What Has Been The Historical And Current Growth Of The Automated Machine Learning (AutoML) Market?
The automated machine learning (automl) market has seen considerable growth due to a variety of factors.
•The market value of automated machine learning (AutoML) has seen significant expansion in the past few years. It is projected to escalate from $1.64 billion in 2024 to $2.35 billion in 2025, with a compound annual growth rate (CAGR) of 43.6%.
Factors such as the intricate nature of machine learning, lack of data science expertise, the need for rapid solutions, progress in AI and computational capacity, and cost-effectiveness have been contributing to its growth during the historic period.
What Is The Forecast For The Automated Machine Learning (AutoML) Market By 2029?
The automated machine learning (automl) market is expected to maintain its strong growth trajectory in upcoming years.
• Expectations are high for the automated machine learning (AutoML) market size, which is forecasted to witness substantial growth in the upcoming years. The market is projected to register a sizeable increase to $10.93 billion by 2029, growing at a compound annual growth rate (CAGR) of 46.8%.
The forecasted growth can be credited to ai integration across different sectors, an increase in IoT and big data, the emergence of edge computing, hybrid cloud and on-site solutions, along with regulatory compliance requirements. Significant trends during the forecast period are expected to be automated feature engineering, advancements in federated learning, explainable ai and model interpretability, AutoML for unstructured data and AutoML application in autonomous systems.
What Are The Essential Drivers Behind The Growth Of The Automated Machine Learning (AutoML) Market?
The escalating demand for sophisticated fraud detection solutions is predicted to fuel the expansion of the automated machine learning (AutoML) market in the future. The process of fraud detection entails the identification and deterrence of fraudulent actions or conduct within a system or organization. Automated machine learning (AutoML) can be implemented for fraud detection, utilizing its capacity to handle and scrutinize large quantities of data, recognize patterns, and unearth irregularities suggestive of fraudulent activities. For example, in February 2024, Allianz Insurance plc, a Germany-based firm that provides insurance and asset management services, reported that they had exposed $95.2 million (£77.4 million) worth of claims fraud in 2023, which was an increase from the $86.96 million (£70.7 million) disclosed in 2022. Consequently, the surging demand for sophisticated fraud detection solutions is responsible for the growth of the automated machine learning (AutoML) market.
How Is The Global Automated Machine Learning (AutoML) Market Divided Into Key Segments?
The automated machine learning (AutoML) market covered in this report is segmented –
1) By Offering: Solutions, Services
2) By Deployment: Cloud, On-Premises
3) By Enterprise: Small And Medium Enterprise, Large Enterprise
4) By Application: Data Processing, Feature Engineering, Model Selection, Hyperparameter Optimization And Tuning, Model Assembling, Other Applications
5) By End User: Banking, Financial Services And Insurance (BFSI), Retail And E-Commerce, Healthcare, Manufacturing, Other End Users
Subsegments:
1) By Solutions: Cloud-Based Solutions, On-Premises Solutions, Integrated Development Environments (IDEs)
2) By Services: Consulting Services, Implementation Services, Training And Support Services
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What Trends Are Reshaping The Future Of The Automated Machine Learning (AutoML) Market?
The increased focus on technological advancements is a prominent trend making waves in the automated machine learning (AutoML) market. Companies leading the pack in the AutoML market are leveraging novel technologies in an effort to maintain a competitive edge. On a case in point, in April 2023, the Singapore-based fintech firm AND Solutions Pte Ltd., known for providing AutoML platforms, announced the launch of the NIKO AutoML platform. This state-of-the-art machine learning tool is designed with the goal of simplifying and accelerating the development of prediction models. This platform brings a multitude of tools and features to the table, which empower users to swiftly build and roll out high-calibre machine learning models, bypassing the need for coding or data science expertise. The platform's user-friendly interface guides users at every step of the process, delivering superior results in a shorter time than conventional methods. The salient advantages of NIKO AutoML include speedy and precise model creation, smoother workflow, heightened productivity, and improved cost efficiency.
Who Are the Key Players in the Automated Machine Learning (AutoML) Market?
Major companies operating in the automated machine learning (AutoML) market include:
• Google LLC
• Microsoft Corporation
• Amazon Web Services Inc.
• International Business Machines Corporation
• Oracle Corporation
• Salesforce Inc.
• Teradata Corporation
• Alteryx
• Altair Engineering Inc.
• EdgeVerve Systems Limited
• TIBCO Software Inc.
• DataRobot Inc.
• Dataiku
• BigPanda.
• H2O.ai Inc.
• KNIME
• Cognitivescale
• Anyscale Inc.
• RapidMiner
• Squark AI Inc.
• Auger.AI
• DotData Inc.
• BigML Inc.
• Valohai
• DarwinAI
• Aible Inc.
• SigOpt
• Zerion
• Xpanse AI
• Neptune Labs
What are the Regional Insights into the Automated Machine Learning (AutoML) Market?
North America was the largest region in the automated machine learning (AutoML) market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the automated machine learning (AutoML) market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa
