MLaaS(Machine Learning as a Service)시장 규모는 2024년 96억 달러에 달했습니다. IMARC Group은 향후 시장이 2033년까지 841억 달러에 이를 것으로 예상하며, 2025년부터 2033년까지 25.88%의 성장률(CAGR)을 나타낼 것으로 예측했습니다. 클라우드 기반 솔루션에 대한 수요 증가, 인공지능(AI) 진보, 사물 인터넷(IoT) 디바이스의 데이터 급증, 금융, 헬스케어, 소매 등 업계에서 예측 분석의 필요성은 시장 성장을 가속하는 요인의 일부입니다.
MLaaS(Machine Learning as a Service)은 클라우드 기반 플랫폼을 통해 머신러닝 기능과 인프라에 대한 액세스를 제공하는 종합적인 솔루션입니다. MLaaS는 하드웨어, 소프트웨어 및 전문적인 전문 지식에 많은 투자를 하지 않고도 기업이 머신러닝의 힘을 활용할 수 있도록 합니다. MLaaS는 머신러닝 모델의 개발, 배포 및 관리를 용이하게 하는 다양한 서비스, 도구 및 리소스를 제공합니다. MLaaS는 개발자와 데이터 과학자가 쉽게 액세스하고 사용할 수 있도록 사전 구축된 알고리즘과 모델을 광범위하게 제공합니다.
세계 MLaaS(Machine Learning as a Service) 시장
현재 대규모 내부 인프라와 전문 지식 없이 머신러닝(ML) 기능을 활용할 수 있는 MLaaS에 대한 수요가 증가함에 따라 시장 성장이 추진되고 있습니다. 이 외에도 효율성과 생산성을 높이고 수작업으로 인한 오류 발생을 줄이기 위해 다양한 비즈니스 업무의 자동화가 진행되고 있는 것도 시장 성장을 뒷받침하고 있습니다. 또한, 딥러닝과 강화 학습을 포함한 ML 알고리즘의 진보가 진행되고 있는 것도 시장 전망을 양호하게 하고 있습니다. 이와는 별도로, 데이터로부터 귀중한 통찰력을 끌어내기 위해 최첨단 기술을 활용하는 기업에 의한 MLaaS의 채용이 증가하고 있는 것도 시장의 성장을 지지하고 있습니다. 게다가 비즈니스 이니셔티브를 가속화하고, 보다 빠른 타임투 타임 마켓을 달성하고, 보다 신속한 투자 수익률(ROI)을 실현하기 위해 자동화를 중시하는 움직임이 증가하고 있는 것도 시장 성장에 기여하고 있습니다.
인공지능(AI) 솔루션에 대한 수요 증가
현재 다양한 업계에서 AI 솔루션의 채택이 증가하고 있다는 것은 MLaaS 수요를 촉진하고 있습니다. 기업이 프로세스 최적화, 고객 경험 향상, 데이터에서 실용적인 통찰력을 얻는 AI의 가치를 인식함에 따라 MLaaS 솔루션에 대한 수요가 증가하고 있습니다. 기업은 MLaaS를 활용하여 하드웨어나 전문 인력에 많은 투자를 하지 않고 머신러닝 알고리즘의 파워를 활용하고 있습니다. 또한 MLaaS 솔루션은 기업이 쉽게 구현할 수 있는 구축된 머신러닝 모델과 데이터 처리 도구를 제공합니다. 이에 따라 중소기업에서도 AI를 이용할 수 있게 되어 자사에서 AI를 개발하기 위한 리소스를 많이 가진 대기업과 경쟁할 수 있게 되었습니다.
클라우드 컴퓨팅의 인기 증가
클라우드 컴퓨팅의 인기가 높아짐에 따라 MLaaS 수요가 크게 늘어나고 있습니다. 클라우드 컴퓨팅은 머신러닝 모델을 배포하기 위한 견고하고 확장 가능한 환경을 제공하므로, 기업은 고가의 하드웨어나 소프트웨어에 투자하지 않고도 최첨단 ML 기능을 활용할 수 있습니다. 이 외에도 클라우드 컴퓨팅은 머신러닝에 필수적인 대량의 데이터 저장, 처리 및 분석을 용이하게 합니다. 클라우드 기반의 MLaaS 솔루션은 이러한 엄청난 데이터 세트를 효율적으로 처리하고, 고속 데이터 처리 능력과 실시간 분석을 제공함으로써 신속한 의사 결정을 가능하게 하고 기업의 경쟁력을 높입니다. 또한 클라우드 플랫폼은 서로 다른 부서나 조직 간에 머신러닝 모델과 데이터 간편한 협업과 원활한 공유를 보장합니다. 이러한 협업의 용이성은 기업이 AI 주도의 디지털 전환을 추진하는데 유익하며, MLaaS의 도입 확대로 이어집니다.
