세계의 AI 오케스트레이션 시장 : 컴포넌트별, 용도별, 기술별, 전개 유형별, 조직 규모별, 최종 사용자별 - 예측(2025-2030년)

The AI Orchestration Market was valued at USD 7.81 billion in 2023, expected to reach USD 9.24 billion in 2024, and is projected to grow at a CAGR of 19.94%, to USD 27.91 billion by 2030.

AI Orchestration refers to the process of integrating, managing, and automating multiple AI systems and processes to work harmoniously within an organization, optimizing their collective performance. It is crucial for maximizing efficiency and effectiveness in AI deployment as it enables seamless interaction between different AI technologies and data sources, reducing operational silos. The necessity for AI Orchestration lies in its ability to streamline AI processes, enhance scalability, and reduce time-to-market, making it particularly indispensable in data-intensive industries like finance, healthcare, retail, and manufacturing. It is applied in automating workflows, improving decision-making accuracy, and fostering innovation by encouraging the collaboration of diverse AI models, leading to comprehensive data-driven insights. Key growth factors include the increasing adoption of cloud-based solutions, growing demand for AI and machine learning, need for efficient process automation, and the exponential rise in data generation. Opportunities for market expansion are also present in the growing trend of digital transformation, where businesses seek integrated AI solutions for competitive advantage. However, challenges such as integration complexity, data privacy concerns, high deployment costs, and the need for significant infrastructure changes pose limitations to market growth. Innovation opportunities exist particularly in developing interoperable AI platforms, enhancing AI governance frameworks, and advancing edge AI capabilities. Businesses can capitalize on these by investing in robust AI orchestration tools that prioritize scalability, interoperability, and privacy. Research is needed to explore hybrid AI orchestration models and improved data management protocols to address market challenges. The nature of the AI Orchestration market is dynamic and continuously evolving, demanding constant adaptation and innovative strategies to harness its full potential effectively. Insights and market intelligence are essential for navigating these changes and staying ahead in this competitive landscape.

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving AI Orchestration Market

The AI Orchestration Market is undergoing transformative changes driven by a dynamic interplay of supply and demand factors. Understanding these evolving market dynamics prepares business organizations to make informed investment decisions, refine strategic decisions, and seize new opportunities. By gaining a comprehensive view of these trends, business organizations can mitigate various risks across political, geographic, technical, social, and economic domains while also gaining a clearer understanding of consumer behavior and its impact on manufacturing costs and purchasing trends.

• Market Drivers
  • Rising demand for automated solutions to minimize human intervention and errors
  • Increasing use of AI across various sectors and proliferation of big data necessitates sophisticated orchestration
• Market Restraints
  • Difficulty in integrating diverse AI models and legacy systems
• Market Opportunities
  • Growth potential in orchestrating AI workflows across edge devices
  • Development of tailored orchestration solutions for niche industries
• Market Challenges
  • Concerns over data governance and security while orchestrating workflows

Porter's Five Forces: A Strategic Tool for Navigating the AI Orchestration Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the AI Orchestration Market. It offers business organizations with a clear methodology for evaluating their competitive positioning and exploring strategic opportunities. This framework helps businesses assess the power dynamics within the market and determine the profitability of new ventures. With these insights, business organizations can leverage their strengths, address weaknesses, and avoid potential challenges, ensuring a more resilient market positioning.

PESTLE Analysis: Navigating External Influences in the AI Orchestration Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the AI Orchestration Market. Political, Economic, Social, Technological, Legal, and Environmental factors analysis provides the necessary information to navigate these influences. By examining PESTLE factors, businesses can better understand potential risks and opportunities. This analysis enables business organizations to anticipate changes in regulations, consumer preferences, and economic trends, ensuring they are prepared to make proactive, forward-thinking decisions.

Market Share Analysis: Understanding the Competitive Landscape in the AI Orchestration Market

A detailed market share analysis in the AI Orchestration Market provides a comprehensive assessment of vendors' performance. Companies can identify their competitive positioning by comparing key metrics, including revenue, customer base, and growth rates. This analysis highlights market concentration, fragmentation, and trends in consolidation, offering vendors the insights required to make strategic decisions that enhance their position in an increasingly competitive landscape.

FPNV Positioning Matrix: Evaluating Vendors' Performance in the AI Orchestration Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the AI Orchestration Market. This matrix enables business organizations to make well-informed decisions that align with their goals by assessing vendors based on their business strategy and product satisfaction. The four quadrants provide a clear and precise segmentation of vendors, helping users identify the right partners and solutions that best fit their strategic objectives.

Strategy Analysis & Recommendation: Charting a Path to Success in the AI Orchestration Market

A strategic analysis of the AI Orchestration Market is essential for businesses looking to strengthen their global market presence. By reviewing key resources, capabilities, and performance indicators, business organizations can identify growth opportunities and work toward improvement. This approach helps businesses navigate challenges in the competitive landscape and ensures they are well-positioned to capitalize on newer opportunities and drive long-term success.

Key Company Profiles

The report delves into recent significant developments in the AI Orchestration Market, highlighting leading vendors and their innovative profiles. These include Activeeon S.A.S., Alibaba Group Holding Limited, AltaSigma GmbH, Alteryx, Inc., Amazon Web Services, Inc., Automation Anywhere, Inc., Beijing Baidu Netcom Science and Technology Co., Ltd., Blue Prism Limited, Broadcom, Inc., Cisco Systems, Inc., DataRobot, Inc., Google LLC, Hewlett Packard Enterprise, Intel Corporation, International Business Machines Corp., ModelOp, NVIDIA Corporation, Oracle Corporation, Rapid Acceleration Partners, Inc., Salesforce, Inc., SAP SE, ServiceNow, Inc., Tencent Holdings Ltd., UiPath, and Wipro Limited.

Market Segmentation & Coverage

This research report categorizes the AI Orchestration Market to forecast the revenues and analyze trends in each of the following sub-markets:

• Based on Component, market is studied across Services and Solutions. The Services is further studied across Managed Services and Professional Services. The Solutions is further studied across Integration Tools and Workflow Automation Tools.
• Based on Application, market is studied across Data Integration, Process Automation, Resource Scheduling, and Service Orchestration. The Process Automation is further studied across Robotic Process Automation and Workflow Automation.
• Based on Technology, market is studied across Computer Vision, Machine Learning, Natural Language Processing, and Predictive Analytics.
• Based on Deployment Type, market is studied across Cloud-Based, Hybrid, and On-Premises.
• Based on Organization Size, market is studied across Large Enterprises and Small & Medium Enterprises.
• Based on End-User, market is studied across Finance, Healthcare, Manufacturing, and Retail. The Finance is further studied across Fraud Detection and Risk Management. The Healthcare is further studied across Clinical Data Management, Medical Billing, and Patient Monitoring. The Manufacturing is further studied across Predictive Maintenance and Supply Chain Optimization. The Retail is further studied across Customer Experience Management and Inventory Management.
• Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

The report offers a comprehensive analysis of the market, covering key focus areas:

1. Market Penetration: A detailed review of the current market environment, including extensive data from top industry players, evaluating their market reach and overall influence.

2. Market Development: Identifies growth opportunities in emerging markets and assesses expansion potential in established sectors, providing a strategic roadmap for future growth.

3. Market Diversification: Analyzes recent product launches, untapped geographic regions, major industry advancements, and strategic investments reshaping the market.

4. Competitive Assessment & Intelligence: Provides a thorough analysis of the competitive landscape, examining market share, business strategies, product portfolios, certifications, regulatory approvals, patent trends, and technological advancements of key players.

5. Product Development & Innovation: Highlights cutting-edge technologies, R&D activities, and product innovations expected to drive future market growth.

The report also answers critical questions to aid stakeholders in making informed decisions:

1. What is the current market size, and what is the forecasted growth?

2. Which products, segments, and regions offer the best investment opportunities?

3. What are the key technology trends and regulatory influences shaping the market?

4. How do leading vendors rank in terms of market share and competitive positioning?

5. What revenue sources and strategic opportunities drive vendors' market entry or exit strategies?

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Segmentation & Coverage
• 1.3. Years Considered for the Study
• 1.4. Currency & Pricing
• 1.5. Language
• 1.6. Stakeholders

2. Research Methodology

• 2.1. Define: Research Objective
• 2.2. Determine: Research Design
• 2.3. Prepare: Research Instrument
• 2.4. Collect: Data Source
• 2.5. Analyze: Data Interpretation
• 2.6. Formulate: Data Verification
• 2.7. Publish: Research Report
• 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

• 5.1. Market Dynamics
  • 5.1.1. Drivers
    • 5.1.1.1. Rising demand for automated solutions to minimize human intervention and errors
    • 5.1.1.2. Increasing use of AI across various sectors and proliferation of big data necessitates sophisticated orchestration
  • 5.1.2. Restraints
    • 5.1.2.1. Difficulty in integrating diverse AI models and legacy systems
  • 5.1.3. Opportunities
    • 5.1.3.1. Growth potential in orchestrating AI workflows across edge devices
    • 5.1.3.2. Development of tailored orchestration solutions for niche industries
  • 5.1.4. Challenges
    • 5.1.4.1. Concerns over data governance and security while orchestrating workflows
• 5.2. Market Segmentation Analysis
  • 5.2.1. Component: Increasing preference for managed services to maintain complex AI systems
  • 5.2.2. Deployment Type: Growing adoption of cloud-based deployment due to its scalability
• 5.3. Porter's Five Forces Analysis
  • 5.3.1. Threat of New Entrants
  • 5.3.2. Threat of Substitutes
  • 5.3.3. Bargaining Power of Customers
  • 5.3.4. Bargaining Power of Suppliers
  • 5.3.5. Industry Rivalry
• 5.4. PESTLE Analysis
  • 5.4.1. Political
  • 5.4.2. Economic
  • 5.4.3. Social
  • 5.4.4. Technological
  • 5.4.5. Legal
  • 5.4.6. Environmental

