The Cloud AI Market size was valued at USD 61.04 Billion in 2023 and is expected to grow to USD 523.0 Billion by 2031 and grow at a CAGR of 30.8% over the forecast period of 2024-2031.
The Cloud Al market is divided into solution and services categories based on type. According to the cloud Al market, the solution segment saw the biggest revenue share in 2022. The increasing availability of cloud-based Al solutions from major tech companies like Microsoft, Amazon, and Google is one of the primary factors propelling the market's growth. These companies spend a lot of money creating cloud-based Al platforms and charging companies of all sizes for them, which makes it easier for organizations to use and access Al solutions without having to pay a lot of money for staff or equipment.
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Healthcare, retail, BFSI, IT & telecommunication, government, manufacturing, automotive & transportation, and other verticals make up the segments of the cloud Al market. The cloud Al market is expected to hold a significant revenue share in 2022 according to the BFS! segment. It is probable that the industry will employ artificial intelligence for a range of risk management functions, such as market risk analysis, credit risk, liquidity risk, and asset & liability management (ALM). The Cloud Al market is expected to grow faster due to the BFSI sector's growing use of this technology for risk management, trading, credit scoring software, fraud detection, and financial market analysis, among other purposes.
Increasing use of cloud-based services and apps
The deployment of cloud Al has advanced since the introduction and ongoing use of the Internet of Things (loT), cloud, blockchain, artificial intelligence (Al), and other cutting-edge technologies. Taking advantage of the competition between the three major cloud service providers, many government agencies have deployed massive server clusters, implemented Hadoop and data lakes, and hired several data scientists. Because of the widespread involvement of businesses, governments across the globe are now more aware of the cloud's evolution from a data storage facility to a suite of capabilities that can reduce expenses and promote creativity and flexibility in all organizational environments.
Growing utilization of cloud-based services and apps
RESTRAIN:
The difficulties posed by open-source platforms
Many small and expanding companies use these platforms because the high costs of buying and licensing commercial software are one of the main reasons for this. Furthermore, by identifying and resolving vulnerabilities that might go unnoticed when the source code is made available to the general public, software security is enhanced. Additionally, open-source platforms are suitable for rapid prototyping and experimentation since they are simple to test prior to deployment. HTML and Perl are a couple of instances of open-source software, as are the DNS, Sendmail, and Apache servers. These platforms have shown to be robust and dependable even in the most trying situations.
OPPORTUNITY:
Al data centers' heightened emphasis on parallel computing
Parallel computing is widely used in commercial servers for tasks like data mining, AI, and VR development. GPUs are ideally suited for parallel computing because of their parallel architecture and numerous cores, which enable them to process multiple instructions at once. Furthermore, the parallel computing approach is suitable for implementing deep learning training and interface because artificial neural networks generally run more efficiently when run in parallel. The market for cloud Al is expected to grow during the projected period as a result of the growing demand for parallel computing.
CHALLENGES:
Technological Advancement
Al has apparently also been sent aboard drones to gather intelligence, launch strikes, and process enemy battlefield communications in facial recognition technology, cyber defense, etc. since Russia's full-scale invasion of Ukraine in February 2022. Reports regarding the use of Al in combat have coincided with extensive news coverage of the advancements in generative Al systems in recent months, giving the impression that the technology is pervasive. But a thorough analysis of the subject must recognize that Al is a relatively new technology with limited battlefield experience prior to the conflict in Ukraine. Thus, by default, Al's deployment in this conflict is unprecedented in terms of both scale and nature. However, it is challenging to determine whether these features and applications have only been utilized on sometimes or extensively utilized. Furthermore, it is impossible to determine whether, to what extent, and for what kind of Al and autonomous technologies are being employed in classified missions and tasks based on publicly available information.
The Bayraktar TB2 drones, manufactured in Turkey, were transferred by Ukraine to combat Russia. The TB2 can operate at medium altitudes and has a long endurance thanks to its armed UAVs that integrate ISR technologies (Baykar). The TB2 drone was given the specific mission of attacking Russian military targets and countering missile attacks. Social media is rife with videos of drones taking down targets, most likely Russian tanks or secret military installations in the woods (CNN, 2022; Eversden, 2022). Utilizing "Ukraine's most sophisticated" technology, the TB2 drones.