데이터 생성 증가
현재 세계에서 데이터 생성량이 증가하고 있으며, MLaaS 수요를 크게 밀어 올리고 있습니다. 기업이 더 많은 데이터를 생성하고 수집함에 따라 거기에서 가치를 끌어내는 ML의 가능성도 높아지고 있습니다. MLaaS 제공업체는 귀중한 통찰력을 얻고 정보를 기반으로 비즈니스 의사 결정을 내릴 수 있도록 이러한 데이터에서 교육할 수 있는 기성품 머신러닝 모델을 제공합니다. 게다가 방대한 데이터 세트의 실시간 분석은 속도가 빠른 데이터 구동 시나리오에서 매우 중요합니다. 기업은 사용 가능한 최신 정보를 바탕으로 신속하게 의사 결정을 내려야 합니다. 대규모 데이터 세트를 실시간으로 처리할 수 있는 기능을 갖춘 MLaaS 플랫폼은 비즈니스에 즉각적인 통찰력을 제공하여 업무 효율성을 개선하고 신속하고 데이터 중심의 의사 결정을 가능하게 합니다.
The global machine learning as a service (MLaaS) market size reached USD 9.6 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 84.1 Billion by 2033, exhibiting a growth rate (CAGR) of 25.88% during 2025-2033. The growing demand for cloud-based solutions, advancements in artificial intelligence (AI), proliferation of data from internet of things (IoT) devices, and the need for predictive analytics in industries including finance, healthcare, and retail are some of the factors propelling the market growth.
Machine learning as a service (MLaaS) is a comprehensive solution that provides access to machine learning capabilities and infrastructure through a cloud-based platform. It enables organizations to leverage the power of machine learning without the need for significant investments in hardware, software, and specialized expertise. MLaaS offers a range of services, tools, and resources that facilitate the development, deployment, and management of machine learning models. It provides a wide array of pre-built algorithms and models that can be easily accessed and utilized by developers and data scientists.
Global Machine Learning As A Service (MLaaS) Market
At present, the increasing demand for MLaaS to access machine learning (ML) capabilities without the need for extensive in-house infrastructure and expertise is impelling the growth of the market. Besides this, the rising automation of various business operations to increase efficiency and productivity and reduce the occurrence of manual errors is propelling the growth of the market. In addition, the growing advancements in ML algorithms, including deep learning and reinforcement learning, are offering a favorable market outlook. Apart from this, the increasing employment of MLaaS by businesses to leverage cutting-edge techniques to extract valuable insights from their data is supporting the growth of the market. Additionally, the rising emphasis on automation to accelerate business initiatives, achieve faster time-to-time markets, and realize quicker returns on investments (ROI) is contributing to the growth of the market.
Rising demand for artificial intelligence (AI) solutions
At present, the increasing employment of AI solutions across various industries is fueling the demand for MLaaS. As organizations recognize the value of AI in optimizing processes, enhancing customer experiences, and gaining actionable insights from data, the demand for MLaaS solutions is increasing. Businesses are leveraging MLaaS to harness the power of machine learning algorithms without the need for significant investments in hardware and specialized talent. MLaaS solutions also offer pre-built machine learning models and data handling tools which businesses can easily implement. It has made AI accessible to small and medium-sized businesses, enabling them to compete with larger companies that have more resources for developing AI in-house.
Growing popularity of cloud computing
The rising popularity of cloud computing is significantly driving the demand for MLaaS as it provides a robust and scalable environment for deploying machine learning models, enabling businesses to access cutting-edge ML capabilities without investing in expensive hardware or software. Besides this, cloud computing facilitates easy storage, processing, and analysis of large volumes of data, which are crucial for machine learning. Cloud-based MLaaS solutions can handle these vast datasets efficiently, providing high-speed data processing capabilities and real-time analytics, thereby enabling quick decision-making and creating a competitive edge for businesses. In addition, cloud platforms ensure easy collaboration and seamless sharing of machine learning models and data across different departments or even different organizations. This ease of collaboration can be instrumental in businesses to drive AI-driven digital transformation, thereby leading to increased uptake of MLaaS.
Increasing generation of data
Presently, there is an increase in data generation worldwide, which is significantly propelling the demand for MLaaS. As businesses generate and collect more data, the potential for ML to extract value from it also increases. MLaaS providers deliver ready-made machine learning models that can be trained on this data to gain valuable insights and make informed business decisions. Moreover, the real-time analysis of massive datasets is crucial in fast-paced, data-driven scenarios. Businesses need to make decisions quickly based on the latest information available. MLaaS platforms, equipped with the capability to process large datasets in real time, can provide businesses with immediate insights, thereby improving their operational efficiency and enabling swift and data-driven decision-making.