6. AI Orchestration Market, by Component

• 6.1. Introduction
• 6.2. Services
  • 6.2.1. Managed Services
  • 6.2.2. Professional Services
• 6.3. Solutions
  • 6.3.1. Integration Tools
  • 6.3.2. Workflow Automation Tools

7. AI Orchestration Market, by Application

• 7.1. Introduction
• 7.2. Data Integration
• 7.3. Process Automation
  • 7.3.1. Robotic Process Automation
  • 7.3.2. Workflow Automation
• 7.4. Resource Scheduling
• 7.5. Service Orchestration

8. AI Orchestration Market, by Technology

• 8.1. Introduction
• 8.2. Computer Vision
• 8.3. Machine Learning
• 8.4. Natural Language Processing
• 8.5. Predictive Analytics

9. AI Orchestration Market, by Deployment Type

• 9.1. Introduction
• 9.2. Cloud-Based
• 9.3. Hybrid
• 9.4. On-Premises

10. AI Orchestration Market, by Organization Size

• 10.1. Introduction
• 10.2. Large Enterprises
• 10.3. Small & Medium Enterprises

11. AI Orchestration Market, by End-User

• 11.1. Introduction
• 11.2. Finance
  • 11.2.1. Fraud Detection
  • 11.2.2. Risk Management
• 11.3. Healthcare
  • 11.3.1. Clinical Data Management
  • 11.3.2. Medical Billing
  • 11.3.3. Patient Monitoring
• 11.4. Manufacturing
  • 11.4.1. Predictive Maintenance
  • 11.4.2. Supply Chain Optimization
• 11.5. Retail
  • 11.5.1. Customer Experience Management
  • 11.5.2. Inventory Management

12. Americas AI Orchestration Market

• 12.1. Introduction
• 12.2. Argentina
• 12.3. Brazil
• 12.4. Canada
• 12.5. Mexico
• 12.6. United States

13. Asia-Pacific AI Orchestration Market

• 13.1. Introduction
• 13.2. Australia
• 13.3. China
• 13.4. India
• 13.5. Indonesia
• 13.6. Japan
• 13.7. Malaysia
• 13.8. Philippines
• 13.9. Singapore
• 13.10. South Korea
• 13.11. Taiwan
• 13.12. Thailand
• 13.13. Vietnam

14. Europe, Middle East & Africa AI Orchestration Market

• 14.1. Introduction
• 14.2. Denmark
• 14.3. Egypt
• 14.4. Finland
• 14.5. France
• 14.6. Germany
• 14.7. Israel
• 14.8. Italy
• 14.9. Netherlands
• 14.10. Nigeria
• 14.11. Norway
• 14.12. Poland
• 14.13. Qatar
• 14.14. Russia
• 14.15. Saudi Arabia
• 14.16. South Africa
• 14.17. Spain
• 14.18. Sweden
• 14.19. Switzerland
• 14.20. Turkey
• 14.21. United Arab Emirates
• 14.22. United Kingdom

15. Competitive Landscape

• 15.1. Market Share Analysis, 2023
• 15.2. FPNV Positioning Matrix, 2023
• 15.3. Competitive Scenario Analysis
  • 15.3.1. TCS launches AI WisdomNext to streamline AI adoption with compliance, cost efficiency, and faster prototyping for businesses
  • 15.3.2. Nvidia to acquire Run AI for USD 700 million to boost AI computing capabilities with advanced Kubernetes-based orchestration software
  • 15.3.3. EPAM unveils DIAL Orchestration Platform, blending public and proprietary LLMs for enhanced business efficiency
• 15.4. Strategy Analysis & Recommendation

Companies Mentioned

• 1. Activeeon S.A.S.
• 2. Alibaba Group Holding Limited
• 3. AltaSigma GmbH
• 4. Alteryx, Inc.
• 5. Amazon Web Services, Inc.
• 6. Automation Anywhere, Inc.
• 7. Beijing Baidu Netcom Science and Technology Co., Ltd.
• 8. Blue Prism Limited
• 9. Broadcom, Inc.
• 10. Cisco Systems, Inc.
• 11. DataRobot, Inc.
• 12. Google LLC
• 13. Hewlett Packard Enterprise
• 14. Intel Corporation
• 15. International Business Machines Corp.
• 16. ModelOp
• 17. NVIDIA Corporation
• 18. Oracle Corporation
• 19. Rapid Acceleration Partners, Inc.
• 20. Salesforce, Inc.
• 21. SAP SE
• 22. ServiceNow, Inc.
• 23. Tencent Holdings Ltd.
• 24. UiPath
• 25. Wipro Limited