Global AI/Deep Learning Workstation Market Size (2023-2030)

The Global AI/Deep Learning Workstation Market was estimated to be worth USD 49.6 Billion in 2022 and is anticipated to reach a value of USD 687.23 Billion by 2030, growing at a fast CAGR of 38.90% during the outlook period 2023-2030.

Many repetitive and routine tasks can be completed by deep learning algorithms more quickly and effectively than by humans. It can also provide extra features like crucial insights and a guarantee for the calibre of the work. Therefore, applying deep learning use within organisations can help save time and money, ultimately freeing up the staff to carry out creative projects that need human involvement. Deep learning is therefore viewed as a disruptive technology across many end-use sectors, increasing the demand for technology during the predicted period.

Recent advancements in neural network architecture, training methods, graphics processing units (GPU), and the accessibility of a sizable amount of data from many industries have all contributed to the growth of deep learning technology. Data volume increased as a result of the adoption of machine vision, IoT, cybersecurity applications, industrial automation, and robotics. Deep learning systems, which aid in diagnosis and testing, can use this data as a training module.

Deep learning algorithms build a consolidated data environment and learn from previous experiences. Results will be more accurate and data will be handled consistently as there is more data available. Machine translation, chatbots, and service bots are just a few areas where deep learning is used. A Deep Neural Network (DNN) that has been trained can translate a word or a sentence without the use of a sizable database. The performance of the system is enhanced by DNNs, which deliver more precise and superior outcomes than traditional machine translation techniques.

Chatbots and service bots can utilise deep learning algorithms to enhance customer service and lessen the workload on contact centres. Automatic Speech Recognition (ASR) and Natural Language Processing (NLP) are two applications of the deep learning platform that chatbots use to automatically transfer calls. According to a 2018 poll by Oracle Corporation, chatbots are currently used by 80% of enterprises.

Global AI/Deep Learning Workstation Market Drivers:

• Improving computing power and declining hardware cost is increasing growth in the AI/Deep Learning Workstation Market.

Growing organisational demand for processing power and the deployment of IoT devices across a variety of industries are driving market expansion. Additionally, 2.5 quintillion bytes of new data are generated daily, and that figure is rising. Huge amounts of data generated by numerous industry sectors are creating profitable opportunities for deep learning solutions to give businesses effective, adaptable, and scalable insights. Additionally, the banking, financial services, and insurance (BFSI) industry held the largest deep learning market share in 2022 due to the industry's high production of sensitive data, rising cyberattack rate, and emphasis on customer data security and legal compliance, all of which contribute to the market's expansion. Additionally, it's getting cheaper and simpler than ever to instrument anything and convey that data in real-time through a messaging system, enabling businesses to make wise decisions more quickly and favourably influence the market expansion.

• Increased use of cloud-based services and the massive production of unstructured data is driving growth in the AI/Deep Learning Workstation Market.

The demand for deep learning solutions has increased as a result of the widespread use of cloud-based services and the massive production of unstructured data. In addition, the increasing use of deep learning in recent years for language translation, data mining, and image/speech recognition, as well as the rise in popularity of humanoid robots like Hanson Robotics' Sophia, are some of the key factors driving the deep learning market. Key market participants are likely to increase their efforts in the development of machine learning and deep learning applications in the area, accelerating market growth. Additionally, industry growth is anticipated to be boosted by the quick rise in data collected across a variety of end-use industries.

Global AI/Deep Learning Workstation Market Challenges:

The market growth is being constrained by reasons including a lack of deep learning technical competence and a lack of standards and protocols. Additionally, tough tasks that restrict growth include the integration of deep learning software and solutions into the current systems. Additionally, deployment of DL for applications like NLP in regional dialects, lack of flexibility and multitasking, and increasing complexity in hardware due to complicated algorithms are possible barriers to the growth of the global deep learning market.

Global AI/Deep Learning Workstation Market Opportunities:

The growing demand for human-machine interaction is giving solution providers new growth opportunities to deliver improved solutions and capabilities. Additionally, the widespread use of deep learning integration with big data analytics and the growing demand for increased computing power and lower hardware costs as a result of deep learning algorithms' ability to run or execute more quickly on a GPU than a CPU is expected to have a positive impact on the growth of the global deep learning market. Positive growth opportunities are provided by technological advancements, the lack of sufficient structured data to meet the growing demand for deep learning solutions, cumulative spending in the healthcare, travel, tourist, and hospitality sectors, and untapped potential in emerging economies.

COVID-19 Impact on Global AI/Deep Learning Workstation Market:

Due to the spike in demand for anti-money laundering (AML), fraud detection, and other solutions in the pandemic condition, the COVID-19 pandemic has caused a considerable increase in the income of the deep learning market.

Additionally, the COVID-19 pandemic has caused changes in model performance since deep learning models are developed using static validation and testing techniques, which are less effective at mitigating different types of risk. The General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) are just two examples of the strict rules that have been implemented by various governments in response to the growing digital revolution, which is fueling the market's expansion.

