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Global Artificial Intelligence as a Service Market to reach USD 43.29 billion by the end of 2030.

Global Artificial Intelligence as a Service Market Size study & Forecast, by Technology (Deep Learning, Machine Learning, Natural Language Processing) By Vertical (Government, BFSI, Healthcare, Manufacturing, Retail, Telecommunication) and Regional Analysis, 2023-2030

Product Code: ICTNGT-83592264
Publish Date: 4-10-2023
Page: 200

Global Artificial Intelligence as a Service Market is valued approximately at USD 6.90 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 25.8% over the forecast period 2023-2030. Artificial Intelligence as a Service refers to the provision of artificial intelligence (AI) capabilities and functionalities as cloud-based services. It allows individuals and organizations to access and utilize AI technologies without the need for extensive infrastructure or expertise in AI development. The Artificial Intelligence as a Service market is expanding because of factors such as rising demand of automation and increasing adoption of IoT devices. its importance has progressively increased during the forecast period 2023-2030.

According to Statista, in 2020, the global industrial automation industry accounts approximately USD 175 billion and the market is projected to grow at a compound annual growth rate of roughly 9% worth approximately USD 265 billion by 2025. Furthermore, the global intelligent process automation market accounted for USD 20 billion in 2021, rising at a compound annual growth rate of 16% to reach about USD 30 billion by year 2024. Another important factor driving the Artificial Intelligence as a Service market is increasing adoption of IoT devices. Artificial Intelligence offers a range of services, such as machine learning, natural language processing, computer vision, and data analytics. These services are made available through application programming interfaces that developers can integrate into their own applications or systems. In addition, as per Statista, the global number of Internet of Things devices is expected to nearly triple from 9.7 billion in 2020 to more than 29 billion in 2030. China will witness the most IoT devices with roughly 5 billion consumer devices by 2030. Moreover, rising technological advancement on AI and machine learning and growing adoption of 5G network infrastructure is anticipated to create a lucrative growth opportunity for the market over the forecast period. However, high cost associated to Artificial Intelligence techniques and technical complexity stifles market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Artificial Intelligence as a Service Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 with largest market share owing to the increasing presence of leading AI companies, including Google, Microsoft, IBM, and Amazon, which have been investing heavily in AI research and development. Furthermore, Asia Pacific is expected to be the fastest growing during the forecast period, owing to factors such as increasing adoption of 5G network infrastructure and growing automation in various end use industries.

Major market player included in this report are:
IBM Corporation
Google Inc.
Amazon Web Service
Microsoft Corporation
Salesforce Inc
Baidu Inc
SAP SE
Intel Corporation
Fair Isaac Corporation (FICO)
BigML Inc

Recent Developments in the Market:
Ø In June 2023, Amazon Web Services has invested USD 100 million in the new AWS Generative AI Innovation Centre, which is intended to “help customers across numerous industries make better use of advancements in machine learning and automation, and scope high-value use cases based on best practises and industry expertise.” The effort will eventually connect the cloud provider’s machine learning (ML) and artificial intelligence (AI) experts with clients and partners worldwide.

Global Artificial Intelligence as a Service 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, 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 Vertical
Government
BFSI
Healthcare
Manufacturing
Retail
Telecommunication

By Region:

North America
U.S.
Canada

Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC

Latin America
Brazil
Mexico

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. Artificial Intelligence as a Service Market, by region, 2020-2030 (USD Billion)
1.2.2. Artificial Intelligence as a Service Market, by Technology, 2020-2030 (USD Billion)
1.2.3. Artificial Intelligence as a Service Market, by Vertical, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Artificial Intelligence as a Service 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 Artificial Intelligence as a Service Market Dynamics
3.1. Artificial Intelligence as a Service Market Impact Analysis (2020-2030)
3.1.1. Market Drivers
3.1.1.1. Rising demand for automation
3.1.1.2. Increasing adoption of IoT devices
3.1.2. Market Challenges
3.1.2.1. High Cost Associated to Artificial Intelligence Techniques
3.1.2.2. Technical Complexity
3.1.3. Market Opportunities
3.1.3.1. Rising technological advancement on AI and machine learning
3.1.3.2. Growing adoption of 5G network infrastructure
Chapter 4. Global Artificial Intelligence as a Service 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. Economic
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 Artificial Intelligence as a Service Market, by Technology
5.1. Market Snapshot
5.2. Global Artificial Intelligence as a Service Market by Technology, Performance – Potential Analysis
5.3. Global Artificial Intelligence as a Service Market Estimates & Forecasts by Technology 2020-2030 (USD Billion)
5.4. Artificial Intelligence as a Service Market, Sub Segment Analysis
5.4.1. Deep Learning
5.4.2. Machine Learning
5.4.3. Natural Language Processing
Chapter 6. Global Artificial Intelligence as a Service Market, by Vertical
6.1. Market Snapshot
6.2. Global Artificial Intelligence as a Service Market by Vertical, Performance – Potential Analysis
6.3. Global Artificial Intelligence as a Service Market Estimates & Forecasts by Vertical 2020-2030 (USD Billion)
6.4. Artificial Intelligence as a Service Market, Sub Segment Analysis
6.4.1. Government
6.4.2. BFSI
6.4.3. Healthcare
6.4.4. Manufacturing
6.4.5. Retail
6.4.6. Telecommunication
Chapter 7. Global Artificial Intelligence as a Service Market, Regional Analysis
7.1. Top Leading Countries
7.2. Top Emerging Countries
7.3. Artificial Intelligence as a Service Market, Regional Market Snapshot
7.4. North America Artificial Intelligence as a Service Market
7.4.1. U.S. Artificial Intelligence as a Service Market
7.4.1.1. Technology breakdown estimates & forecasts, 2020-2030
7.4.1.2. Vertical breakdown estimates & forecasts, 2020-2030
7.4.2. Canada Artificial Intelligence as a Service Market
7.5. Europe Artificial Intelligence as a Service Market Snapshot
7.5.1. U.K. Artificial Intelligence as a Service Market
7.5.2. Germany Artificial Intelligence as a Service Market
7.5.3. France Artificial Intelligence as a Service Market
7.5.4. Spain Artificial Intelligence as a Service Market
7.5.5. Italy Artificial Intelligence as a Service Market
7.5.6. Rest of Europe Artificial Intelligence as a Service Market
7.6. Asia-Pacific Artificial Intelligence as a Service Market Snapshot
7.6.1. China Artificial Intelligence as a Service Market
7.6.2. India Artificial Intelligence as a Service Market
7.6.3. Japan Artificial Intelligence as a Service Market
7.6.4. Australia Artificial Intelligence as a Service Market
7.6.5. South Korea Artificial Intelligence as a Service Market
7.6.6. Rest of Asia Pacific Artificial Intelligence as a Service Market
7.7. Latin America Artificial Intelligence as a Service Market Snapshot
7.7.1. Brazil Artificial Intelligence as a Service Market
7.7.2. Mexico Artificial Intelligence as a Service Market
7.8. Middle East & Africa Artificial Intelligence as a Service Market
7.8.1. Saudi Arabia Artificial Intelligence as a Service Market
7.8.2. South Africa Artificial Intelligence as a Service Market
7.8.3. Rest of Middle East & Africa Artificial Intelligence as a Service Market

Chapter 8. Competitive Intelligence
8.1. Key Company SWOT Analysis
8.1.1. Company 1
8.1.2. Company 2
8.1.3. Company 3
8.2. Top Market Strategies
8.3. Company Profiles
8.3.1. IBM Corporation
8.3.1.1. Key Information
8.3.1.2. Overview
8.3.1.3. Financial (Subject to Data Availability)
8.3.1.4. Product Summary
8.3.1.5. Recent Developments
8.3.2. Google Inc.
8.3.3. Amazon Web Service
8.3.4. Microsoft Corporation
8.3.5. Salesforce Inc
8.3.6. Baidu Inc
8.3.7. SAP SE
8.3.8. Intel Corporation
8.3.9. Fair Isaac Corporation (FICO)
8.3.10. BigML Inc
Chapter 9. Research Process
9.1. Research Process
9.1.1. Data Mining
9.1.2. Analysis
9.1.3. Market Estimation
9.1.4. Validation
9.1.5. Publishing
9.2. Research Attributes
9.3. 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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