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Global AI Orchestration Market to reach USD 47.71 billion by 2032.

Global AI Orchestration Market Size study, by Component (Solution, Services), by Deployment Mode (On-Premise, Cloud), by Application (Customer Service Orchestration, Infrastructure Orchestration, Manufacturing Orchestration, Workflow Orchestration, Others), by Organization Size (Large Enterprises, Small and Medium-sized Enterprises), by Industry Vertical (IT and Telecommunications, Manufacturing, Healthcare, BFSI, Consumer Goods and Retail, Government and Defense, Energy and Utilities, Others) and Regional Forecasts 2024-2032

Product Code: ICTNGT-72589876
Publish Date: 25-08-2024
Page: 200

Global AI Orchestration Market is valued at approximately USD 7.68 billion in 2023 and is anticipated to grow with a healthy growth rate of more than 22.5% over the forecast period 2024-2032. An AI orchestration solution helps enterprises operationalize artificial intelligence (AI), enabling scalability and growth. Enabling technologies such as machine learning and AI assist with data preparation, model building and deployment, insight generation, and insight explanation, augmenting how enterprises explore and analyze data. Furthermore, AI orchestration accesses an automated machine learning environment that redefines enterprise AI by automating every step of the data life cycle, including auto model building using simple workflows. This allows the building and management of AI models in minutes without writing a single line of code, democratizing AI across the organization and ensuring transparency and interpretability through explainable AI capabilities.

Moreover, AI orchestration helps visualize, analyze, and consume complex enterprise data. It auto-visualizes data and automatically uncovers hidden and crucial insights, creating charts, dashboards, and reports to understand and share business insights. It derives deep insights from real-time streaming data, improving productivity and reducing infrastructure management time, enhancing innovation and growth across businesses through AI-driven decision analytics. Additionally, AI orchestration offers multiple benefits, including enabling IT teams to automate tasks across multiple platforms from a single point and providing centralized monitoring and management over all IT servers, applications, and workflows. This centralized coordination among IT servers and applications enables easier and faster integration of new tools and systems into the existing infrastructure. Moreover, the lack of skilled professionals and high initial investment costs present various lucrative opportunities over the forecast years. However, the expansion in emerging markets, integration of AI with advanced technologies like 5G, as well as increasing demand for responsible AI solutions are challenging the market growth throughout the forecast period of 2024-2032.

The key regions considered for the Global AI Orchestration Market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America is a dominating region in the Global AI Orchestration Market in terms of revenue. The market growth in the region is being attributed to factors including the high concentration of artificial intelligence and cloud-based solution vendors in the region, providing lucrative growth opportunities for the AI orchestration market. Whereas, the market in Asia Pacific is anticipated to grow at the fastest rate over the forecast period fueled by rapid digital transformation trends that are expected to increase the scope for the AI orchestration industry in this region.

Major market players included in this report are:
IBM Corporation
Oracle Corporation
Fujitsu Limited
BMC Software, Inc.
Wipro Limited
Capgemini Services SAS
TIBCO Software Inc.
General Electric Company
Cisco Systems, Inc.
Hewlett Packard Enterprise Company
Accenture plc
Cognizant Technology Solutions Corporation
Infosys Limited
Amazon Web Services, Inc.
Microsoft Corporation

The detailed segments and sub-segment of the market are explained below:
By Component:
Solution
Services

By Deployment Mode:
On-Premise
Cloud

By Application:
Customer Service Orchestration
Infrastructure Orchestration
Manufacturing Orchestration
Workflow Orchestration
Others

By Organization Size:
Large Enterprises
Small and Medium-sized Enterprises

By Industry Vertical:
IT and Telecommunications
Manufacturing
Healthcare
BFSI
Consumer Goods and Retail
Government and Defense
Energy and Utilities
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 Latin America

Middle East & Africa
Saudi Arabia
South Africa
RoMEA

Years considered for the study are as follows:
Historical year – 2022
Base year – 2023
Forecast period – 2024 to 2032
Key Takeaways:
Market Estimates & Forecast for 10 years from 2022 to 2032.
Annualized revenues and regional level analysis for each market segment.
Detailed analysis of geographical landscape with Country level analysis of major regions.
Competitive landscape with information on major players in the market.
Analysis of key business strategies and recommendations on future market approach.
Analysis of competitive structure of the market.
Demand side and supply side analysis of the market.

Chapter 1. Global AI Orchestration Market Executive Summary
1.1. Global AI Orchestration Market Size & Forecast (2022-2032)
1.2. Regional Summary
1.3. Segmental Summary
1.3.1. By Component
1.3.2. By Deployment Mode
1.3.3. By Application
1.3.4. By Organization Size
1.3.5. By Industry Vertical
1.4. Key Trends
1.5. Recession Impact
1.6. Analyst Recommendation & Conclusion

Chapter 2. Global AI Orchestration Market Definition and Research Assumptions
2.1. Research Objective
2.2. Market Definition
2.3. Research Assumptions
2.3.1. Inclusion & Exclusion
2.3.2. Limitations
2.3.3. Supply Side Analysis
2.3.3.1. Availability
2.3.3.2. Infrastructure
2.3.3.3. Regulatory Environment
2.3.3.4. Market Competition
2.3.3.5. Economic Viability (Consumer’s Perspective)
2.3.4. Demand Side Analysis
2.3.4.1. Regulatory Frameworks
2.3.4.2. Technological Advancements
2.3.4.3. Environmental Considerations
2.3.4.4. Consumer Awareness & Acceptance
2.4. Estimation Methodology
2.5. Years Considered for the Study
2.6. Currency Conversion Rates

Chapter 3. Global AI Orchestration Market Dynamics
3.1. Market Drivers
3.1.1. Rising adoption of AI orchestration solutions
3.1.2. Technological advancements in AI and machine learning
3.1.3. Increasing investment in AI technologies
3.2. Market Challenges
3.2.1. Lack of skilled professionals
3.2.2. High initial investment costs
3.3. Market Opportunities
3.3.1. Expansion in emerging markets
3.3.2. Integration of AI with advanced technologies like 5G
3.3.3. Increasing demand for responsible AI solutions

Chapter 4. Global AI Orchestration 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
4.1.7. Porter’s 5 Force Impact Analysis
4.2. PESTEL Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.2.5. Environmental
4.2.6. Legal
4.3. Top Investment Opportunities
4.4. Top Winning Strategies
4.5. Disruptive Trends
4.6. Industry Expert Perspective
4.7. Analyst Recommendation & Conclusion

Chapter 5. Global AI Orchestration Market Size & Forecasts by Component 2022-2032
5.1. Segment Dashboard
5.2. Global AI Orchestration Market: Component Revenue Trend Analysis, 2022 & 2032 (USD Billion)
5.2.1. Solution
5.2.2. Services

Chapter 6. Global AI Orchestration Market Size & Forecasts by Deployment Mode 2022-2032
6.1. Segment Dashboard
6.2. Global AI Orchestration Market: Deployment Mode Revenue Trend Analysis, 2022 & 2032 (USD Billion)
6.2.1. On-Premise
6.2.2. Cloud

Chapter 7. Global AI Orchestration Market Size & Forecasts by Application 2022-2032
7.1. Segment Dashboard
7.2. Global AI Orchestration Market: Application Revenue Trend Analysis, 2022 & 2032 (USD Billion)
7.2.1. Customer Service Orchestration
7.2.2. Infrastructure Orchestration
7.2.3. Manufacturing Orchestration
7.2.4. Workflow Orchestration
7.2.5. Others

Chapter 8. Global AI Orchestration Market Size & Forecasts by Organization Size 2022-2032
8.1. Segment Dashboard
8.2. Global AI Orchestration Market: Organization Size Revenue Trend Analysis, 2022 & 2032 (USD Billion)
8.2.1. Large Enterprises
8.2.2. Small and Medium-sized Enterprises

Chapter 9. Global AI Orchestration Market Size & Forecasts by Industry Vertical 2022-2032
9.1. Segment Dashboard
9.2. Global AI Orchestration Market: Industry Vertical Revenue Trend Analysis, 2022 & 2032 (USD Billion)
9.2.1. IT and Telecommunications
9.2.2. Manufacturing
9.2.3. Healthcare
9.2.4. BFSI
9.2.5. Consumer Goods and Retail
9.2.6. Government and Defense
9.2.7. Energy and Utilities
9.2.8. Others

Chapter 10. Global AI Orchestration Market Size & Forecasts by Region 2022-2032
10.1. North America AI Orchestration Market
10.1.1. U.S. AI Orchestration Market
10.1.1.1. Component breakdown size & forecasts, 2022-2032
10.1.1.2. Deployment Mode breakdown size & forecasts, 2022-2032
10.1.1.2. Application Mode breakdown size & forecasts, 2022-2032
10.1.1.2. Organization Size Mode breakdown size & forecasts, 2022-2032
10.1.1.2. Industry Vertical Mode breakdown size & forecasts, 2022-2032
10.1.2. Canada AI Orchestration Market
10.2. Europe AI Orchestration Market
10.2.1. U.K. AI Orchestration Market
10.2.2. Germany AI Orchestration Market
10.2.3. France AI Orchestration Market
10.2.4. Spain AI Orchestration Market
10.2.5. Italy AI Orchestration Market
10.2.6. Rest of Europe AI Orchestration Market
10.3. Asia-Pacific AI Orchestration Market
10.3.1. China AI Orchestration Market
10.3.2. India AI Orchestration Market
10.3.3. Japan AI Orchestration Market
10.3.4. Australia AI Orchestration Market
10.3.5. South Korea AI Orchestration Market
10.3.6. Rest of Asia Pacific AI Orchestration Market
10.4. Latin America AI Orchestration Market
10.4.1. Brazil AI Orchestration Market
10.4.2. Mexico AI Orchestration Market
10.4.3. Rest of Latin America AI Orchestration Market
10.5. Middle East & Africa AI Orchestration Market
10.5.1. Saudi Arabia AI Orchestration Market
10.5.2. South Africa AI Orchestration Market
10.5.3. Rest of Middle East & Africa AI Orchestration Market

Chapter 11. Competitive Intelligence
11.1. Key Company SWOT Analysis
11.1.1. Company 1
11.1.2. Company 2
11.1.3. Company 3
11.2. Top Market Strategies
11.3. Company Profiles
11.3.1. IBM Corporation
11.3.1.1. Key Information
11.3.1.2. Overview
11.3.1.3. Financial (Subject to Data Availability)
11.3.1.4. Product Summary
11.3.1.5. Market Strategies
11.3.2. Oracle Corporation
11.3.3. Fujitsu Limited
11.3.4. BMC Software, Inc.
11.3.5. Wipro Limited
11.3.6. Capgemini Services SAS
11.3.7. TIBCO Software Inc.
11.3.8. General Electric Company
11.3.9. Cisco Systems, Inc.
11.3.10. Hewlett Packard Enterprise Company
11.3.11. Accenture plc
11.3.12. Cognizant Technology Solutions Corporation
11.3.13. Infosys Limited
11.3.14. Amazon Web Services, Inc.
11.3.15. Microsoft Corporation

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

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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