With a focus on actionable insights and strategic value, The Business Research Company’s 2026 market reports include market attractiveness scoring, total addressable market sizing, company benchmarking matrices, interactive Excel dashboards, deeper supply chain intelligence, emerging startup tracking, and granular product-level insights.
How Much Will The Automated Machine Learning Solution Market Be Worth By 2030?
The automated machine learning solution market has seen a rapid expansion in its size over recent years. It will grow from $3.11 billion in 2025 to $4.59 billion in 2026 at a compound annual growth rate (CAGR) of 47.5%. Key factors contributing to this historical growth include the increasing integration of machine learning within businesses, the escalating intricacy of ML model creation, a scarcity of proficient data scientists, the imperative for quicker model deployment, and the emergence of cloud computing platforms.
The automated machine learning solution market is anticipated to experience substantial expansion over the coming years. It will grow to $21.72 billion in 2030 at a compound annual growth rate (CAGR) of 47.5%. This projected increase is driven by factors such as the integration with AI-powered analytics platforms, the growing acceptance of cloud-based AutoML solutions, wider application in healthcare and retail, the need for automated model governance and oversight, and increased uptake by both SMEs and large enterprises. Key developments expected during this period involve automated feature engineering, hyperparameter optimization tools, ready-made machine learning pipelines, automatic model assessment and validation, and integrated development environments (IDEs) for AutoML.
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The Key Driver Behind The Automated Machine Learning Solution Market’s 47.5% CAGR
The automated machine learning solution market is anticipated to expand due to the growing demand for industrial automation. Industrial automation involves utilizing machines, control systems, and software to operate industrial processes with reduced human involvement. This rise in industrial automation stems from a heightened need for improved productivity and quicker manufacturing outcomes. Within industrial automation, automated machine learning solutions are employed to analyze real-time data and automatically enhance equipment performance, leading to greater efficiency. As an illustration, the International Federation of Robotics (IFR), a Germany-based non-profit organization, reported in September 2024 that industrial robot installations in the UK saw a 51% increase, reaching 3,830 units. Concurrently, in the Americas, more than 50,000 units were installed for the third consecutive year, amounting to 55,389 units in 2023. Consequently, the escalating demand for industrial automation is set to fuel the expansion of the automated machine learning solution market.
Automated Machine Learning Solution Market Classification: Main Segments And Detailed Subsegments
The automated machine learning solution market covered in this report is segmented –
1) By Offering: Platform, Service
2) By Deployment: On-Premise, Cloud
3) By Enterprise Size: Large Enterprises, SMEs
4) By End-Users: BFSI, Retail And E-Commerce, Healthcare, Manufacturing
Subsegments:
1) By Platform: Cloud-Based Platforms, On-Premises Platforms, Auto ML Tools
2) By Service: Consulting Services, Implementation Services, Support And Maintenance Services, Training And Workshops
Automated Machine Learning Solution Market Strategic Shifts: What Leading Players Are Prioritizing
Major companies operating in the automated machine learning solution market are implementing advanced technological innovations to maintain their competitive edge. These advancements in automated ML solutions focus on improving model interpretability and integration, leading to more efficient and streamlined development of machine learning models. As an illustration, in April 2023, AND Solutions Pte Ltd., a Singaporean fintech firm specializing in automated machine learning solution platforms, introduced the NIKO AutoML platform. This innovative machine-learning tool is designed to simplify and accelerate the development of prediction models. The platform provides a range of features and tools, empowering users to rapidly and easily create and deploy high-quality machine learning models without requiring coding or data science expertise. Its user-friendly interface guides individuals through each step of the process, delivering superior results significantly faster than conventional methods. NIKO AutoML delivers notable advantages such as rapid and precise model creation, an optimized workflow, enhanced productivity, and greater cost-effectiveness.
Automated Machine Learning Solution Market Company Analysis: Major Industry Participants
Major companies operating in the automated machine learning solution market are Microsoft Corporation; Amazon Web Services Inc; Microsoft Azure Automated Machine Learning; International Business Machines Corporation; Oracle; SAS Institute Inc; Databricks; Alteryx; H2O.ai; Dataiku; Datarobot Inc; KNIME; Peltarion; RapidMiner; Auger.AI; BigML; dotData Inc; Big Squid Inc; Determined.AI Inc; Turi
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Automated Machine Learning Solution Market Global Regional Breakdown: Key Regions Analyzed
North America was the largest region in the automated machine learning solution market in 2025. The regions covered in the automated machine learning solution market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.
