시장보고서
상품코드
1430809

세계의 AIaaS(AI as a Service) 시장 규모, 점유율 및 동향 분석 보고서 : 조직 규모별, 제공 제품별, 클라우드 유형별, 기술별, 산업별, 지역별 전망 및 예측(2023-2030년)

Global AI as a Service Market Size, Share & Trends Analysis Report By Organization Size, By Offering, By Cloud Type, By Technology, By Vertical, By Regional Outlook and Forecast, 2023 - 2030

발행일: | 리서치사: KBV Research | 페이지 정보: 영문 383 Pages | 배송안내 : 즉시배송

    
    
    



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AIaaS(AI as a Service) 시장 규모는 2030년까지 1,167억 달러에 달하고, 예측 기간 동안 41.4%의 연평균 시장 성장률을 나타낼 것으로 예상됩니다.

KBV Cardinal matrix의 분석에 따르면, Microsoft Corporation과 Google LLC가 서비스형 AI 시장의 선구자이며, 2023년 6월 Microsoft Corporation은 분석 및 비즈니스 인텔리전스 회사인 MicroStrategy Incorporated와 다년간의 파트너십을 체결했습니다. 분석 및 비즈니스 인텔리전스 기업인 MicroStrategy Incorporated와 다년간의 파트너십을 체결했습니다. 이 다년간의 파트너십에 따라 MicroStrategy의 고급 분석 역량과 Microsoft의 Azure OpenAI Service가 결합되었습니다. 또한 이 파트너십을 통해 MicroStrategy의 제품을 Microsoft Azure를 통해 이용할 수 있게 되었으며, Oracle Corporation, IBM Corporation, Baidu, Inc. 서비스형 AI 시장의 주요 혁신 기업입니다.

시장 성장 요인

최근 몇 년동안 다양한 산업 분야의 기업들이 AI가 혁신을 주도하고, 업무 효율성을 개선하며, 탁월한 고객 경험을 제공하는 데 있어 AI의 변혁적 잠재력을 인식하기 시작하면서 AIaaS에 대한 수요가 급증하고 있습니다. 이러한 수요는 AI 서비스 제공업체와 혁신적 솔루션의 견고한 생태계를 형성하며 시장의 확대와 진화를 촉진하고 있으며, AIaaS 제공업체의 급증은 AI 기반 기능에 대한 수요 증가에 기인하고 있습니다. 이들 기업은 업계의 다양한 요구 사항을 충족하기 위해 다양한 서비스를 제공합니다. 이러한 확장은 스타트업부터 대기업에 이르기까지 모든 규모의 기업이 AIaaS에 쉽게 접근할 수 있도록 하여, 이전에는 많은 조직이 접근하기 어려웠던 고급 AI 기술에 대한 접근을 민주화했습니다. 따라서 기업들이 AI를 전략적 필수 요소로 받아들이면서 시장은 더욱 진화하고 성숙해져 다양한 산업 및 지역 기업의 다양한 요구를 충족시키기 위해 더욱 고도화되고 전문적인 AI 서비스를 제공하게 될 것으로 예상됩니다.

클라우드 컴퓨팅 제공업체가 제공하는 확장 가능하고 적응력이 뛰어난 인프라는 AI 서비스 호스팅에 적합합니다. 이는 기기나 소프트웨어에 대한 초기 투자 없이 AIaaS를 도입하고자 하는 기업의 요구에 부응합니다. 이러한 컴퓨팅 플랫폼은 기업에 확장 가능한 리소스를 제공하고 AI 워크로드 수요에 따라 용량을 조정할 수 있도록 지원합니다. 이러한 확장성은 복잡한 머신러닝 모델 학습이나 대량의 데이터 처리와 같은 작업에 막대한 컴퓨팅 리소스를 필요로 하는 AI 용도에 필수적입니다. 클라우드 인프라의 확장성을 활용하면 기업은 하드웨어 및 인프라에 대한 대규모 선행 투자 없이도 AI 워크로드를 효율적으로 관리할 수 있습니다. 그 결과, 기업은 AI를 시험해보고, AI 기반 용도를 배포하고, AI 이니셔티브를 보다 저렴하게 확장할 수 있어 다양한 산업군에서 AIaaS를 폭넓게 도입할 수 있게 됩니다. 이처럼 앞서 언급한 모든 요인들이 시장 성장을 견인하고 있습니다.

시장 성장 억제요인

많은 기업들이 AI 기능을 지원하도록 설계되지 않은 레거시 시스템을 사용하고 있기 때문에 AIaaS 솔루션을 워크플로우에 원활하게 통합하는 데 어려움을 겪고 있습니다. 이러한 상호운용성 부족은 데이터 사일로화로 이어져 귀중한 정보가 고립된 시스템에 갇혀 기업 전체가 AI의 잠재력을 최대한 활용할 수 있는 능력을 저해할 수 있습니다. 또 다른 문제는 AIaaS 솔루션과 기존 소프트웨어 및 하드웨어와의 통합의 복잡성입니다. 이러한 복잡성은 AI 모델이 데이터의 무결성과 보안을 유지하면서 다양한 시스템, 데이터베이스 및 용도과 효과적으로 통신할 수 있도록 하는 데서 비롯됩니다. 이러한 수준의 통합을 달성하기 위해서는 많은 경우 상당한 커스터마이징과 개발 노력이 필요하며, 특히 복잡한 IT 생태계를 가진 대기업의 경우 시간과 비용이 많이 소요됩니다. 그러나 AIaaS 솔루션이 기존 시스템과 원활하게 통합되지 않으면 증가하는 수요에 대응하기 위한 확장이 어렵고, 대대적인 재설계가 필요할 수 있습니다. 따라서 상호운용성 및 통합 문제는 시장 성장을 저해하는 요인이 될 수 있습니다.

