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Global Enterprise Artificial Intelligence Market to reach USD 91.25 billion by 2028.

Global Enterprise Artificial Intelligence Market Size study, by Deployment (Cloud, On-premises) by Technology (Natural Language Processing (NLP), Machine Learning, Computer Vision, Speech Recognition, Others) by Organization (Large Enterprises, Small And Medium Enterprises) by End-use (Media & Advertising, Retail, BFSI, IT & Telecom, Healthcare, Automotive & Transportation, Others) and Regional Forecasts 2022-2028

Product Code: ICTEITS-92662061
Publish Date: 14-08-2022
Page: 200

Global Enterprise Artificial Intelligence Market is valued approximately USD 11.4 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 34.6% over the forecast period 2022-2028. Factors such as increased demand for virtual assistants, chatbots, and robots from different organizations, as well as the increasing requirement to evaluate exponentially larger data volumes, are driving enterprise demand for artificial intelligence. Furthermore, the transition of firms from conventional to digital platforms is increasing demand for artificial intelligence technologies in enterprises throughout the world. The rising usage of artificial intelligence in organizations to improve customer happiness, offer better organizational management, and organize data sets is one of the primary factors driving demand for artificial intelligence in enterprises. To meet the market’s expanding need for AI, multiple AI service providers are inventing and creating new goods and services in collaboration with various government institutes and research and development agencies. For example, in May 2022, IBM Corporation announced a strategic relationship with Mohamed bin Zayed Institution of Artificial Intelligence (MBZUAI), the first artificial intelligence research university in Abu Dhabi, United Arab Emirates (UAE). The partnership focuses on the progress of fundamental AI research as well as the acceleration of other sorts of scientific discoveries that would increase AI’s capacity to assist overcome future difficulties. The rising need for artificial intelligence technologies in emerging nations presents a substantial potential for corporate AI service providers. According to a study published in June 2020 by MIT Technology in collaboration with the United States-based software company Genesys, artificial intelligence (AI) is providing growth opportunities in the Latin American region by assisting in the resolution of numerous critical issues such as food security, unemployment, smart cities, and natural resources. However, the high cost of Enterprise Artificial Intelligence restrains market growth from 2022 to 2028.

The key regions considered for the Global Enterprise Artificial Intelligence Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America dominated in terms of revenue. The presence of prominent firms that produce AI solutions and services, technological infrastructure facilities, and a large number of end-users using data management devices are pushing the market in the area. During the projection period, Asia-Pacific is predicted to have the quickest CAGR. The rising acceptance of AI and the installation of data management platforms that address concerns such as privacy and security, team collaboration, and the formation of moral standards for organizations may be ascribed to regional growth.

Major market player included in this report are:
Amazon Web Services, Inc.
IBM Corporation
Microsoft Corporation
Oracle Corporation
Intel Corporation
Alphabet Inc.
SAP SE
C3.ai, Inc.
DataRobot, Inc.
Hewlett Packard Enterprise Development LP
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 eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available 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 Deployment:
Cloud
On-premises
By Technology:
Natural Language Processing (NLP)
Machine Learning
Computer Vision
Speech Recognition
Others
By Organization:
Large Enterprises
Small And Medium Enterprises

By End-use:
Media & Advertising
Retail
BFSI
IT & Telecom
Healthcare
Automotive & Transportation
Others

