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Report Scope & Overview:

AI Cloud Market size was valued at USD 44.9 billion in 2022 and is expected to grow to USD 651.35 billion by 2030 and grow at a CAGR of 39.7% over the forecast period of 2023-2030.

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.

AI Cloud Market Revenue Analysis

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.

KEY DRIVERS: 

  • 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

IMPACT ANALYSIS

IMPACT OF RUSSIAN UKRAINE WAR

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.

MARKET SEGMENTATION

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

AI Cloud Market Segmentation Analysis

REGIONAL ANALYSIS

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.

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

KEY PLAYERS

Some of key players of AI Cloud Market 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.

Apple Inc-Company Financial Analysis

RECENT DEVELOPMENT

  • 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.

    AI Cloud Market Report Scope:
    Report Attributes Details

    Market Size in 2022

     US$ 44.9 billion 

    Market Size by 2030

     US$ 651.35 billion 

    CAGR 

     CAGR of 39.7%   From 2023 to 2030

    Base Year

    2022

    Forecast Period

     2023-2030

    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

     

 

Frequently Asked Questions

Increasing use of cloud-based services and apps & Growing utilization of cloud-based services and apps.

 Technological Advancement

 North America is dominating the AI Cloud Market.

AI Cloud Market size was valued at USD 44.9 billion in 2022

AI Cloud Market is anticipated to expand by 39.7% from 2023 to 2030.

TABLE OF CONTENT

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. AI Cloud Market Segmentation, By Technology 
8.1    Deep Learning
8.2    Machine Learning
8.3    Natural Language Processing
8.4    Others

9. AI Cloud Market Segmentation, By Type
9.1    Solution
9.2    Services
9.3    Vertical Outlook (Revenue, USD Million, 2017 - 2030)
9.4    Healthcare
9.5    Retail
9.6    BFSI
9.7    IT & Telecommunication
9.8    Government
9.9    Manufacturing
9.10 Automotive & Transportation
9.11 Others