Global AI/Deep Learning Workstation Market Recent Developments:

• In January 2020, Johnson Controls said that Intel Corporation and its retail solutions portfolio, Sensormatic Solutions, will work together to provide scalable, AI-powered solutions for retailers. In the future, Intel systems will serve as the foundation for Sensormatic Solutions' AI edge offering. For the delivery of its solutions, Sensormatic Solutions will also use Intel Distribution of the OpenVINO toolkit and Intel models.
• In June 2021, Amazon Web Services and Larsen & Toubro Infotech signed a strategic collaboration agreement. The business recently established a separate AWS cloud entity that would concentrate on data analytics, the Internet of Things, migration and modernization, and SAP application workloads. Additionally, it will offer professional services, delivery capabilities, and consulting services.
• In February 2021, the acquisition of Auggi by Seed Health was announced. For automatic stool image detection, Auggi employs a deep learning method. Deep convolutional neural networks and computer vision are used to characterize an individual's stool over time. Through the acquisition, Seed Health will be able to include Auggi's mobile monitoring application in their human clinical trials evaluating DS-01 and the gut flora in IBS following antibiotic use.
• On February 1, 2020, The Oracle Cloud Data Science Platform was introduced, by Oracle Corporation, a renowned technology company. The recently released platform will help companies develop, train, manage, and collaboratively deploy machine learning models to enhance the effectiveness of data science programmes.
• In April 2020, to manage complex systems and conduct scientific research, the US Department of Energy stated that it will allocate up to USD 30 million for advanced machine learning and artificial intelligence research. The effort covers two distinct subject areas. The development of ML and A.I. for simulation and predictive modelling with an emphasis on research in the physical sciences is one area of discussion.

AI/DEEP LEARNING WORKSTATION MARKET REPORT COVERAGE:

Global AI/Deep Learning Workstation Market Segmentation:

Global AI/Deep Learning Workstation Market Segmentation: By Solution

• Hardware
• Software
• Service
  • Installation services
  • Integration services
  • Maintenance & support services

The market for deep learning services is expected to grow at the greatest CAGR throughout the projected period, with the software category holding the largest market share. The demand is being accelerated by the variables that can be linked to the growing use of software solutions in a variety of applications, including smartphone assistants, ATMs that can read checks, voice and image recognition software on social networks, and software that serves up advertisements on several websites.

Global AI/Deep Learning Workstation Market Segmentation: By Hardware

• Central Processing Unit (CPU)
• Graphics Processing Unit (GPU)
• Field Programmable Gate Array (FPGA)
• Application-Specific Integration Circuit (ASIC)

In 2022, the Graphics Processing Unit (GPU) accounted for roughly 56.3% of the market. As they offer high memory bandwidth and throughput, GPUs are a frequently utilised hardware category for enhancing training and classification procedures in computer neural networks (CNNs). Additionally, the GPU improves processing capability, enabling the system to perform several simultaneous activities. By merging multiple GPUs in one machine, multi-GPU improves the performance of deep learning.

Additionally, it provides a quick and accurate computational capability to carry out a variety of activities simultaneously in real time. The autonomous vehicle can detect objects with the aid of many GPUs. The system must quickly complete a wide range of tasks, including obstacle identification, boundary determination, and junction detection. Deep learning is being advanced by several innovations.

The greatest option for deep learning technology has emerged as FPGA. FPGA setups are currently widely used for many applications when formerly they were exclusively used for training. FPGA has a wide range of applications for data processing in data centres and is quick, quick, and power-efficient. FPGAs have also grown in popularity among engineers and researchers because they make it possible to quickly prototype a variety of designs in comparison to using a standard IC.

Global AI/Deep Learning Workstation Market Segmentation: By End-Use

• Automotive
• Law
• Agriculture
• Retail
• Marketing
• Security
• Healthcare
• Manufacturing
• Human Resources

For the forecasted time, the security segment has the biggest market share, followed by marketing. Because new varieties of cyberattacks are continually being discovered and organisations need to stay on top of these threats to protect their essential assets, several variables may be ascribed to the rapidly evolving cybersecurity ecosystem. Deep learning in security solutions enables businesses to safeguard sensitive data and prevent data loss. Gaining significance in the sphere of marketing as well, particularly for media and advertising.

Global AI/Deep Learning Workstation Market Segmentation: By Region

• North America
• Europe
• Asia Pacific
• Middle East and Africa
• South America

Due to greater investments in artificial intelligence and neural networks, North America dominated the market in 2022 with a revenue share of approximately 36.8%. Over the course of the projected period, new growth prospects should be made possible by the region's strong adoption of image and pattern recognition. Additionally, the region is among the early adopters of cutting-edge technologies, enabling businesses to embrace deep learning skills more quickly.

Additionally, it is anticipated that increasing government backing will have a favourable effect on the expansion of the sector in the area. The federal government's creation of machine learning and artificial intelligence subcommittees is paving the way for expansion.

Europe has made a substantial contribution to the market's growth as a result of new initiatives to promote the artificial intelligence industry there and foster the development of a digital economy. As a result, the deep learning industry now offers many chances for expansion. The development of technology in the fields of driverless vehicles, smart devices, and cyber security is supported by the United Kingdom.

Global AI/Deep Learning Workstation Market Key Players:

1. Advanced Micro Devices, Inc.(AMD)
2. Alphabet, Inc.
3. Amazon.Com, Inc.
4. Amp Robotics
5. Creative Virtual
6. Curemetrix
7. Datagen
8. Graphcore
9. IBM Corporation