세계의 AIaaS(AI-as-a-Service) 시장 : 서비스 유형별, 기술별, 조직 규모별, 전개별, 최종 사용자별-예측(2025-2030년)

The AI-as-a-Service Market was valued at USD 7.25 billion in 2023, expected to reach USD 9.15 billion in 2024, and is projected to grow at a CAGR of 27.55%, to USD 39.85 billion by 2030.

AI-as-a-Service (AIaaS) provides businesses with outsourced AI capabilities, enabling them to deploy scalable machine learning solutions and advanced data processing without significant investment in infrastructure. This service model is crucial for companies lacking AI expertise, as it democratizes access to artificial intelligence, leveraging cloud-based solutions to streamline operations and enhance decision-making processes. AIaaS applications range from automated data analysis and natural language processing to more specialized uses like predictive analytics and computer vision, serving end-users across sectors such as finance, healthcare, retail, and manufacturing. The key growth factors driving the AIaaS market include the escalating adoption of cloud-based services, massive data generation across industries, and the pressing demand for automating business functions as companies pivot towards digital transformation strategies. Additionally, advances in AI technologies such as deep learning and neural networks present lucrative opportunities for developers and service providers to create more sophisticated and tailored offerings. Despite its promise, the market faces challenges like data privacy concerns, integration complexities with legacy systems, and a potential shortage of skilled professionals adept in AI technologies, which could inhibit growth. Furthermore, regulatory issues concerning data protection and ethical AI usage require careful navigation. Potential areas for innovation include the development of more intuitive AI models that require less data to train, enhancing collaborativity between AI systems and human operators, and improving AI transparency and accountability to meet regulatory demands. Companies are recommended to focus on building partnerships with technology providers and investing in strategic alliances to maximize the benefits AIaaS offers while ensuring robust data governance frameworks are in place. For sustained business growth, understanding evolving customer needs and technological advancements can provide a meaningful edge in this dynamic market landscape.

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving AI-as-a-Service Market

The AI-as-a-Service 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
  • Growing adoption of AI technologies across various industries to enhance operational efficiency
  • Increasing use of AI for improving data transfer efficiency and wireless network capacity
  • Proliferation of big data analytics boosting demand for AI tools and platforms
• Market Restraints
  • Limited access to quality data & overreliance on cloud infrastructure
• Market Opportunities
  • Developing AI-fueled environmental monitoring systems to support sustainable agricultural practices worldwide
  • Expanding AI-powered predictive maintenance services for industries reliant on heavy machinery
• Market Challenges
  • Data privacy and security concerns associated with AI-as-a-Service

Porter's Five Forces: A Strategic Tool for Navigating the AI-as-a-Service Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the AI-as-a-Service 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-as-a-Service Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the AI-as-a-Service 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-as-a-Service Market

A detailed market share analysis in the AI-as-a-Service 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-as-a-Service Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the AI-as-a-Service 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-as-a-Service Market

A strategic analysis of the AI-as-a-Service 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-as-a-Service Market, highlighting leading vendors and their innovative profiles. These include Accenture PLC, Amazon Web Services, Inc., Avenga International GmbH, BigML, Inc., BMC Software, Inc., Booz Allen Hamilton, Cerence Inc., Cognizant Technology Solutions Corporation, Databricks, Inc, EXPERT.AI, Fair Isaac Corporation, Google LLC by Alphabet Inc., Hewlett Packard Enterprise Development LP, IDC CEMA s.r.o., Infosys Limited, Intel Corporation, International Business Machines Corporation, Kyndryl Inc., Levity AI GmbH, Microsoft Corporation, NICE Ltd., Runai Labs Ltd., Salesforce, Inc., SAP SE, and Siemens AG.

Market Segmentation & Coverage

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

• Based on Service Type, market is studied across Application Programming Interface (APIs), Chatbots & Digital Assistants, Data Labeling, Machine Learning (ML) Frameworks, and No-Code or Low-Code ML Services.
• Based on Technology, market is studied across Computer Vision, Machine Learning, Natural Language Processing, and Robotic Process Automation. The Computer Vision is further studied across Facial Recognition, Image Recognition, and Object Detection. The Natural Language Processing is further studied across Sentiment Analysis and Text Analytics. The Robotic Process Automation is further studied across Customer Support Automation, Data Entry Automation, and Workflow Automation.
• Based on Organization Size, market is studied across Large Enterprises and Small & Medium-sized Enterprises (SMEs).
• Based on Deployment, market is studied across Hybrid, Private, and Public.
• Based on End-User, market is studied across Banking, Financial, & Insurance (BFSI), Energy & Utility, Government & Defense, Healthcare & Life Sciences, IT & Telecommunication, Manufacturing, and Retail.
• 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. Growing adoption of AI technologies across various industries to enhance operational efficiency

• 5.1.1.2. Increasing use of AI for improving data transfer efficiency and wireless network capacity