IMPACT OF ONGOING RECESSION
The COVID-19 pandemic caused a sharp spike in demand during the course of the last few years, which has resulted in notable growth in the cloud Al market. This was explained by the fact that businesses were moving to take advantage of the increased automation and digitization in the healthcare sector, which led to an increase in demand for healthcare services. In addition, the increase in COVID-19 cases forced governments and local authorities to impose stringent regulations, ranging from social distancing and self-isolation guidelines to the closure of actual stores and enterprises. This was done in an attempt to slow the COVID-19 case outbreak, which in turn led to an increase in the number of businesses relying on digital technologies. These patterns quickened the During the pandemic, physical businesses underwent digital transformation. However, the pandemic's effects on the economy forced businesses to look for more affordable options. As a result, businesses could easily expand their cloud-based business solutions deployments to support a large number of remote users without having to make large infrastructure investments. Citrix data indicates that 81% of IT directors intend to raise Desktop as a Service (DaaS) spending in 2022, and 71% of them believe DaaS is essential to their company's business strategy for securing hybrid working. The need for cloud computing will increase as a result.
In 2022, the region with the largest revenue share, North America, accounted for 34.67%. Numerous major companies, including Apple Inc., Google Inc., IBM Corp., Intel Corp., and Microsoft Corp., are present in the region. Businesses in a variety of industries that are early adopters of artificial intelligence (AI) and machine learning technologies are responsible for the region's high growth. It covers sectors that use Al to boost innovation, cut costs, and improve operational efficiency, including healthcare, finance, and retail. The workforce in North America is sizable and extremely skilled, making it well-suited to create and apply Al solutions. North America is home to numerous universities and research centres that are at the forefront of Al research and development, producing a constant flow of bright people who are propelling market innovation.
Over the course of the projection period, Asia Pacific is anticipated to grow at the fastest rate. The growth of the region is primarily ascribed to significant investments in cloud and Al technologies. The Asia-Pacific region is witnessing a surge in the demand for cloud-based apps and services, as well as enhanced operational effectiveness in the manufacturing sector. For example, in October 2021, as part of the Indian government's efforts to deploy machine learning and Al-driven cloud models to make sense of massive amounts of data, Amazon Web Services trained relevant government employees in India to develop a cloudiest approach to digital transformation and enhanced skill sets.
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REGIONAL COVERAGE:
North America
US
Canada
Mexico
Europe
Eastern Europe
Poland
Romania
Hungary
Turkey
Rest of Eastern Europe
Western Europe
Germany
France
UK
Italy
Spain
Netherlands
Switzerland
Austria
Rest of Western Europe
Asia Pacific
China
India
Japan
South Korea
Vietnam
Singapore
Australia
Rest of Asia Pacific
Middle East & Africa
Middle East
UAE
Egypt
Saudi Arabia
Qatar
Rest of Middle East
Africa
Nigeria
South Africa
Rest of Africa
Latin America
Brazil
Argentina
Colombia
Rest of Latin America
The Major Players are Apple Inc., Google, Inc., IBM Corp., Intel Corp., Microsoft Corp., MicroStrategy, Inc., NVIDIA Corp., Oracle Corp., Qlik Technologies, Inc., Salesforce.com Inc., ZTE Corp. and other players are listed in a final report.
November 2022 - Huawei Technologies (Malaysia) Sdn Bhd and ToGL Technology Sdn Bhd officially announced their partnership to develop cloud-based digital solutions in Malaysia. Artificial intelligence (Al) services and modern cloud experiences play a role in collaboration,
November 2022: The company's AssetCare platform will be merged with Google Cloud's power and scope as three Al-powered sustainability applications, in addition to additional services like Google Earth Engine, according to mCloud Technologies Corp., a top supplier of Al-powered asset management and Environmental, Social, and Governance solutions, which just declared that it and Google Cloud had formed a strategic alliance.
April 2023: IBM and Moderna, Inc., a biotechnology business that invented messenger RNA vaccines and treatments, reached a deal. As per the terms of the agreement, Moderna would investigate cutting-edge technologies such as quantum computing and artificial intelligence to promote and expedite mRNA science. Furthermore, Moderna would be able to benefit from multi-year research endeavors in generative Al for therapeutics that aid in the development of new molecules and help scientists better understand how they behave.