시장의 주요 기업들은 시장 경쟁력을 유지하기 위해 다양한 혁신 제품으로 경쟁하고 있습니다. 위 그림은 이 시장에서 주요 기업의 매출 비중을 나타냅니다. 시장의 주요 기업들은 다양한 산업 수요를 충족시키기 위해 다양한 전략을 채택하고 있습니다. 이 시장의 주요 개발 전략은 파트너십, 제휴 및 계약입니다.

목차

제1장 시장 범위와 조사 방법

  • 시장의 정의
  • 목적
  • 시장 범위
  • 세분화
  • 조사 방법

제2장 시장 요람

  • 주요 하이라이트

제3장 시장 개요

  • 서론
    • 개요
      • 시장 구성과 시나리오
  • 시장에 영향을 미치는 주요 요인
    • 시장 성장 촉진요인
    • 시장 성장 억제요인
    • 시장 기회
    • 시장이 해결해야 할 과제

제4장 경쟁 분석 - 세계

  • KBV Cardinal Matrix
  • 최근 업계 전체의 전략적 전개
    • 파트너십, 협업 및 계약
    • 제품 발매와 제품 확대
    • 인수와 합병
  • 시장 점유율 분석(2022년)
  • 주요 성공 전략
    • 주요 전략
    • 주요 전략적 동향
  • Porter의 Five Forces 분석

제5장 세계 시장 : 조직 규모별

  • 세계의 대기업 시장 : 지역별
  • 세계의 중소기업 시장 : 지역별

제6장 세계 시장 : 제공별

  • 세계의 nfrastructure as a Service 시장 : 지역별
  • 세계의 Platform as a Service 시장 : 지역별
  • 세계의 Software as a Service 시장 : 지역별

제7장 세계 시장 : 클라우드 유형별

  • 세계의 퍼블릭 클라우드 시장 : 지역별
  • 세계의 프라이빗 클라우드 시장 : 지역별
  • 세계의 하이브리드 클라우드 시장 : 지역별

제8장 세계 시장 : 기술별

  • 세계의 머신러닝 시장 : 지역별
  • 세계의 자연언어처리 시장 : 지역별
  • 세계의 상황 인식 시장 : 지역별
  • 세계의 컴퓨터 비전 시장 : 지역별

제9장 세계 시장 : 업계별

  • 세계의 은행/금융서비스/보험(BFSI) 시장 : 지역별
  • 세계의 IT 및 텔레콤 시장 : 지역별
  • 세계의 소매 및 전자상거래 시장 : 지역별
  • 세계의 제조업 시장 : 지역별
  • 세계의 헬스케어 및 생명과학 시장 : 지역별
  • 세계의 정부 및 방위 시장 : 지역별
  • 세계의 에너지 및 유틸리티 시장 : 지역별
  • 세계의 기타 시장 : 지역별

제10장 세계 시장 : 지역별

  • 북미
    • 북미 시장 : 국가별
      • 미국
      • 캐나다
      • 멕시코
      • 기타 북미
  • 유럽
    • 유럽 시장 : 국가별
      • 독일
      • 영국
      • 프랑스
      • 러시아
      • 스페인
      • 이탈리아
      • 기타 유럽
  • 아시아태평양
    • 아시아태평양 시장 : 국가별
      • 중국
      • 일본
      • 인도
      • 한국
      • 싱가포르
      • 말레이시아
      • 기타 아시아태평양
  • 라틴아메리카/중동 및 아프리카
    • 라틴아메리카/중동 및 아프리카 시장 : 국가별
      • 브라질
      • 아르헨티나
      • 아랍에미리트(UAE)
      • 사우디아라비아
      • 남아프리카공화국
      • 나이지리아
      • 기타 라틴아메리카/중동 및 아프리카

제11장 기업 개요

  • IBM Corporation
  • Microsoft Corporation
  • Amazon Web Services, Inc(Amazon.com, Inc.)
  • Oracle Corporation
  • Google LLC(Alphabet Inc)
  • Fair Isaac Corporation(FICO)
  • Baidu, Inc
  • SAS Institute, Inc
  • SAP SE
  • Salesforce, Inc

제12장 AI as a Service 시장을 위한 성공 필수 조건

LSH 24.03.11

The Global AI as a Service Market size is expected to reach $116.7 billion by 2030, rising at a market growth of 41.4% CAGR during the forecast period.

The need for AIaaS in the medical industry is fueled by several issues, including the need to handle data more efficiently and optimize healthcare costs, expanding public-private partnerships, and rising regional healthcare spending. Thus, the healthcare & life sciences segment acquired $866.8 million in 2022. By analyzing vast quantities of chemical and biological data, AIaaS is being utilized to escalate drug discovery as well as the development process. AI algorithms can identify potential drug candidates, predict their efficacy and safety profiles, and optimize clinical trial designs, leading to faster and more cost-effective drug development.

The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. For instance, In January, 2024, IBM Corporation has collaborated with SAP SE. The collaboration aims to enhance supply chain, finance operations, sales, and services. The focus is on assisting CPG companies, wholesalers, and retailers in efficiently managing assortments, improving product distribution, and driving incremental revenue. This will be achieved through transportation planning enhancement, optimization of store-level assortments, and the automation of order settlement processes. Additionally, In December 2023, IBM Corporation has entered into an agreement with Software AG to acquire StreamSets, WebMethods, and iPaaS (integration platform-as-a-service) enterprise technology platforms. This acquisition underscores IBM's strong commitment and investment in AI and hybrid cloud.

Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation and Google LLC are the forerunners in the AI as a Service Market. In June, 2023, Microsoft Corporation formed a multi-year partnership with MicroStrategy Incorporated, an analytics and business intelligence company. Under the multi-year partnership, the advanced analytics abilities of MicroStrategy were combined with the Azure OpenAI Service of Microsoft. Additionally, the partnership increased the availability of the products of MicroStrategy through Microsoft Azure. Companies such as Oracle Corporation, IBM Corporation and Baidu, Inc. are some of the key innovators in AI as a Service Market.

Market Growth Factors

Recently, businesses across industries have started recognizing the transformative potential of AI in driving innovation, enhancing operational efficiency, and delivering superior customer experiences, the demand for AIaaS has surged. This demand is fueling the expansion and evolution of the market, creating a robust ecosystem of AI service providers and innovative solutions. The proliferation of AIaaS providers has resulted from the increasing demand for AI-driven capabilities; these companies offer various services to meet the varying requirements of industries. This expansion has made AIaaS more accessible to businesses of all sizes, from startups to large enterprises, democratizing access to advanced AI technologies previously out of reach for many organizations. Therefore, as businesses continue to embrace AI as a strategic imperative, the market is expected to evolve and mature further, offering even more advanced and specialized AI services to meet the diverse needs of businesses across industries and regions.

The scalable and adaptable infrastructure provided by cloud computing providers is ideal for hosting AI services. This meets the needs of organizations that wish to adopt AIaaS without making substantial initial investments in devices or software. These computing platforms provide enterprises with scalable resources, enabling them to adjust their capacity in accordance with the demands of their AI workload. This scalability is essential for AI applications, which often require significant computational resources for tasks such as training complex machine learning models or processing large volumes of data. By leveraging the scalability of cloud infrastructure, businesses can efficiently manage their AI workloads without the need for large upfront investments in hardware or infrastructure. As a result, businesses can now experiment with AI, deploy AI-powered applications, and scale their AI initiatives more affordably, driving broader adoption of AIaaS across diverse industry sectors. Thus, all of these aforementioned factors are aiding in the market's growth.

Market Restraining Factors

Many organizations operate with legacy systems not designed to accommodate AI capabilities, making seamlessly integrating AIaaS solutions into their workflows challenging. This lack of interoperability can lead to data silos, where valuable information is trapped in isolated systems, hindering the ability to harness the full potential of AI across the enterprise. Another challenge is the complexity of integrating AIaaS solutions with existing software and hardware. This complexity arises from ensuring that AI models communicate effectively with different systems, databases, and applications while maintaining data integrity and security. Achieving this level of integration often requires significant customization and development efforts, which can be time-consuming and costly, especially for large enterprises with complex IT ecosystems. However, if AIaaS solutions are not seamlessly integrated with existing systems, scaling them up to meet growing demands can be difficult and require substantial reengineering efforts. Therefore, the interoperability and integration challenges may hamper the market's growth.

The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships, Collaborations & Agreements.

By Organization Size Analysis

By organization size, the market is divided into small & medium-sized enterprises and large enterprises. The large enterprises segment witnessed the maximum revenue share in the market in 2022. AIaaS allows large enterprises to accelerate the development and deployment of AI applications. By leveraging pre-built AI models, APIs, and development tools offered by AIaaS providers, enterprises can reduce the time and effort required to build and deploy AI solutions, allowing them to bring new AI-powered products and services to market faster. Large enterprises can benefit from the pay-as-you-go model of AIaaS, which allows them to pay only for the AI services and resources they use, avoiding upfront capital expenditures and reducing total cost of ownership (TCO) for AI initiatives.

By Offering Analysis

Based on offering, the market is segmented into infrastructure as a service, platform as a service, and software as a service. The platform as a service segment acquired a substantial revenue share in the market in 2022. In order to facilitate multi-tenancy, PaaS offerings enable concurrent utilization of shared infrastructure and resources by multiple users. This multi-tenancy enables organizations to optimize resource utilization and reduce costs while supporting multiple AI applications and users. Businesses are now looking to AI Platforms as a Service (AIPaaS) to address their cloud issues by reducing cloud waste, lowering expenses, and streamlining operations.

By Cloud Type Analysis

On the basis of cloud type, the market is classified into public cloud, hybrid cloud, and private cloud. The public cloud segment acquired the largest revenue share in the market in 2022. Public clouds offer scalable and flexible computing resources, allowing businesses to scale their AI initiatives easily based on demand. Pay-as-you-go public cloud providers often allow businesses to pay just for the services they utilize. Additionally, having a worldwide presence, public cloud providers offer high availability to businesses worldwide.

By Technology Analysis

Based on technology, the market is characterized into machine learning, natural language processing, context awareness, and computer vision. The computer vision segment procured a considerable growth rate in the market in 2022. The demand for computer vision technology is driven by its ability to automate tasks, enhance user experiences, improve healthcare outcomes, enable autonomous vehicles, enhance security and surveillance, and optimize industrial processes. By utilizing cloud-based computer vision platforms, businesses may effortlessly upload, analyze, and train models to perform difficult tasks like object detection, picture recognition, and video analysis.

By Vertical Analysis

On the basis of vertical, the market is classified into BFSI, retail & eCommerce, healthcare & life sciences, IT & telecom, government & defense, manufacturing, energy & utilities, and others. The IT and telecom segment witnessed a considerable growth rate in the market in 2022. The IT and telecom segment is one of the largest AI tools and technologies consumers, contributing to its growth. This is because it improves productivity and makes handling complex software development projects easier. AIaaS can automate IT operations, such as IT service management, infrastructure provisioning, and application deployment. AI-powered automation can streamline IT workflows, reduce manual errors, and improve operational efficiency, allowing IT and telecom companies to focus on strategic initiatives.

By Regional Analysis

Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America segment acquired the maximum revenue share in the market in 2022. North America is at the forefront of technological innovation, with a robust ecosystem of technology companies, research institutions, and startups driving AI and cloud computing advancements. This ecosystem fosters a culture of innovation and entrepreneurship, leading to the development of cutting-edge AIaaS solutions and platforms. This region is home to several well-known AI businesses making significant investments in the field of study and development. As a result, new AI applications and technologies have been created, significantly boosting the market for AI as a service.

