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Global Cloud AI Market to reach USD xx billion by the end of 2029.

Global Cloud AI Market Size study & Forecast, by Technology (Deep Learning, Machine Learning, Natural Language Processing, Others), by Type (Solution, Services), by Vertical (Healthcare, Retail, BFSI, IT & Telecommunication, Government, Manufacturing and Others) and Regional Analysis, 2023-2030

Product Code: ICTBC-87051036
Publish Date: 10-06-2023
Page: 200

Global Cloud AI Market is valued at approximately USD xx billion in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2029. Cloud AI refers to the use of cloud computing resources, such as processing power, storage, and algorithms, to train and deploy artificial intelligence (AI) models. It allows individuals and organizations to access AI capabilities without needing to invest in expensive hardware or maintain complex software infrastructures. The Cloud AI Market is expanding because of factors such as rising big data volume and increasing demand for virtual assistants.

The increased demand for cloud-based intelligence services and the trend towards multi-cloud operation both contribute to this increase. According to IBM, in the year 2021 multi-cloud architectures are being used by 98% of the organizations. Just 41% of businesses have a multi-cloud management strategy, and 38% have the processes and tools necessary to manage a multi-cloud environment. This has the potential to enormously expand the market for cloud AI services. Moreover, according to a recent IDC report, nearly 80% of corporate banks in India are expected to operate their trade finance and treasury workloads on Cloud based technology by 2024. Thus, the rising adoption of the cloud is driving market growth. In addition, the growing Adoption of Cloud-based Services and rising adoption of digital services applications is creating lucrative growth in the market. However, the high cost of Cloud AI and lack of Skilled Workforce and Data Security Concerns stifles market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Cloud AI Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America dominated the market in terms of revenue, owing to the dominance of key market players and rising technological advancements in the region. Whereas Asia Pacific is expected to grow with the highest CAGR during the forecast period, owing to factors such as the rising demand from end-use industry, rising adoption of cloud services and rising initiatives to adopt new technologies in the region.

Major market player included in this report are:
Amazon Web Services Inc.
Microsoft Corporation
Google LLC
International Business Machines Corporation
Infosys Limited
Wipro Limited
Cloudminds Technology Inc.
AIBrain Inc.
Salesforce Inc.
SoundHound AI, Inc.

Recent Developments in the Market:
Ø In May 2022, Huawei Technologies (Malaysia) Sdn Bhd and ToGL Technology Sdn Bhd formally joined forces to develop cloud-based digital solutions in Malaysia. The collaboration includes contemporary cloud and AI services and experiences,

Global Insulin Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Technology, Type, Vertical, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Technology:
Deep Learning
Machine Learning
Natural Language Processing
By Type:
By Vertical:
IT & Telecommunication

By Region:

North America


Asia Pacific
South Korea

Latin America

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Cloud AI Market, by Region, 2020-2030 (USD Billion)
1.2.2. Cloud AI Market, by Technology, 2020-2030 (USD Billion)
1.2.3. Cloud AI Market, by Type, 2020-2030 (USD Billion)
1.2.4. Cloud AI Market, by Vertical, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Cloud AI Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Cloud AI Market Dynamics
3.1. Cloud AI Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Rising Big Data Volume Increasing Demand for Virtual Assistants
3.1.2. Market Challenges Lack of Skilled Workforce and Data Security Concerns
3.1.3. Market Opportunities Growing Adoption of Cloud-based Service and Application Rising adoption of digital services
Chapter 4. Global Cloud AI Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Cloud AI Market, by Technology
5.1. Market Snapshot
5.2. Global Cloud AI Market by Technology, Performance – Potential Analysis
5.3. Global Cloud AI Market Estimates & Forecasts by Technology 2020-2030 (USD Billion)
5.4. Cloud AI Market, Sub Segment Analysis
5.4.1. Deep Learning
5.4.2. Machine Learning
5.4.3. Natural Language Processing
5.4.4. Others
Chapter 6. Global Cloud AI Market, by Type
6.1. Market Snapshot
6.2. Global Cloud AI Market by Type, Performance – Potential Analysis
6.3. Global Cloud AI Market Estimates & Forecasts by Type 2020-2030 (USD Billion)
6.4. Cloud AI Market, Sub Segment Analysis
6.4.1. Solution
6.4.2. Services
Chapter 7. Global Cloud AI Market, by Vertical
7.1. Market Snapshot
7.2. Global Cloud AI Market by Vertical, Performance – Potential Analysis
7.3. Global Cloud AI Market Estimates & Forecasts by Vertical 2020-2030 (USD Billion)
7.4. Cloud AI Market, Sub Segment Analysis
7.4.1. Healthcare
7.4.2. Retail
7.4.3. BFSI
7.4.4. IT & Telecommunication
7.4.5. Government
7.4.6. Manufacturing
7.4.7. Others
Chapter 8. Global Cloud AI Market, Regional Analysis
8.1. Top Leading Countries
8.2. Top Emerging Countries
8.3. Cloud AI Market, Regional Market Snapshot
8.4. North America Cloud AI Market
8.4.1. U.S. Cloud AI Market Technology breakdown estimates & forecasts, 2020-2030 Type breakdown estimates & forecasts, 2020-2030 Vertical breakdown estimates & forecasts, 2020-2030
8.4.2. Canada Cloud AI Market
8.5. Europe Cloud AI Market Snapshot
8.5.1. U.K. Cloud AI Market
8.5.2. Germany Cloud AI Market
8.5.3. France Cloud AI Market
8.5.4. Spain Cloud AI Market
8.5.5. Italy Cloud AI Market
8.5.6. Rest of Europe Cloud AI Market
8.6. Asia-Pacific Cloud AI Market Snapshot
8.6.1. China Cloud AI Market
8.6.2. India Cloud AI Market
8.6.3. Japan Cloud AI Market
8.6.4. Australia Cloud AI Market
8.6.5. South Korea Cloud AI Market
8.6.6. Rest of Asia Pacific Cloud AI Market
8.7. Latin America Cloud AI Market Snapshot
8.7.1. Brazil Cloud AI Market
8.7.2. Mexico Cloud AI Market
8.8. Middle East & Africa Cloud AI Market
8.8.1. Saudi Arabia Cloud AI Market
8.8.2. South Africa Cloud AI Market
8.8.3. Rest of Middle East & Africa Cloud AI Market

Chapter 9. Competitive Intelligence
9.1. Key Company SWOT Analysis
9.1.1. Company 1
9.1.2. Company 2
9.1.3. Company 3
9.2. Top Market Strategies
9.3. Company Profiles
9.3.1. Amazon Web Services Inc. Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
9.3.2. Microsoft Corporation
9.3.3. Google LLC
9.3.4. International Business Machines Corporation
9.3.5. Infosys Limited
9.3.6. Wipro Limited
9.3.7. Cloudminds Technology Inc
9.3.8. AIBrain Inc,
9.3.9. Salesforce Inc.
9.3.10. SoundHound AI, Inc.
Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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