10. Regional Analysis
10.1 Introduction
10.2 North America
10.2.1 North America AI Cloud Market by Country
10.2.2North America AI Cloud Market by Technology
10.2.3 North America AI Cloud Market by Type
10.2.4 USA
10.2.4.1 USA AI Cloud Market by Technology
10.2.4.2 USA AI Cloud Market by Type
10.2.5 Canada
10.2.5.1 Canada AI Cloud Market by Technology
10.2.5.2 Canada AI Cloud Market by Type
10.2.6 Mexico
10.2.6.1 Mexico AI Cloud Market by Technology
10.2.6.2 Mexico AI Cloud Market by Type
10.3 Europe
10.3.1 Eastern Europe
10.3.1.1 Eastern Europe AI Cloud Market by Country
10.3.1.2 Eastern Europe AI Cloud Market by Technology
10.3.1.3 Eastern Europe AI Cloud Market by Type
10.3.1.4 Poland
10.3.1.4.1 Poland AI Cloud Market by Technology
10.3.1.4.2 Poland AI Cloud Market by Type
10.3.1.5 Romania
10.3.1.5.1 Romania AI Cloud Market by Technology
10.3.1.5.2 Romania AI Cloud Market by Type
10.3.1.6 Hungary
10.3.1.6.1 Hungary AI Cloud Market by Technology
10.3.1.6.2 Hungary AI Cloud Market by Type
10.3.1.7 Turkey
10.3.1.7.1 Turkey AI Cloud Market by Technology
10.3.1.7.2 Turkey AI Cloud Market by Type
10.3.1.8 Rest of Eastern Europe
10.3.1.8.1 Rest of Eastern Europe AI Cloud Market by Technology
10.3.1.8.2 Rest of Eastern Europe AI Cloud Market by Type
10.3.2 Western Europe
10.3.2.1 Western Europe AI Cloud Market by Country
10.3.2.2 Western Europe AI Cloud Market by Technology
10.3.2.3 Western Europe AI Cloud Market by Type
10.3.2.4 Germany
10.3.2.4.1 Germany AI Cloud Market by Technology
10.3.2.4.2 Germany AI Cloud Market by Type
10.3.2.5 France
10.3.2.5.1 France AI Cloud Market by Technology
10.3.2.5.2 France AI Cloud Market by Type
10.3.2.6 UK
10.3.2.6.1 UK AI Cloud Market by Technology
10.3.2.6.2 UK AI Cloud Market by Type
10.3.2.7 Italy
10.3.2.7.1 Italy AI Cloud Market by Technology
10.3.2.7.2 Italy AI Cloud Market by Type
10.3.2.8 Spain
10.3.2.8.1 Spain AI Cloud Market by Technology
10.3.2.8.2 Spain AI Cloud Market by Type
10.3.2.9 Netherlands
10.3.2.9.1 Netherlands AI Cloud Market by Technology
10.3.2.9.2 Netherlands AI Cloud Market by Type
10.3.2.10 Switzerland
10.3.2.10.1 Switzerland AI Cloud Market by Technology
10.3.2.10.2 Switzerland AI Cloud Market by Type
10.3.2.11 Austria
10.3.2.11.1 Austria AI Cloud Market by Technology
10.3.2.11.2 Austria AI Cloud Market by Type
10.3.2.12 Rest of Western Europe
10.3.2.12.1 Rest of Western Europe AI Cloud Market by Technology
10.3.2.12.2 Rest of Western Europe AI Cloud Market by Type
10.4 Asia-Pacific
10.4.1 Asia Pacific AI Cloud Market by Country
10.4.2 Asia Pacific AI Cloud Market by Technology
10.4.3 Asia Pacific AI Cloud Market by Type
10.4.4 China
10.4.4.1 China AI Cloud Market by Technology
10.4.4.2 China AI Cloud Market by Type
10.4.5 India
10.4.5.1 India AI Cloud Market by Technology
10.4.5.2 India AI Cloud Market by Type
10.4.6 Japan
10.4.6.1 Japan AI Cloud Market by Technology
10.4.6.2 Japan AI Cloud Market by Type
10.4.7 South Korea
10.4.7.1 South Korea AI Cloud Market by Technology
10.4.7.2 South Korea AI Cloud Market by Type
10.4.8 Vietnam
10.4.8.1 Vietnam AI Cloud Market by Technology
10.4.8.2 Vietnam AI Cloud Market by Type
10.4.9 Singapore
10.4.9.1 Singapore AI Cloud Market by Technology
10.4.9.2 Singapore AI Cloud Market by Type
10.4.10 Australia
10.4.10.1 Australia AI Cloud Market by Technology
10.4.10.2 Australia AI Cloud Market by Type
10.4.11 Rest of Asia-Pacific
10.4.11.1 Rest of Asia-Pacific AI Cloud Market by Technology
10.4.11.2 Rest of Asia-Pacific AI Cloud Market by Type
10.5 Middle East & Africa
10.5.1 Middle East
10.5.1.1 Middle East AI Cloud Market by Country
10.5.1.2 Middle East AI Cloud Market by Technology
10.5.1.3 Middle East AI Cloud Market by Type
10.5.1.4 UAE
10.5.1.4.1 UAE AI Cloud Market by Technology
10.5.1.4.2 UAE AI Cloud Market by Type
10.5.1.5 Egypt
10.5.1.5.1 Egypt AI Cloud Market by Technology
10.5.1.5.2 Egypt AI Cloud Market by Type
10.5.1.6 Saudi Arabia
10.5.1.6.1 Saudi Arabia AI Cloud Market by Technology
10.5.1.6.2 Saudi Arabia AI Cloud Market by Type
10.5.1.7 Qatar
10.5.1.7.1 Qatar AI Cloud Market by Technology
10.5.1.7.2 Qatar AI Cloud Market by Type
10.5.1.8 Rest of Middle East
10.5.1.8.1 Rest of Middle East AI Cloud Market by Technology
10.5.1.8.2 Rest of Middle East AI Cloud Market by Type
10.5.2 Africa
10.5.2.1 Africa AI Cloud Market by Country
10.5.2.2 Africa AI Cloud Market by Technology
10.5.2.3 Africa AI Cloud Market by Type
10.5.2.4 Nigeria
10.5.2.4.1 Nigeria AI Cloud Market by Technology
10.5.2.4.2 Nigeria AI Cloud Market by Type
10.5.2.5 South Africa
10.5.2.5.1 South Africa AI Cloud Market by Technology
10.5.2.5.2 South Africa AI Cloud Market by Type
10.5.2.6 Rest of Africa
10.5.2.6.1 Rest of Africa AI Cloud Market by Technology
10.5.2.6.2 Rest of Africa AI Cloud Market by Type
10.6 Latin America
10.6.1 Latin America AI Cloud Market by Country
10.6.2 Latin America AI Cloud Market by Technology
10.6.3 Latin America AI Cloud Market by Type
10.6.4 Brazil
10.6.4.1 Brazil AI Cloud Market by Technology
10.6.4.2 Brazil Africa AI Cloud Market by Type
10.6.5 Argentina
10.6.5.1 Argentina AI Cloud Market by Technology
10.6.5.2 Argentina AI Cloud Market by Type
10.6.6 Colombia
10.6.6.1 Colombia AI Cloud Market by Technology
10.6.6.2 Colombia AI Cloud Market by Type
10.6.7 Rest of Latin America
10.6.7.1 Rest of Latin America AI Cloud Market by Technology
10.6.7.2 Rest of Latin America AI Cloud Market by Type