Recent Strategies Deployed in the Market

  • Jan-2024: IBM Corporation has collaborated with SAP SE, a German multinational enterprise software company, to develop generative AI solutions benefiting clients in consumer-packaged goods and retail. The collaboration aims to enhance supply chain, finance operations, sales, and services. The focus is on assisting CPG companies, wholesalers, and retailers in efficiently managing assortments, improving product distribution, and driving incremental revenue. This will be achieved through transportation planning enhancement, optimization of store-level assortments, and the automation of order settlement processes.
  • Dec-2023: IBM Corporation has entered into an agreement with Software AG, a German multinational software corporation majority owned by Silver Lake. The deal aims to acquire StreamSets, WebMethods, and iPaaS (integration platform-as-a-service) enterprise technology platforms. This acquisition underscores IBM's strong commitment and investment in AI and hybrid cloud. StreamSets will enhance data ingestion capabilities for Watson, IBM's AI and data platform, while WebMethods will provide clients and partners with additional tools for integration and API management in hybrid multi-cloud environments.
  • Dec-2023: Google, LLC has unveiled Gemini, large language models developed by Google DeepMind. The product will be available in three versions - ultra, pro and nano and rolled out across Google's suite of products.
  • Nov-2023: Amazon Web Services, Inc. extended its collaboration with NVIDIA Corporation, an American multinational technology company. Under this extended collaboration, the multi-node systems of NVIDIA were integrated with the technologies of AWS. Additionally, the extended collaboration provided the customers with generative AI infrastructure and services.
  • Nov-2023: Amazon Web Services, Inc. expanded their partnership with Salesforce, Inc., an American cloud-based software company. Under this extended partnership, the companies assisted customers to manage their data in Salesforce and Amazon Web Services. Additionally, the extended partnership helped in incorporating generative AI technologies in applications and workflows.
  • Aug-2023: IBM Corporation has successfully acquired Apptio Inc., a Washington-based company specializing in the development of technology business management software. With this strategic acquisition, IBM aims to integrate Apptio's FinOps solutions, which include ApptioOne, Cloudability, and Targetprocess, with IBM's automation portfolio comprising Turbonomic, AIOps, and Instana. This move is designed to provide clients with a comprehensive "virtual command center" that facilitates the efficient management, optimization, and automation of technology spending decisions.

List of Key Companies Profiled

  • IBM Corporation
  • Microsoft Corporation
  • Amazon Web Services, Inc. (Amazon.com, Inc.)
  • Oracle Corporation
  • Google LLC (Alphabet Inc.)
  • Fair Isaac Corporation (FICO)
  • Baidu, Inc.
  • SAS Institute, Inc.
  • SAP SE
  • Salesforce, Inc.

Global AI as a Service Market Report Segmentation

By Organization Size

  • Large Enterprises
  • Small & Medium-Sized Enterprises

By Offering

  • Infrastructure as a Service
  • Platform as a Service
  • Software as a Service

By Cloud Type

  • Public Cloud
  • Private Cloud
  • Hybrid Cloud

By Technology

  • Machine Learning
  • Natural Language Processing
  • Context Awareness
  • Computer Vision

By Vertical

  • BFSI
  • IT & Telecom
  • Retail & eCommerce
  • Manufacturing
  • Healthcare & Life Sciences
  • Government & Defense
  • Energy & Utilities
  • Others

By Geography

  • North America
    • US
    • Canada
    • Mexico
    • Rest of North America
  • Europe
    • Germany
    • UK
    • France
    • Russia
    • Spain
    • Italy
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Singapore
    • Malaysia
    • Rest of Asia Pacific
  • LAMEA
    • Brazil
    • Argentina
    • UAE
    • Saudi Arabia
    • South Africa
    • Nigeria
    • Rest of LAMEA

Table of Contents

Chapter 1. Market Scope & Methodology

  • 1.1 Market Definition
  • 1.2 Objectives
  • 1.3 Market Scope
  • 1.4 Segmentation
    • 1.4.1 Global AI as a Service Market, by Organization Size
    • 1.4.2 Global AI as a Service Market, by Offering
    • 1.4.3 Global AI as a Service Market, by Cloud Type
    • 1.4.4 Global AI as a Service Market, by Technology
    • 1.4.5 Global AI as a Service Market, by Vertical
    • 1.4.6 Global AI as a Service Market, by Geography
  • 1.5 Methodology for the research

Chapter 2. Market at a Glance

  • 2.1 Key Highlights

Chapter 3. Market Overview

  • 3.1 Introduction
    • 3.1.1 Overview
      • 3.1.1.1 Market Composition and Scenario
  • 3.2 Key Factors Impacting the Market
    • 3.2.1 Market Drivers
    • 3.2.2 Market Restraints
    • 3.2.3 Market Opportunities
    • 3.2.4 Market Challenges

Chapter 4. Competition Analysis - Global

  • 4.1 KBV Cardinal Matrix
  • 4.2 Recent Industry Wide Strategic Developments
    • 4.2.1 Partnerships, Collaborations and Agreements
    • 4.2.2 Product Launches and Product Expansions
    • 4.2.3 Acquisition and Mergers
  • 4.3 Market Share Analysis, 2022
  • 4.4 Top Winning Strategies
    • 4.4.1 Key Leading Strategies: Percentage Distribution (2019-2023)
    • 4.4.2 Key Strategic Move: (Partnerships, Collaborations & Agreements: 2020, Jun - 2024, Jan) Leading Players
  • 4.5 Porter's Five Forces Analysis

Chapter 5. Global AI as a Service Market by Organization Size

  • 5.1 Global Large Enterprises Market by Region
  • 5.2 Global Small & Medium-Sized Enterprises Market by Region

Chapter 6. Global AI as a Service Market by Offering

  • 6.1 Global Infrastructure as a Service Market by Region
  • 6.2 Global Platform as a Service Market by Region
  • 6.3 Global Software as a Service Market by Region

Chapter 7. Global AI as a Service Market by Cloud Type

  • 7.1 Global Public Cloud Market by Region
  • 7.2 Global Private Cloud Market by Region
  • 7.3 Global Hybrid Cloud Market by Region

Chapter 8. Global AI as a Service Market by Technology

  • 8.1 Global Machine Learning Market by Region
  • 8.2 Global Natural Language Processing Market by Region
  • 8.3 Global Context Awareness Market by Region
  • 8.4 Global Computer Vision Market by Region

Chapter 9. Global AI as a Service Market by Vertical

  • 9.1 Global BFSI Market by Region
  • 9.2 Global IT & Telecom Market by Region
  • 9.3 Global Retail & eCommerce Market by Region
  • 9.4 Global Manufacturing Market by Region
  • 9.5 Global Healthcare & Life Sciences Market by Region
  • 9.6 Global Government & Defense Market by Region
  • 9.7 Global Energy & Utilities Market by Region
  • 9.8 Global Others Market by Region

Chapter 10. Global AI as a Service Market by Region

  • 10.1 North America AI as a Service Market
    • 10.1.1 North America AI as a Service Market by Organization Size
      • 10.1.1.1 North America Large Enterprises Market by Region
      • 10.1.1.2 North America Small & Medium-Sized Enterprises Market by Region
    • 10.1.2 North America AI as a Service Market by Offering
      • 10.1.2.1 North America Infrastructure as a Service Market by Country
      • 10.1.2.2 North America Platform as a Service Market by Country
      • 10.1.2.3 North America Software as a Service Market by Country
    • 10.1.3 North America AI as a Service Market by Cloud Type
      • 10.1.3.1 North America Public Cloud Market by Country
      • 10.1.3.2 North America Private Cloud Market by Country
      • 10.1.3.3 North America Hybrid Cloud Market by Country
    • 10.1.4 North America AI as a Service Market by Technology
      • 10.1.4.1 North America Machine Learning Market by Country
      • 10.1.4.2 North America Natural Language Processing Market by Country
      • 10.1.4.3 North America Context Awareness Market by Country
      • 10.1.4.4 North America Computer Vision Market by Country
    • 10.1.5 North America AI as a Service Market by Vertical
      • 10.1.5.1 North America BFSI Market by Country
      • 10.1.5.2 North America IT & Telecom Market by Country
      • 10.1.5.3 North America Retail & eCommerce Market by Country
      • 10.1.5.4 North America Manufacturing Market by Country
      • 10.1.5.5 North America Healthcare & Life Sciences Market by Country
      • 10.1.5.6 North America Government & Defense Market by Country
      • 10.1.5.7 North America Energy & Utilities Market by Country
      • 10.1.5.8 North America Others Market by Country
    • 10.1.6 North America AI as a Service Market by Country
      • 10.1.6.1 US AI as a Service Market
        • 10.1.6.1.1 US AI as a Service Market by Organization Size
        • 10.1.6.1.2 US AI as a Service Market by Offering
        • 10.1.6.1.3 US AI as a Service Market by Cloud Type
        • 10.1.6.1.4 US AI as a Service Market by Technology
        • 10.1.6.1.5 US AI as a Service Market by Vertical
      • 10.1.6.2 Canada AI as a Service Market
        • 10.1.6.2.1 Canada AI as a Service Market by Organization Size
        • 10.1.6.2.2 Canada AI as a Service Market by Offering
        • 10.1.6.2.3 Canada AI as a Service Market by Cloud Type
        • 10.1.6.2.4 Canada AI as a Service Market by Technology
        • 10.1.6.2.5 Canada AI as a Service Market by Vertical
      • 10.1.6.3 Mexico AI as a Service Market
        • 10.1.6.3.1 Mexico AI as a Service Market by Organization Size
        • 10.1.6.3.2 Mexico AI as a Service Market by Offering
        • 10.1.6.3.3 Mexico AI as a Service Market by Cloud Type
        • 10.1.6.3.4 Mexico AI as a Service Market by Technology
        • 10.1.6.3.5 Mexico AI as a Service Market by Vertical
      • 10.1.6.4 Rest of North America AI as a Service Market
        • 10.1.6.4.1 Rest of North America AI as a Service Market by Organization Size
        • 10.1.6.4.2 Rest of North America AI as a Service Market by Offering
        • 10.1.6.4.3 Rest of North America AI as a Service Market by Cloud Type
        • 10.1.6.4.4 Rest of North America AI as a Service Market by Technology
        • 10.1.6.4.5 Rest of North America AI as a Service Market by Vertical
  • 10.2 Europe AI as a Service Market
    • 10.2.1 Europe AI as a Service Market by Organization Size
      • 10.2.1.1 Europe Large Enterprises Market by Country
      • 10.2.1.2 Europe Small & Medium-Sized Enterprises Market by Country
    • 10.2.2 Europe AI as a Service Market by Offering
      • 10.2.2.1 Europe Infrastructure as a Service Market by Country
      • 10.2.2.2 Europe Platform as a Service Market by Country
      • 10.2.2.3 Europe Software as a Service Market by Country
    • 10.2.3 Europe AI as a Service Market by Cloud Type
      • 10.2.3.1 Europe Public Cloud Market by Country
      • 10.2.3.2 Europe Private Cloud Market by Country
      • 10.2.3.3 Europe Hybrid Cloud Market by Country
    • 10.2.4 Europe AI as a Service Market by Technology
      • 10.2.4.1 Europe Machine Learning Market by Country
      • 10.2.4.2 Europe Natural Language Processing Market by Country
      • 10.2.4.3 Europe Context Awareness Market by Country
      • 10.2.4.4 Europe Computer Vision Market by Country
    • 10.2.5 Europe AI as a Service Market by Vertical
      • 10.2.5.1 Europe BFSI Market by Country
      • 10.2.5.2 Europe IT & Telecom Market by Country
      • 10.2.5.3 Europe Retail & eCommerce Market by Country
      • 10.2.5.4 Europe Manufacturing Market by Country
      • 10.2.5.5 Europe Healthcare & Life Sciences Market by Country
      • 10.2.5.6 Europe Government & Defense Market by Country
      • 10.2.5.7 Europe Energy & Utilities Market by Country
      • 10.2.5.8 Europe Others Market by Country
    • 10.2.6 Europe AI as a Service Market by Country
      • 10.2.6.1 Germany AI as a Service Market
        • 10.2.6.1.1 Germany AI as a Service Market by Organization Size
        • 10.2.6.1.2 Germany AI as a Service Market by Offering
