fuelling the market growth.
Asia-Pacific is the fastest growing region in the AI chipset market and is expected to witness growth during the forecast period. The growth is attributed to increasing adoption of smart phones in developing economies which creates necessity to adopt AI chipsets on account of surge in antimalware/antivirus solutions. Moreover, increasing product launches and technical enhancements by regional technology vendors for various applications are also one of the factors escalating the market growth. For instance, For instance, China-based SenseTime leverages its deep learning platform to power image recognition, intelligent video analytic and medical image recognition to its customers, through its facial recognition technology called DeepID.
Similarly, DeepSight AI Labs, an India-based start-up also uses deep learning to develop SuperSecure – Platform, a smart retrofit video surveillance solution that works on any CCTV to provide a contextualized AI solution to detect objects and behaviors.
The global Artificial Intelligence Chipsets market has been segmented into hardware, function, technology and end-users
On the basis of hardware, the global Artificial Intelligence Chipsets market has been segmented into processor, memory and network
Memory segment holds higher CAGR and is anticipated to witness growth during the forecast period. The growth is owing to surge in accumulation of data which requires for predictive analytics, machine learning, and computer vision among others to validate, test and train. Thus, this creates necessity of high data storage memory. Moreover, high bandwidth memory is being deployed foray applications independent of its computing architecture. Additionally, fewer startups companies are being exploring high bandwidth file system to enhance efficiency. For instance, in February 2020, Micron, collaborate with technology company Continentalto explore and adapt Micron’s deep learning accelerator for next-generation machine learning automotive applications. This enables two technology leaders to enhance machine learning to meet extreme memory requirement.
On the basis of technology, the global Artificial Intelligence chipsets market has been categorized into Machine Learning, Natural Language Processing, Context-aware Computing, Computer Vision, and Predictive Analysis
Machine Learning is the fastest growing segment and is expected to witness growth during the forecast period. The growth is attributed to increasing investment in innovative products such as voice recognition, image recognition, and multiple language chatbots among others. Thus, these products require advanced machine learning to leverage multiple level of data. Furthermore, Machine Learning enabled solutions are readily being adopted across the globe to enhance customers’ experience, ROI, and to gain competitive edge in business operations. Moreover, increasing adoption of machine learning product across various industries vertical is presumed to gain growth in the coming years particularly in government and defence and manufacturing sector to enhance fraud detection and security activities.
On the basis of function, the global Artificial Intelligence chipsets market has been segmented into training and interference
The interference segment holds dominant position and is expected to grow during the forecast period. The growth owes to surge in adoption of edge computing on account of privacy and security concerns. Moreover, dual offering of interference segment both in cloud and edge computing also pave the way for adoption of interference segment. This also enables the vendors to shift towards the offering of interference segment over training. For instance, in January 2018, Google has built its Artificial Intelligence chipsets for interference workload.
On the basis of end-users, the global Artificial Intelligence Chipsets market has been categorized into healthcare, automotive, manufacturing, agriculture, retail, cyber security, human resources, marketing, law, fintech and government.
Cyber security sector holds higher CAGR and is expected to grow during the forecast period. The growth is attributed to increasing cyber attack cases across the globe. Furthermore, growing penetration rate of smart phones for broad range of applications such as banking, social networking, e-mails and data storage often leads to way for surge in cyber attack activities. Moreover, growing SMEs across the globe which prefers cloud based services on account of budget constraints adopts users-friendly antivirus thereby paving way for the growth of market.
The impact of COVID-19 has devastating effect across all industry vertical globally. The market of AI chipsets has witnessed declination in growth amid pandemic COVID-19 on account of affected supply chains and limited adoption of AI in various end-user industries in 2020 due to the lockdowns and shifting priorities of different industries. Moreover, many manufacturing company has temporarily stop business operation leading to damage the supply chain and industry. Thus, this leads to delay in adoption of Ai-based hardware and software products. However, Ed-Tech firms have deployed AI tools to enhance online learning and virtual classroom experience for students.
Thus from the above stats, it can say that AI chipsets is expected to witness growth during the forecast period on account of increasing adoption of online learning and virtual classroom adoption among educational institutions.
Top 24 Companies In The Global Market
In February 2020, GAVS Technologies and Darktrace partnered to ensure resilience and security for business service continuity that keeps the infrastructure free of outages and data disasters, enabling businesses to remain on the competitive vanguard through the ever-increasing threat landscape.