• 5.1.1.3. Proliferation of big data analytics boosting demand for AI tools and platforms
• 5.1.2. Restraints
  • 5.1.2.1. Limited access to quality data & overreliance on cloud infrastructure
• 5.1.3. Opportunities
  • 5.1.3.1. Developing AI-fueled environmental monitoring systems to support sustainable agricultural practices worldwide
  • 5.1.3.2. Expanding AI-powered predictive maintenance services for industries reliant on heavy machinery

• 5.1.4. Challenges
  • 5.1.4.1. Data privacy and security concerns associated with AI-as-a-Service
• 5.2. Market Segmentation Analysis
  • 5.2.1. Technology :

5.2.2. Organization Size :

5.2.3. Deployment :

5.2.4. End-User :

• 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-as-a-Service Market, by Service Type

• 6.1. Introduction
• 6.2. Application Programming Interface (APIs)
• 6.3. Chatbots & Digital Assistants
• 6.4. Data Labeling
• 6.5. Machine Learning (ML) Frameworks
• 6.6. No-Code or Low-Code ML Services

7. AI-as-a-Service Market, by Technology

• 7.1. Introduction
• 7.2. Computer Vision
  • 7.2.1. Facial Recognition
  • 7.2.2. Image Recognition
  • 7.2.3. Object Detection
• 7.3. Machine Learning
• 7.4. Natural Language Processing
  • 7.4.1. Sentiment Analysis
  • 7.4.2. Text Analytics
• 7.5. Robotic Process Automation
  • 7.5.1. Customer Support Automation
  • 7.5.2. Data Entry Automation
  • 7.5.3. Workflow Automation

8. AI-as-a-Service Market, by Organization Size

• 8.1. Introduction
• 8.2. Large Enterprises
• 8.3. Small & Medium-sized Enterprises (SMEs)

9. AI-as-a-Service Market, by Deployment

• 9.1. Introduction
• 9.2. Hybrid
• 9.3. Private
• 9.4. Public

10. AI-as-a-Service Market, by End-User

• 10.1. Introduction
• 10.2. Banking, Financial, & Insurance (BFSI)
• 10.3. Energy & Utility
• 10.4. Government & Defense
• 10.5. Healthcare & Life Sciences
• 10.6. IT & Telecommunication
• 10.7. Manufacturing
• 10.8. Retail

11. Americas AI-as-a-Service Market

• 11.1. Introduction
• 11.2. Argentina
• 11.3. Brazil
• 11.4. Canada
• 11.5. Mexico
• 11.6. United States

12. Asia-Pacific AI-as-a-Service Market

• 12.1. Introduction
• 12.2. Australia
• 12.3. China
• 12.4. India
• 12.5. Indonesia
• 12.6. Japan
• 12.7. Malaysia
• 12.8. Philippines
• 12.9. Singapore
• 12.10. South Korea
• 12.11. Taiwan
• 12.12. Thailand
• 12.13. Vietnam

13. Europe, Middle East & Africa AI-as-a-Service Market

• 13.1. Introduction
• 13.2. Denmark
• 13.3. Egypt
• 13.4. Finland
• 13.5. France
• 13.6. Germany
• 13.7. Israel
• 13.8. Italy
• 13.9. Netherlands
• 13.10. Nigeria
• 13.11. Norway
• 13.12. Poland
• 13.13. Qatar
• 13.14. Russia
• 13.15. Saudi Arabia
• 13.16. South Africa
• 13.17. Spain
• 13.18. Sweden
• 13.19. Switzerland
• 13.20. Turkey
• 13.21. United Arab Emirates
• 13.22. United Kingdom

14. Competitive Landscape

• 14.1. Market Share Analysis, 2023
• 14.2. FPNV Positioning Matrix, 2023
• 14.3. Competitive Scenario Analysis
• 14.4. Strategy Analysis & Recommendation

Companies Mentioned

• 1. Accenture PLC
• 2. Amazon Web Services, Inc.
• 3. Avenga International GmbH
• 4. BigML, Inc.
• 5. BMC Software, Inc.
• 6. Booz Allen Hamilton
• 7. Cerence Inc.
• 8. Cognizant Technology Solutions Corporation
• 9. Databricks, Inc
• 10. EXPERT.AI
• 11. Fair Isaac Corporation
• 12. Google LLC by Alphabet Inc.
• 13. Hewlett Packard Enterprise Development LP
• 14. IDC CEMA s.r.o.
• 15. Infosys Limited
• 16. Intel Corporation
• 17. International Business Machines Corporation
• 18. Kyndryl Inc.
• 19. Levity AI GmbH
• 20. Microsoft Corporation
• 21. NICE Ltd.
• 22. Runai Labs Ltd.
• 23. Salesforce, Inc.
• 24. SAP SE
• 25. Siemens AG