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
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Enterprise Artificial Intelligence Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Billion)
1.2.1. Enterprise Artificial Intelligence Market, by Region, 2020-2028 (USD Billion)
1.2.2. Enterprise Artificial Intelligence Market, by Deployment, 2020-2028 (USD Billion)
1.2.3. Enterprise Artificial Intelligence Market, by Technology, 2020-2028 (USD Billion)
1.2.4. Enterprise Artificial Intelligence Market, by Organization, 2020-2028 (USD Billion)
1.2.5. Enterprise Artificial Intelligence Market, by End-use, 2020-2028 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Enterprise Artificial Intelligence Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Enterprise Artificial Intelligence Market Dynamics
3.1. Enterprise Artificial Intelligence Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Growing demand for virtual assistants, chatbots, and robots
3.1.1.2. Increasing need to analyzeanalyse exponentially growing demand for data sets
3.1.2. Market Challenges
3.1.2.1. Threat of Cyber Attacks
3.1.3. Market Opportunities
3.1.3.1. Increasing Technological Advancements
Chapter 4. Global Enterprise Artificial Intelligence 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
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Enterprise Artificial Intelligence Market, by Deployment
6.1. Market Snapshot
6.2. Global Enterprise Artificial Intelligence Market by Deployment, Performance – Potential Analysis
6.3. Global Enterprise Artificial Intelligence Market Estimates & Forecasts by Deployment 2018-2028 (USD Billion)
6.4. Enterprise Artificial Intelligence Market, Sub Segment Analysis
6.4.1. Cloud
6.4.2. On-premises
Chapter 7. Global Enterprise Artificial Intelligence Market, by Technology
7.1. Market Snapshot
7.2. Global Enterprise Artificial Intelligence Market by Technology, Performance – Potential Analysis
7.3. Global Enterprise Artificial Intelligence Market Estimates & Forecasts by Technology 2018-2028 (USD Billion)
7.4. Enterprise Artificial Intelligence Market, Sub Segment Analysis
7.4.1. Natural Language Processing (NLP)
7.4.2. Machine Learning
7.4.3. Computer Vision
7.4.4. Speech Recognition
7.4.5. Others
Chapter 8. Global Enterprise Artificial Intelligence Market, by Organization
8.1. Market Snapshot
8.2. Global Enterprise Artificial Intelligence Market by Organization, Performance – Potential Analysis
8.3. Global Enterprise Artificial Intelligence Market Estimates & Forecasts by Organization 2018-2028 (USD Billion)
8.4. Enterprise Artificial Intelligence Market, Sub Segment Analysis
8.4.1. Large Enterprises
8.4.2. Small And Medium Enterprises
Chapter 9. Global Enterprise Artificial Intelligence Market, by End-use
9.1. Market Snapshot
9.2. Global Enterprise Artificial Intelligence Market by End-use, Performance – Potential Analysis
9.3. Global Enterprise Artificial Intelligence Market Estimates & Forecasts by End-use 2018-2028 (USD Billion)
9.4. Enterprise Artificial Intelligence Market, Sub Segment Analysis
9.4.1. Media & Advertising
9.4.2. Retail
9.4.3. BFSI
9.4.4. IT & Telecom
9.4.5. Healthcare
9.4.6. Automotive & Transportation
9.4.7. Others
Chapter 10. Global Enterprise Artificial Intelligence Market, Regional Analysis
10.1. Enterprise Artificial Intelligence Market, Regional Market Snapshot
10.2. North America Enterprise Artificial Intelligence Market
10.2.1. U.S. Enterprise Artificial Intelligence Market
10.2.1.1. Deployment breakdown estimates & forecasts, 2018-2028
10.2.1.2. Technology breakdown estimates & forecasts, 2018-2028
10.2.1.3. Organization breakdown estimates & forecasts, 2018-2028
10.2.1.4. End-use breakdown estimates & forecasts, 2018-2028
10.2.2. Canada Enterprise Artificial Intelligence Market
10.3. Europe Enterprise Artificial Intelligence Market Snapshot
10.3.1. U.K. Enterprise Artificial Intelligence Market
10.3.2. Germany Enterprise Artificial Intelligence Market
10.3.3. France Enterprise Artificial Intelligence Market
10.3.4. Spain Enterprise Artificial Intelligence Market
10.3.5. Italy Enterprise Artificial Intelligence Market
10.3.6. Rest of Europe Enterprise Artificial Intelligence Market
10.4. Asia-Pacific Enterprise Artificial Intelligence Market Snapshot
10.4.1. China Enterprise Artificial Intelligence Market
10.4.2. India Enterprise Artificial Intelligence Market
10.4.3. Japan Enterprise Artificial Intelligence Market
10.4.4. Australia Enterprise Artificial Intelligence Market
10.4.5. South Korea Enterprise Artificial Intelligence Market
10.4.6. Rest of Asia Pacific Enterprise Artificial Intelligence Market
10.5. Latin America Enterprise Artificial Intelligence Market Snapshot
10.5.1. Brazil Enterprise Artificial Intelligence Market
10.5.2. Mexico Enterprise Artificial Intelligence Market
10.6. Rest of The World Enterprise Artificial Intelligence Market

Chapter 11. Competitive Intelligence
11.1. Top Market Strategies
11.2. Company Profiles
11.2.1. Amazon Web Services, Inc.
11.2.1.1. Key Information
11.2.1.2. Overview
11.2.1.3. Financial (Subject to Data Availability)
11.2.1.4. Deployment Summary
11.2.1.5. Recent Developments
11.2.2. IBM Corporation
11.2.3. Microsoft Corporation
11.2.4. Oracle Corporation
11.2.5. Intel Corporation
11.2.6. Alphabet Inc.
11.2.7. SAP SE
11.2.8. C3.ai, Inc.
11.2.9. DataRobot, Inc.
11.2.10. Hewlett Packard Enterprise Development LPs
Chapter 12. Research Process
12.1. Research Process
12.1.1. Data Mining
12.1.2. Analysis
12.1.3. Market Estimation
12.1.4. Validation
12.1.5. Publishing
12.2. Research Attributes
12.3. 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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