11 Company Profile
11.1 Apple Inc.
11.1.1 Company Overview
11.1.2 Financials
11.1.3 Product/Services Offered
11.1.4 SWOT Analysis
11.1.5 The SNS View
11.2 Google, Inc.
11.2.1 Company Overview
11.2.2 Financials
11.2.3 Product/Services Offered
11.2.4 SWOT Analysis
11.2.5 The SNS View
11.3 IBM Corp.
11.3.1 Company Overview
11.3.2 Financials
11.3.3 Product/Services Offered
11.3.4 SWOT Analysis
11.3.5 The SNS View
11.4 Intel Corp.
11.4 Company Overview
11.4.2 Financials
11.4.3 Product/Services Offered
11.4.4 SWOT Analysis
11.4.5 The SNS View
11.5 Microsoft Corp.
11.5.1 Company Overview
11.5.2 Financials
11.5.3 Product/Services Offered
11.5.4 SWOT Analysis
11.5.5 The SNS View
11.6 MicroStrategy, Inc.
11.6.1 Company Overview
11.6.2 Financials
11.6.3 Product/Services Offered
11.6.4 SWOT Analysis
11.6.5 The SNS View
11.7 NVIDIA Corp.
11.7.1 Company Overview
11.7.2 Financials
11.7.3 Product/Services Offered
11.7.4 SWOT Analysis
11.7.5 The SNS View
11.8 Oracle Corp.
11.8.1 Company Overview
11.8.2 Financials
11.8.3 Product/Services Offered
11.8.4 SWOT Analysis
11.8.5 The SNS View
11.9 Qlik Technologies, Inc.
11.9.1 Company Overview
11.9.2 Financials
11.9.3 Product/ Services Offered
11.9.4 SWOT Analysis
11.9.5 The SNS View
11.10 Salesforce.com Inc.
11.10.1 Company Overview
11.10.2 Financials
11.10.3 Product/Services Offered
11.10.4 SWOT Analysis
11.10.5 The SNS View
11.11 ZTE Corp.
11.11.1 Company Overview
11.11.2 Financials
11.11.3 Product/Services Offered
11.11.4 SWOT Analysis
11.11.5 The SNS View

12. Competitive Landscape
12.1 Competitive Bench marking
12.2 Market Share Analysis
12.3 Recent Developments
12.3.1 Industry News
12.3.2 Company News
12.3.3 Mergers & Acquisitions

13. USE Cases and Best Practices

14. Conclusion

An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.

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The 5 steps process:

Step 1: Secondary Research:

Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.

Secondary Research

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Primary Research

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Data Bank Validation

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