Apr-2023: In order to help industrial companies drive efficiency and innovation throughout the engineering, design, manufacturing, and operational lifecycle of products, Microsoft partnered with Siemens Digital Industries Software to provide advanced generative artificial intelligence. As a result of their collaboration, Siemens' Teamcenter product lifecycle management (PLM) software and Microsoft Teams are being integrated.
| Report Attributes | Details |
|
Market Size in 2023 |
US$ 61.04 billion |
|
Market Size by 2031 |
US$ 523.0 billion |
|
CAGR |
CAGR of 30.8% From 2024 to 2031 |
|
Base Year |
2023 |
|
Forecast Period |
2024-2031 |
|
Historical Data |
2019-2021 |
|
Report Scope & Coverage |
Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
|
Key Segments |
By Technology (Deep Learning, Machine Learning, Natural Language Processing, Others), By Type (Solution, Services, Vertical Outlook (Revenue, USD Million, 2017 - 2030), Healthcare, Retail, BFSI, IT & Telecommunication, Government, Manufacturing, Automotive & Transportation, Others) |
|
Regional Analysis/Coverage |
North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia Rest of Latin America) |
|
Company Profiles |
Apple Inc., Google, Inc., IBM Corp., Intel Corp., Microsoft Corp., MicroStrategy, Inc., NVIDIA Corp., Oracle Corp., Qlik Technologies, Inc., Salesforce.com Inc., ZTE Corp. |
|
Market Opportunities |
• Al data centers' heightened emphasis on parallel computing |
|
Market Challenges: |
• Technological Advancement |
Ans: Increasing use of cloud-based services and apps & Growing utilization of cloud-based services and apps.
Ans: Integrating data from various sources and managing it effectively for AI applications can be complex.
ns: The North America is dominating the AI Cloud Market.
Ans: The Cloud AI Market size was valued at USD 44.9 billion in 2022.
Ans: The Cloud AI Market is growing at a CAGR of 39.7% over the Forecast Period of 2023-2030.
TABLE OF CONTENTS
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Research Methodology
3. Market Dynamics
3.1 Drivers
3.2 Restraints
3.3 Opportunities
3.4 Challenges
4. Impact Analysis
4.1 Impact of the Russia-Ukraine War
4.2 Impact of Ongoing Recession
4.2.1 Introduction
4.2.2 Impact on major economies
4.2.2.1 US
4.2.2.2 Canada
4.2.2.3 Germany
4.2.2.4 France
4.2.2.5 United Kingdom
4.2.2.6 China
4.2.2.7 Japan
4.2.2.8 South Korea
4.2.2.9 Rest of the World
5. Value Chain Analysis
6. Porter’s 5 forces model
7. PEST Analysis
8. Cloud AI Market Segmentation, By Technology
8.1 Deep Learning
8.2 Machine Learning
8.3 Natural Language Processing
8.4 Others
9. Cloud AI Market Segmentation, By Type
9.1 Solution
9.2 Services
10. Cloud AI Market Segmentation, By Vertical
10.1 Healthcare
10.2 Retail
10.3 BFSI
10.4 IT & Telecommunication
10.5 Government
10.6 Manufacturing
10.7 Automotive & Transportation
10.11 Others
11. Regional Analysis
11.1 Introduction
11.2 North America
11.2.1 North America Cloud AI Market by Country
11.2.2North America Cloud AI Market by Technology
11.2.3 North America Cloud AI Market by Type
11.2.4 USA
11.2.4.1 USA Cloud AI Market by Technology
11.2.4.2 USA Cloud AI Market by Type
11.2.5 Canada
11.2.5.1 Canada Cloud AI Market by Technology
11.2.5.2 Canada Cloud AI Market by Type
11.2.6 Mexico
11.2.6.1 Mexico Cloud AI Market by Technology
11.2.6.2 Mexico Cloud AI Market by Type
11.3 Europe
11.3.1 Eastern Europe
11.3.1.1 Eastern Europe Cloud AI Market by Country
11.3.1.2 Eastern Europe Cloud AI Market by Technology
11.3.1.3 Eastern Europe Cloud AI Market by Type
11.3.1.4 Poland
11.3.1.4.1 Poland Cloud AI Market by Technology
11.3.1.4.2 Poland Cloud AI Market by Type
11.3.1.5 Romania
11.3.1.5.1 Romania Cloud AI Market by Technology
11.3.1.5.2 Romania Cloud AI Market by Type
11.3.1.6 Hungary
11.3.1.6.1 Hungary Cloud AI Market by Technology
11.3.1.6.2 Hungary Cloud AI Market by Type
11.3.1.7 Turkey
11.3.1.7.1 Turkey Cloud AI Market by Technology
11.3.1.7.2 Turkey Cloud AI Market by Type
11.3.1.8 Rest of Eastern Europe
11.3.1.8.1 Rest of Eastern Europe Cloud AI Market by Technology
11.3.1.8.2 Rest of Eastern Europe Cloud AI Market by Type
11.3.2 Western Europe
11.3.2.1 Western Europe Cloud AI Market by Country
11.3.2.2 Western Europe Cloud AI Market by Technology
11.3.2.3 Western Europe Cloud AI Market by Type
11.3.2.4 Germany
11.3.2.4.1 Germany Cloud AI Market by Technology
11.3.2.4.2 Germany Cloud AI Market by Type
11.3.2.5 France
11.3.2.5.1 France Cloud AI Market by Technology
11.3.2.5.2 France Cloud AI Market by Type
11.3.2.6 UK
11.3.2.6.1 UK Cloud AI Market by Technology
11.3.2.6.2 UK Cloud AI Market by Type
11.3.2.7 Italy
11.3.2.7.1 Italy Cloud AI Market by Technology
11.3.2.7.2 Italy Cloud AI Market by Type
11.3.2.8 Spain
11.3.2.8.1 Spain Cloud AI Market by Technology
11.3.2.8.2 Spain Cloud AI Market by Type
11.3.2.9 Netherlands
11.3.2.9.1 Netherlands Cloud AI Market by Technology
11.3.2.9.2 Netherlands Cloud AI Market by Type
11.3.2.10 Switzerland
11.3.2.11.1 Switzerland Cloud AI Market by Technology
11.3.2.11.2 Switzerland Cloud AI Market by Type
11.3.2.11 Austria
11.3.2.11.1 Austria Cloud AI Market by Technology
11.3.2.11.2 Austria Cloud AI Market by Type
11.3.2.12 Rest of Western Europe
11.3.2.12.1 Rest of Western Europe Cloud AI Market by Technology
11.3.2.12.2 Rest of Western Europe Cloud AI Market by Type
11.4 Asia-Pacific
11.4.1 Asia Pacific Cloud AI Market by Country
11.4.2 Asia Pacific Cloud AI Market by Technology
11.4.3 Asia Pacific Cloud AI Market by Type
11.4.4 China
11.4.4.1 China Cloud AI Market by Technology
11.4.4.2 China Cloud AI Market by Type
11.4.5 India
11.4.5.1 India Cloud AI Market by Technology
11.4.5.2 India Cloud AI Market by Type
11.4.6 Japan
11.4.6.1 Japan Cloud AI Market by Technology
11.4.6.2 Japan Cloud AI Market by Type
11.4.7 South Korea
11.4.7.1 South Korea Cloud AI Market by Technology
11.4.7.2 South Korea Cloud AI Market by Type
11.4.8 Vietnam
11.4.8.1 Vietnam Cloud AI Market by Technology
11.4.8.2 Vietnam Cloud AI Market by Type
11.4.9 Singapore
11.4.9.1 Singapore Cloud AI Market by Technology
11.4.9.2 Singapore Cloud AI Market by Type
11.4.10 Australia
11.4.11.1 Australia Cloud AI Market by Technology
11.4.11.2 Australia Cloud AI Market by Type
11.4.11 Rest of Asia-Pacific
11.4.11.1 Rest of Asia-Pacific Cloud AI Market by Technology
11.4.11.2 Rest of Asia-Pacific Cloud AI Market by Type
11.5 Middle East & Africa
11.5.1 Middle East
