AI in Hardware Market Surges to $58.61 Billion by 2028, Fueled by Urbanization and IoT Growth

The ai in hardware market size has grown exponentially in recent years. It will grow from $20.88 billion in 2023 to $25.96 billion in 2024 at a compound annual growth rate (CAGR) of 24.3%. The growth in the historic period can be attributed to strong economic growth in emerging markets, increase in penetration of smartphones and rise in adoption of ai hardware in banking, it and telecom.

The ai in hardware market size is expected to see exponential growth in the next few years. It will grow to $58.61 billion in 2028 at a compound annual growth rate (CAGR) of 22.6%. The growth in the forecast period can be attributed to rapid urbanization, increasing penetration of the internet, increase in smart cities, increasing demand for autonomous vehicles and growing demand for cloud computing. Major trends in the forecast period include rapid urbanization, increasing penetration of the internet, increase in smart cities, increasing demand for autonomous vehicles and growing demand for cloud computing.

Market Overview -
AI in hardware refers to the use of artificial intelligence (AI) technologies in hardware devices or systems. This includes the use of machine learning algorithms, deep learning models, and other AI techniques to enhance the functionality, performance, and efficiency of hardware devices such as computers, smartphones, and Internet of Things (IoT) devices.

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AI Hardware Adoption Propelling Growth Across Banking, It, And Telecom Sectors
The adoption of AI hardware in banking, IT, and telecom is expected to propel the growth of the AI in hardware market going forward. Banking, IT and telecom are all growing industries. These industries are increasingly leveraging AI technologies to enhance their operations, improve customer experiences, and drive innovation. AI hardware is used in banking to enhance fraud detection and prevention, risk management, and customer service. IT companies use AI hardware to analyze large amounts of data from connected devices to detect anomalies and predict when maintenance is required and telecom companies use AI-enabled hardware to analyze network traffic in real-time to identify and fix performance issues. For instance, in January 2022, according to the Government Digital Service., a UK-based government office, IT and telecom adopted 29.5% of AI technology. In 2021, the highest AI adoption was in banking and IT, with 52%, and in media and telecoms with 38%. Therefore, the adoption of AI hardware in banking, IT, and telecom is driving the growth of the AI in hardware market.

Competitive Landscape -
Major companies operating in the ai in hardware market report are Qualcomm Technologies, Alphabet Inc., Micron Technology, NVDIA Corporation, Huawei Technologies Co. Ltd.,Intel, Apple Inc., IBM, Advanced Micro Devices Inc., Samsung Electronics Co. Ltd., Xilinx, Cambricon Technologies, Graphcore, Kalray, Mipsology, BrainChip Holdings, LightOn, Synetec, Imobisoft, Light IT Global, Webol, Theodo, Digiryte, Innowise Group, Magora, Skyward Digital, GPU-Tech, Elvees NeoTek, Cogito Instruments, Trencadis Corp, Dell Technology Inc., Amazon Web Services, Inc., Open AI, Empiria.ai, NetuxLab, Tellumat, DataProphet, Cortex Logic, JUMO, Xineoh, Clevva

Technological Advancements Drive Innovation In The AI Hardware Market
Technological advancements are the key trends gaining popularity in the AI in hardware market. Major companies operating in the AI in the hardware market are adopting new technologies to sustain their position in the market. For instance, in April 2021, Intel Corporation, a US-based semiconductor technology corporation, launched 3rd generation Intel Xeon Scalable processors with built-in artificial intelligence (AI) acceleration. This innovative technology, combined with Intel's portfolio of Ethernet adapters, FPGAs, persistent memory and storage, Intel OptaneTM, optimized software solutions, high-performance computing (HPC), networking, and intelligent edge applications, enables performance and workload improvements. Additionally, includes features such as vector neural network instructions (VNNI), which accelerate convolutional neural networks, and tensor float 32 (BFLOAT16) support, which speeds up training and inference in deep learning models. With these AI acceleration capabilities, the 3rd generation Intel Xeon Scalable processors are well-suited for use in AI and machine learning applications.

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Key Segments -
The ai in hardware market covered in this report is segmented -
1) By Type: Processor, Memory Network, Storage
2) By Deployment: Cloud, On-Premise
3) By Technology: Machine Learning, Computer Vision, Natural Language Processing, Expert Systems
4) By Application: Training And Simulation, Driver Monitoring Systems, Surveillance And Security, Other Applications
5) By End User: Telecommunication And IT (Information Technology) Industry, Banking And Finance Sectors, Ecommerce, Robotics, Healthcare, Other End Users

Key highlights covered in the report -
1. Detailed market size forecast and historical data analysis
2. Key drivers influencing market growth
3. Identification of upcoming trends and potential opportunities in the market
4. Analysis of major players strategies, to understand competitive dynamics and market positioning
5. Evaluation of regional dynamics

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