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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
상품코드 : 1430809
리서치사 : KBV Research
발행일 : 2024년 01월
페이지 정보 : 영문 383 Pages
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한글목차

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

제2장 시장 요람

제3장 시장 개요

제4장 경쟁 분석 - 세계

제5장 세계 시장 : 조직 규모별

제6장 세계 시장 : 제공별

제7장 세계 시장 : 클라우드 유형별

제8장 세계 시장 : 기술별

제9장 세계 시장 : 업계별

제10장 세계 시장 : 지역별

제11장 기업 개요

제12장 AI as a Service 시장을 위한 성공 필수 조건

LSH
영문 목차

영문목차

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

List of Key Companies Profiled

Global AI as a Service Market Report Segmentation

By Organization Size

By Offering

By Cloud Type

By Technology

By Vertical

By Geography

Table of Contents

Chapter 1. Market Scope & Methodology

Chapter 2. Market at a Glance

Chapter 3. Market Overview

Chapter 4. Competition Analysis - Global

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

Chapter 6. Global AI as a Service Market by Offering

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

Chapter 8. Global AI as a Service Market by Technology

Chapter 9. Global AI as a Service Market by Vertical

Chapter 10. Global AI as a Service Market by Region

Chapter 11. Company Profiles

Chapter 12. Winning Imperatives for AI as a Service Market

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