11.5.1.1 Middle East Cloud AI Market by Country
11.5.1.2 Middle East Cloud AI Market by Technology
11.5.1.3 Middle East Cloud AI Market by Type
11.5.1.4 UAE
11.5.1.4.1 UAE Cloud AI Market by Technology
11.5.1.4.2 UAE Cloud AI Market by Type
11.5.1.5 Egypt
11.5.1.5.1 Egypt Cloud AI Market by Technology
11.5.1.5.2 Egypt Cloud AI Market by Type
11.5.1.6 Saudi Arabia
11.5.1.6.1 Saudi Arabia Cloud AI Market by Technology
11.5.1.6.2 Saudi Arabia Cloud AI Market by Type
11.5.1.7 Qatar
11.5.1.7.1 Qatar Cloud AI Market by Technology
11.5.1.7.2 Qatar Cloud AI Market by Type
11.5.1.8 Rest of Middle East
11.5.1.8.1 Rest of Middle East Cloud AI Market by Technology
11.5.1.8.2 Rest of Middle East Cloud AI Market by Type
11.5.2 Africa
11.5.2.1 Africa Cloud AI Market by Country
11.5.2.2 Africa Cloud AI Market by Technology
11.5.2.3 Africa Cloud AI Market by Type
11.5.2.4 Nigeria
11.5.2.4.1 Nigeria Cloud AI Market by Technology
11.5.2.4.2 Nigeria Cloud AI Market by Type
11.5.2.5 South Africa
11.5.2.5.1 South Africa Cloud AI Market by Technology
11.5.2.5.2 South Africa Cloud AI Market by Type
11.5.2.6 Rest of Africa
11.5.2.6.1 Rest of Africa Cloud AI Market by Technology
11.5.2.6.2 Rest of Africa Cloud AI Market by Type
11.6 Latin America
11.6.1 Latin America Cloud AI Market by Country
11.6.2 Latin America Cloud AI Market by Technology
11.6.3 Latin America Cloud AI Market by Type
11.6.4 Brazil
11.6.4.1 Brazil Cloud AI Market by Technology
11.6.4.2 Brazil Africa Cloud AI Market by Type
11.6.5 Argentina
11.6.5.1 Argentina Cloud AI Market by Technology
11.6.5.2 Argentina Cloud AI Market by Type
11.6.6 Colombia
11.6.6.1 Colombia Cloud AI Market by Technology
11.6.6.2 Colombia Cloud AI Market by Type
11.6.7 Rest of Latin America
11.6.7.1 Rest of Latin America Cloud AI Market by Technology
11.6.7.2 Rest of Latin America Cloud AI Market by Type
12. Company Profile
12.1 Apple Inc.
12.1.1 Company Overview
12.1.2 Financials
12.1.3 Product/Services Offered
12.1.4 SWOT Analysis
12.1.5 The SNS View
12.2 Google, Inc.
12.2.1 Company Overview
12.2.2 Financials
12.2.3 Product/Services Offered
12.2.4 SWOT Analysis
12.2.5 The SNS View
12.3 IBM Corp.
12.3.1 Company Overview
12.3.2 Financials
12.3.3 Product/Services Offered
12.3.4 SWOT Analysis
12.3.5 The SNS View
12.4 Intel Corp.
12.4 Company Overview
12.4.2 Financials
12.4.3 Product/Services Offered
12.4.4 SWOT Analysis
12.4.5 The SNS View
12.5 Microsoft Corp.
12.5.1 Company Overview
12.5.2 Financials
12.5.3 Product/Services Offered
12.5.4 SWOT Analysis
12.5.5 The SNS View
12.6 MicroStrategy, Inc.
12.6.1 Company Overview
12.6.2 Financials
12.6.3 Product/Services Offered
12.6.4 SWOT Analysis
12.6.5 The SNS View
12.7 NVIDIA Corp.
12.7.1 Company Overview
12.7.2 Financials
12.7.3 Product/Services Offered
12.7.4 SWOT Analysis
12.7.5 The SNS View
12.8 Oracle Corp.
12.8.1 Company Overview
12.8.2 Financials
12.8.3 Product/Services Offered
12.8.4 SWOT Analysis
12.8.5 The SNS View
12.9 Qlik Technologies, Inc.
12.9.1 Company Overview
12.9.2 Financials
12.9.3 Product/ Services Offered
12.9.4 SWOT Analysis
12.9.5 The SNS View
12.10 Salesforce.com Inc.
12.10.1 Company Overview
12.10.2 Financials
12.10.3 Product/Services Offered
12.10.4 SWOT Analysis
12.10.5 The SNS View
12.11 ZTE Corp.
12.12.1 Company Overview
12.12.2 Financials
12.12.3 Product/Services Offered
12.12.4 SWOT Analysis
12.12.5 The SNS View
13. Competitive Landscape
13.1 Competitive Benchmarking
13.2 Market Share Analysis
13.3 Recent Developments
13.3.1 Industry News
13.3.2 Company News
13.3.3 Mergers & Acquisitions
14. USE Cases and Best Practices
15. Conclusion
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By Technology
Deep Learning
Machine Learning
Others
By Type
Solution
Services
By Vertical
Healthcare
Retail
BFSI
IT & Telecommunication
Government
Manufacturing
Automotive & Transportation
Others
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Regional Coverage:
North America
US
Canada
Mexico
Europe
Eastern Europe
Poland
Romania
Hungary
Turkey
Rest of Eastern Europe
Western Europe
Germany
France
UK
Italy
Spain
Netherlands
Switzerland
Austria
Rest of Western Europe
Asia Pacific
China
India
Japan
South Korea
Vietnam
Singapore
Australia
Rest of Asia Pacific
Middle East & Africa
Middle East
UAE
Egypt
Saudi Arabia
Qatar
Rest of Middle East
Africa
Nigeria
South Africa
Rest of Africa
Latin America
Brazil
Argentina
Colombia
Rest of Latin America
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