Software
Services
Services dominate the market
MLaaS providers offer pre-built and customizable machine learning models, which simplifies the adoption of machine learning technologies, especially for small and medium enterprises (SMEs) that may lack the resources or expertise to develop these models in-house. Developing and implementing machine learning models in-house can be quite expensive, considering the costs of hiring skilled data scientists, investing in robust hardware, and maintaining the necessary software. MLaaS provides a more cost-effective alternative as it operates on a pay-as-you-go model, allowing businesses to only pay for what they use. MLaaS providers also offer ongoing support and maintenance services, which can help businesses overcome any challenges they encounter when using the technology. This support can help businesses mitigate risks and ensure that their machine-learning models are performing optimally.
Small and Medium-sized Enterprises
Large Enterprises
Large enterprises hold the largest share in the market
Large enterprises are increasingly turning to machine learning as a service (MLaaS) as it is a convenient, scalable, and cost-effective solution for implementing advanced machine learning capabilities, allowing large businesses to make data-driven decisions and gain a competitive edge. The vast amount of data generated by these enterprises necessitates efficient tools to extract meaningful insights, and MLaaS offers robust machine-learning models capable of processing this information swiftly and effectively. Moreover, in a dynamic business environment, large enterprises need to respond spontaneously to changing market conditions. With MLaaS, they can leverage real-time analytics to derive immediate insights from their data, enhancing their decision-making process and operational efficiency. This is particularly beneficial for industries that operate in fast-paced environments, such as finance, technology, and e-commerce.
Marketing and Advertising
Fraud Detection and Risk Management
Predictive Analytics
Augmented and Virtual Reality
Natural Language Processing
Computer Vision
Security and Surveillance
Others
Marketing and advertising hold the biggest share in the market
Marketing and advertising industries increasingly require machine learning as a service (MLaaS) due to its potential to transform their operations and customer engagements significantly. In these fields, understanding consumer behavior and preferences is of utmost importance, and the ability to analyze vast amounts of customer data is vital. MLaaS provides robust machine learning models that can process and analyze this data, offering valuable insights about customers, enabling personalized marketing, and improving target advertising. MLaaS is also used to segment customers based on various characteristics, enabling marketers to tailor their messages and offers to specific groups. It allows for precise targeting, which can significantly enhance the effectiveness of marketing campaigns.
IT and Telecom
Automotive
Healthcare
Aerospace and Defense
Retail
Government
BFSI
Others
BFSI holds the maximum share of the market
The banking, financial services and insurance (BFSI) sector is relying on machine learning as a service (MLaaS) due to its transformative potential to streamline operations, enhance customer experiences, and bolster security measures. The BFSI sector deals with enormous amounts of data, and MLaaS provides an efficient way to process, analyze, and draw actionable insights from this data, enabling financial institutions to make informed decisions. MLaaS plays a pivotal role in personalizing customer experiences in the BFSI sector. By analyzing customer data, machine learning models can identify individual behaviors and preferences, enabling financial institutions to tailor their services to each customer's unique needs. Furthermore, by leveraging MLaaS, financial institutions can build predictive models that can alert them to potential fraud or risks in real-time, significantly enhancing their security measures and customer trust.
North America
United States
Canada
Asia-Pacific
China
Japan
India
South Korea
Australia
Indonesia
Others
Europe
Germany
France
United Kingdom
Italy
Spain
Russia
Others
Latin America
Brazil
Mexico
Others
Middle East and Africa
North America exhibits a clear dominance, accounting for the largest machine learning as a service (MLaaS) market share
The report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and Others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa.
North America held the biggest market share due to the rising number of businesses that are integrating AI and ML in their operations to achieve efficiency and scalability and minimize the involvement of humans.
Another contributing aspect is the rising generation of data through various online channels. Besides this, the increasing number of cyber threats and data breaches is propelling the growth of the market.
Asia Pacific is estimated to expand further in this domain due to the rising popularity of cloud computing and edge computing. Apart from this, the rising focus on automating various business operations is strengthening the growth of the market.
Key market players are investing in research operations to improve their machine-learning services. They are also providing cutting-edge machine learning tools and capabilities that are efficient, scalable, and easy to use. Top companies are entering into strategic partnerships with other tech companies, startups, and research institutions to deliver more comprehensive and innovative solutions. They are also focusing on providing training and certification programs to create a skilled workforce. Leading companies are taking initiatives to enhance the security features of their platforms. They are implementing stronger data encryption, enhancing access controls, and using machine learning to detect and respond to security threats.
Amazon.com Inc.
Bigml Inc.
Fair Isaac Corporation
Google LLC (Alphabet Inc.)
H2O.ai Inc.
Hewlett Packard Enterprise Development LP
Iflowsoft Solutions Inc.
International Business Machines Corporation
Microsoft Corporation
MonkeyLearn
Sas Institute Inc.
Yottamine Analytics Inc.