Machine Learning as a Service (MLaaS) Global Market Report 2024

The machine learning as a service (MLaaS) market size has grown exponentially in recent years. It will grow from $42.09 billion in 2023 to $57.88 billion in 2024 at a compound annual growth rate (CAGR) of 37.5%. The growth in the historic period can be attributed to the growth of big data, increased adoption of machine learning, advancements in deep learning, the rise of data science and AI, and increased awareness of predictive analytics.

The machine learning as a service (MLaaS) market size is expected to see exponential growth in the next few years. It will grow to $203.1 billion in 2028 at a compound annual growth rate (CAGR) of 36.9%. The forecasted growth in the upcoming period can be attributed to several factors, including the increasing availability of industry-specific solutions, the rise of explainable AI, the expansion of autonomous systems, the adoption of hybrid cloud deployments, and the implementation of enhanced security and privacy features. Major trends expected during this period include the development of vertical-specific machine learning platforms, the integration of AI-enhanced automation, efforts to democratize machine learning, the promotion of collaborative machine learning approaches, and the implementation of continuous learning systems.

The increasing integration of cloud technologies is expected to drive the growth of the machine learning as a service (MLaaS) market in the future. Cloud technology integration involves connecting various cloud-based systems into a cohesive whole or linking cloud-based systems with on-premises systems. Cloud technologies leverage MLaaS to provide users with accessible, scalable, and cost-effective machine learning capabilities. This enables users to utilize pre-trained models and tools for various applications without requiring extensive expertise in machine learning or infrastructure management. For example, in December 2023, Eurostat reported that 42.5% of EU enterprises purchased cloud computing services, primarily for email, file storage, and office software, marking a 4.2 percentage point increase from 2021. Additionally, data from Augusta Free Press in December 2022 indicated that global digital transformation spending reached approximately $1.85 trillion, a 16% increase from the previous year. Consequently, the increasing integration of cloud technologies is propelling the growth of the MLaaS market.

Major companies in the machine learning as a service (MLaaS) market are innovating by offering services such as Kubeflow as a service to democratize AI development. Kubeflow-as-a-Service (KFaaS) is a managed environment that enables users to utilize Kubeflow's capabilities for machine learning (ML) projects without managing the underlying infrastructure. For example, in February 2023, Civo, a UK-based web hosting company, introduced Kubeflow as a service. With a fully managed development environmentsuch as Civo KFaaS, users can access the service provider's compute capabilities without dealing with infrastructure management. KFaaS streamlines ML project workflows by integrating with popular ML tools and platforms such as TensorFlow, PyTorch, RStudio, Visual Studio Code, and Jupyter notebooks.

In September 2021, DataRobot Inc., a US-based technology company, acquired Decision AI for an undisclosed amount. This acquisition is intended to enhance DataRobot's existing no-code app development and decision intelligence flow capabilities, allowing users to optimize dynamic business processes and make faster, more informed decisions. The acquisition is part of DataRobot's strategy to expand its AI Platform's decision intelligence suite and enhance the ability to make smarter decisions using machine learning. Decision AI, based in the US, specializes in Machine Learning as a Service (MLaaS).

Major companies operating in the machine learning as a service (mlaas) market report are Amazon.com Inc., Alphabet Inc., Microsoft Corporation, Meta Platforms Inc., Intel Corporation, International Business Machines Corporation, Oracle Corporation, Mitsubishi Electric Corporation, SAP SE, Hewlett Packard Enterprise Company, NVIDIA Corporation, Tata Consultancy Services Limited, Infosys Limited, Wipro Ltd., Fair Isaac Corporation, Databricks Inc., TIBCO Software Inc., Cyient Ltd., Dataiku Ltd., H2O.ai Inc., Iflowsoft Solutions Inc., BigML Inc., AscentCore, MonkeyLearn Inc., Sift Science Inc., Yottamine Analytics LLC.

North America was the largest region in the machine learning as a service (MLaaS) market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the machine learning as a service (mlaas) market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the machine learning as a service (mlaas) market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Machine learning as a service (MLaaS) is a cloud-based system that offers users access to tools and resources for developing, deploying, and managing machine learning (ML) models. It enables individuals and organizations to leverage ML capabilities without needing extensive expertise in algorithms, programming, or infrastructure.

The key components of MLaaS are software tools and services. Software tools are cloud-based platforms that provide ML tools and services to support the daily work of data scientists and data engineers. MLaaS is used by organizations of all sizes, including small and medium enterprises (SMEs) and large enterprises. It is employed in various applications such as marketing and advertisement, predictive maintenance, automated network management, fraud detection, risk management, sentiment analysis, and more. MLaaS finds application in industries such as banking, financial services and insurance (BFSI), information technology and telecom, automotive, healthcare, aerospace & defense, retail, government, and others.

The machine learning as a service (MLaaS) market research report is one of a series of new reports that provides machine learning as a service (MLaaS) market statistics, including machine learning as a service (MLaaS) industry global market size, regional shares, competitors with machine learning as a service (MLaaS) market share, detailed machine learning as a service (MLaaS) market segments, market trends, and opportunities, and any further data you may need to thrive in the machine learning as a service (MLaaS) industry. This machine learning as a service (MLaaS) market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The machine learning as a service (MLaaS) market includes revenues earned by entities by providing services such as predictive analytics, natural language processing, image and video recognition, speech recognition, recommendation systems, and anomaly detection services. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included. The machine learning as a service (MLaaS) market consists of sales of central processing units (CPUs), graphic processing units (GPUs), and field-programmable gate arrays (FPGAs). Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.


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