        • 10.2.6.1.3 Germany AI as a Service Market by Cloud Type
        • 10.2.6.1.4 Germany AI as a Service Market by Technology
        • 10.2.6.1.5 Germany AI as a Service Market by Vertical
      • 10.2.6.2 UK AI as a Service Market
        • 10.2.6.2.1 UK AI as a Service Market by Organization Size
        • 10.2.6.2.2 UK AI as a Service Market by Offering
        • 10.2.6.2.3 UK AI as a Service Market by Cloud Type
        • 10.2.6.2.4 UK AI as a Service Market by Technology
        • 10.2.6.2.5 UK AI as a Service Market by Vertical
      • 10.2.6.3 France AI as a Service Market
        • 10.2.6.3.1 France AI as a Service Market by Organization Size
        • 10.2.6.3.2 France AI as a Service Market by Offering
        • 10.2.6.3.3 France AI as a Service Market by Cloud Type
        • 10.2.6.3.4 France AI as a Service Market by Technology
        • 10.2.6.3.5 France AI as a Service Market by Vertical
      • 10.2.6.4 Russia AI as a Service Market
        • 10.2.6.4.1 Russia AI as a Service Market by Organization Size
        • 10.2.6.4.2 Russia AI as a Service Market by Offering
        • 10.2.6.4.3 Russia AI as a Service Market by Cloud Type
        • 10.2.6.4.4 Russia AI as a Service Market by Technology
        • 10.2.6.4.5 Russia AI as a Service Market by Vertical
      • 10.2.6.5 Spain AI as a Service Market
        • 10.2.6.5.1 Spain AI as a Service Market by Organization Size
        • 10.2.6.5.2 Spain AI as a Service Market by Offering
        • 10.2.6.5.3 Spain AI as a Service Market by Cloud Type
        • 10.2.6.5.4 Spain AI as a Service Market by Technology
        • 10.2.6.5.5 Spain AI as a Service Market by Vertical
      • 10.2.6.6 Italy AI as a Service Market
        • 10.2.6.6.1 Italy AI as a Service Market by Organization Size
        • 10.2.6.6.2 Italy AI as a Service Market by Offering
        • 10.2.6.6.3 Italy AI as a Service Market by Cloud Type
        • 10.2.6.6.4 Italy AI as a Service Market by Technology
        • 10.2.6.6.5 Italy AI as a Service Market by Vertical
      • 10.2.6.7 Rest of Europe AI as a Service Market
        • 10.2.6.7.1 Rest of Europe AI as a Service Market by Organization Size
        • 10.2.6.7.2 Rest of Europe AI as a Service Market by Offering
        • 10.2.6.7.3 Rest of Europe AI as a Service Market by Cloud Type
        • 10.2.6.7.4 Rest of Europe AI as a Service Market by Technology
        • 10.2.6.7.5 Rest of Europe AI as a Service Market by Vertical
  • 10.3 Asia Pacific AI as a Service Market
    • 10.3.1 Asia Pacific AI as a Service Market by Organization Size
      • 10.3.1.1 Asia Pacific Large Enterprises Market by Country
      • 10.3.1.2 Asia Pacific Small & Medium-Sized Enterprises Market by Country
    • 10.3.2 Asia Pacific AI as a Service Market by Offering
      • 10.3.2.1 Asia Pacific Infrastructure as a Service Market by Country
      • 10.3.2.2 Asia Pacific Platform as a Service Market by Country
      • 10.3.2.3 Asia Pacific Software as a Service Market by Country
    • 10.3.3 Asia Pacific AI as a Service Market by Cloud Type
      • 10.3.3.1 Asia Pacific Public Cloud Market by Country
      • 10.3.3.2 Asia Pacific Private Cloud Market by Country
      • 10.3.3.3 Asia Pacific Hybrid Cloud Market by Country
    • 10.3.4 Asia Pacific AI as a Service Market by Technology
      • 10.3.4.1 Asia Pacific Machine Learning Market by Country
      • 10.3.4.2 Asia Pacific Natural Language Processing Market by Country
      • 10.3.4.3 Asia Pacific Context Awareness Market by Country
      • 10.3.4.4 Asia Pacific Computer Vision Market by Country
    • 10.3.5 Asia Pacific AI as a Service Market by Vertical
      • 10.3.5.1 Asia Pacific BFSI Market by Country
      • 10.3.5.2 Asia Pacific IT & Telecom Market by Country
      • 10.3.5.3 Asia Pacific Retail & eCommerce Market by Country
      • 10.3.5.4 Asia Pacific Manufacturing Market by Country
      • 10.3.5.5 Asia Pacific Healthcare & Life Sciences Market by Country
      • 10.3.5.6 Asia Pacific Government & Defense Market by Country
      • 10.3.5.7 Asia Pacific Energy & Utilities Market by Country
      • 10.3.5.8 Asia Pacific Others Market by Country
    • 10.3.6 Asia Pacific AI as a Service Market by Country
      • 10.3.6.1 China AI as a Service Market
        • 10.3.6.1.1 China AI as a Service Market by Organization Size
        • 10.3.6.1.2 China AI as a Service Market by Offering
        • 10.3.6.1.3 China AI as a Service Market by Cloud Type
        • 10.3.6.1.4 China AI as a Service Market by Technology
        • 10.3.6.1.5 China AI as a Service Market by Vertical
      • 10.3.6.2 Japan AI as a Service Market
        • 10.3.6.2.1 Japan AI as a Service Market by Organization Size
        • 10.3.6.2.2 Japan AI as a Service Market by Offering
        • 10.3.6.2.3 Japan AI as a Service Market by Cloud Type
        • 10.3.6.2.4 Japan AI as a Service Market by Technology
        • 10.3.6.2.5 Japan AI as a Service Market by Vertical
      • 10.3.6.3 India AI as a Service Market
        • 10.3.6.3.1 India AI as a Service Market by Organization Size
        • 10.3.6.3.2 India AI as a Service Market by Offering
        • 10.3.6.3.3 India AI as a Service Market by Cloud Type
        • 10.3.6.3.4 India AI as a Service Market by Technology
        • 10.3.6.3.5 India AI as a Service Market by Vertical
      • 10.3.6.4 South Korea AI as a Service Market
        • 10.3.6.4.1 South Korea AI as a Service Market by Organization Size
        • 10.3.6.4.2 South Korea AI as a Service Market by Offering
        • 10.3.6.4.3 South Korea AI as a Service Market by Cloud Type
        • 10.3.6.4.4 South Korea AI as a Service Market by Technology
        • 10.3.6.4.5 South Korea AI as a Service Market by Vertical
      • 10.3.6.5 Singapore AI as a Service Market
        • 10.3.6.5.1 Singapore AI as a Service Market by Organization Size
        • 10.3.6.5.2 Singapore AI as a Service Market by Offering
        • 10.3.6.5.3 Singapore AI as a Service Market by Cloud Type
        • 10.3.6.5.4 Singapore AI as a Service Market by Technology
        • 10.3.6.5.5 Singapore AI as a Service Market by Vertical
      • 10.3.6.6 Malaysia AI as a Service Market
        • 10.3.6.6.1 Malaysia AI as a Service Market by Organization Size
        • 10.3.6.6.2 Malaysia AI as a Service Market by Offering
        • 10.3.6.6.3 Malaysia AI as a Service Market by Cloud Type
        • 10.3.6.6.4 Malaysia AI as a Service Market by Technology
        • 10.3.6.6.5 Malaysia AI as a Service Market by Vertical
      • 10.3.6.7 Rest of Asia Pacific AI as a Service Market
        • 10.3.6.7.1 Rest of Asia Pacific AI as a Service Market by Organization Size
        • 10.3.6.7.2 Rest of Asia Pacific AI as a Service Market by Offering
        • 10.3.6.7.3 Rest of Asia Pacific AI as a Service Market by Cloud Type
        • 10.3.6.7.4 Rest of Asia Pacific AI as a Service Market by Technology
        • 10.3.6.7.5 Rest of Asia Pacific AI as a Service Market by Vertical
  • 10.4 LAMEA AI as a Service Market
    • 10.4.1 LAMEA AI as a Service Market by Organization Size
      • 10.4.1.1 LAMEA Large Enterprises Market by Country
      • 10.4.1.2 LAMEA Small & Medium-Sized Enterprises Market by Country
    • 10.4.2 LAMEA AI as a Service Market by Offering
      • 10.4.2.1 LAMEA Infrastructure as a Service Market by Country
      • 10.4.2.2 LAMEA Platform as a Service Market by Country
      • 10.4.2.3 LAMEA Software as a Service Market by Country
    • 10.4.3 LAMEA AI as a Service Market by Cloud Type
      • 10.4.3.1 LAMEA Public Cloud Market by Country
      • 10.4.3.2 LAMEA Private Cloud Market by Country
      • 10.4.3.3 LAMEA Hybrid Cloud Market by Country
    • 10.4.4 LAMEA AI as a Service Market by Technology
      • 10.4.4.1 LAMEA Machine Learning Market by Country
      • 10.4.4.2 LAMEA Natural Language Processing Market by Country
      • 10.4.4.3 LAMEA Context Awareness Market by Country
      • 10.4.4.4 LAMEA Computer Vision Market by Country
    • 10.4.5 LAMEA AI as a Service Market by Vertical
      • 10.4.5.1 LAMEA BFSI Market by Country
      • 10.4.5.2 LAMEA IT & Telecom Market by Country
      • 10.4.5.3 LAMEA Retail & eCommerce Market by Country
      • 10.4.5.4 LAMEA Manufacturing Market by Country
      • 10.4.5.5 LAMEA Healthcare & Life Sciences Market by Country
      • 10.4.5.6 LAMEA Government & Defense Market by Country
      • 10.4.5.7 LAMEA Energy & Utilities Market by Country
      • 10.4.5.8 LAMEA Others Market by Country
    • 10.4.6 LAMEA AI as a Service Market by Country
      • 10.4.6.1 Brazil AI as a Service Market
        • 10.4.6.1.1 Brazil AI as a Service Market by Organization Size
        • 10.4.6.1.2 Brazil AI as a Service Market by Offering
        • 10.4.6.1.3 Brazil AI as a Service Market by Cloud Type
        • 10.4.6.1.4 Brazil AI as a Service Market by Technology
        • 10.4.6.1.5 Brazil AI as a Service Market by Vertical
      • 10.4.6.2 Argentina AI as a Service Market
        • 10.4.6.2.1 Argentina AI as a Service Market by Organization Size
        • 10.4.6.2.2 Argentina AI as a Service Market by Offering
        • 10.4.6.2.3 Argentina AI as a Service Market by Cloud Type
        • 10.4.6.2.4 Argentina AI as a Service Market by Technology
        • 10.4.6.2.5 Argentina AI as a Service Market by Vertical
      • 10.4.6.3 UAE AI as a Service Market
        • 10.4.6.3.1 UAE AI as a Service Market by Organization Size
        • 10.4.6.3.2 UAE AI as a Service Market by Offering
        • 10.4.6.3.3 UAE AI as a Service Market by Cloud Type
        • 10.4.6.3.4 UAE AI as a Service Market by Technology
        • 10.4.6.3.5 UAE AI as a Service Market by Vertical
      • 10.4.6.4 Saudi Arabia AI as a Service Market
        • 10.4.6.4.1 Saudi Arabia AI as a Service Market by Organization Size
        • 10.4.6.4.2 Saudi Arabia AI as a Service Market by Offering
        • 10.4.6.4.3 Saudi Arabia AI as a Service Market by Cloud Type
        • 10.4.6.4.4 Saudi Arabia AI as a Service Market by Technology
        • 10.4.6.4.5 Saudi Arabia AI as a Service Market by Vertical
      • 10.4.6.5 South Africa AI as a Service Market
        • 10.4.6.5.1 South Africa AI as a Service Market by Organization Size
        • 10.4.6.5.2 South Africa AI as a Service Market by Offering
        • 10.4.6.5.3 South Africa AI as a Service Market by Cloud Type
        • 10.4.6.5.4 South Africa AI as a Service Market by Technology
        • 10.4.6.5.5 South Africa AI as a Service Market by Vertical
      • 10.4.6.6 Nigeria AI as a Service Market
        • 10.4.6.6.1 Nigeria AI as a Service Market by Organization Size
        • 10.4.6.6.2 Nigeria AI as a Service Market by Offering
        • 10.4.6.6.3 Nigeria AI as a Service Market by Cloud Type
        • 10.4.6.6.4 Nigeria AI as a Service Market by Technology
        • 10.4.6.6.5 Nigeria AI as a Service Market by Vertical
      • 10.4.6.7 Rest of LAMEA AI as a Service Market
        • 10.4.6.7.1 Rest of LAMEA AI as a Service Market by Organization Size
        • 10.4.6.7.2 Rest of LAMEA AI as a Service Market by Offering
        • 10.4.6.7.3 Rest of LAMEA AI as a Service Market by Cloud Type
        • 10.4.6.7.4 Rest of LAMEA AI as a Service Market by Technology
        • 10.4.6.7.5 Rest of LAMEA AI as a Service Market by Vertical

Chapter 11. Company Profiles

  • 11.1 IBM Corporation
    • 11.1.1 Company Overview
    • 11.1.2 Financial Analysis
    • 11.1.3 Regional & Segmental Analysis
    • 11.1.4 Research & Development Expenses
    • 11.1.5 Recent strategies and developments:
      • 11.1.5.1 Partnerships, Collaborations, and Agreements:
      • 11.1.5.2 Product Launches and Product Expansions:
      • 11.1.5.3 Acquisition and Mergers:
    • 11.1.6 SWOT Analysis
  • 11.2 Microsoft Corporation
    • 11.2.1 Company Overview
    • 11.2.2 Financial Analysis
    • 11.2.3 Segmental and Regional Analysis
    • 11.2.4 Research & Development Expenses
    • 11.2.5 Recent strategies and developments:
      • 11.2.5.1 Partnerships, Collaborations, and Agreements:
      • 11.2.5.2 Acquisition and Mergers:
      • 11.2.5.3 Product Launches and Product Expansions:
    • 11.2.6 SWOT Analysis
  • 11.3 Amazon Web Services, Inc. (Amazon.com, Inc.)
    • 11.3.1 Company Overview
    • 11.3.2 Financial Analysis
    • 11.3.3 Segmental Analysis
    • 11.3.4 Recent strategies and developments:
      • 11.3.4.1 Partnerships, Collaborations, and Agreements:
      • 11.3.4.2 Product Launches and Product Expansions:
    • 11.3.5 SWOT Analysis
  • 11.4 Oracle Corporation
    • 11.4.1 Company Overview
    • 11.4.2 Financial Analysis
    • 11.4.3 Segmental and Regional Analysis
    • 11.4.4 Research & Development Expense
    • 11.4.5 Recent strategies and developments:
      • 11.4.5.1 Partnerships, Collaborations, and Agreements:
      • 11.4.5.2 Product Launches and Product Expansions:
      • 11.4.5.3 Acquisition and Mergers:
    • 11.4.6 SWOT Analysis
  • 11.5 Google LLC (Alphabet Inc.)
    • 11.5.1 Company Overview
    • 11.5.2 Financial Analysis
    • 11.5.3 Segmental and Regional Analysis
    • 11.5.4 Research & Development Expense
    • 11.5.5 Recent strategies and developments:
      • 11.5.5.1 Partnerships, Collaborations, and Agreements:
      • 11.5.5.2 Product Launches and Product Expansions:
    • 11.5.6 SWOT Analysis
  • 11.6 Fair Isaac Corporation (FICO)
    • 11.6.1 Company Overview
    • 11.6.2 Financial Analysis
    • 11.6.3 Segmental and Regional Analysis
    • 11.6.4 Research & Development Expenses
    • 11.6.5 Recent strategies and developments:
      • 11.6.5.1 Partnerships, Collaborations, and Agreements:
    • 11.6.6 SWOT Analysis
  • 11.7 Baidu, Inc.
    • 11.7.1 Company Overview
    • 11.7.2 Financial Analysis
    • 11.7.3 Segmental Analysis
    • 11.7.4 Research & Development Expenses
    • 11.7.5 Recent strategies and developments:
      • 11.7.5.1 Partnerships, Collaborations, and Agreements:
      • 11.7.5.2 Product Launches and Product Expansions:
    • 11.7.6 SWOT Analysis
  • 11.8 SAS Institute, Inc.
    • 11.8.1 Company Overview
    • 11.8.2 Recent strategies and developments:
      • 11.8.2.1 Partnerships, Collaborations, and Agreements:
      • 11.8.2.2 Acquisition and Mergers:
      • 11.8.2.3 Product Launches and Product Expansions:
    • 11.8.3 SWOT Analysis
  • 11.9 SAP SE
    • 11.9.1 Company Overview
    • 11.9.2 Financial Analysis
    • 11.9.3 Segmental and Regional Analysis
    • 11.9.4 Research & Development Expense
    • 11.9.5 SWOT Analysis
  • 11.10. Salesforce, Inc.
    • 11.10.1 Company Overview
    • 11.10.2 Financial Analysis
    • 11.10.3 Regional Analysis
    • 11.10.4 Research & Development Expense
    • 11.10.5 Recent strategies and developments:
      • 11.10.5.1 Partnerships, Collaborations, and Agreements:
    • 11.10.6 SWOT Analysis

Chapter 12. Winning Imperatives for AI as a Service Market

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