Chicago, May 24, 2023 (GLOBE NEWSWIRE) -- The global Automated Machine Learning (AutoML) Market size is projected to grow from USD 1.0 billion in 2023 to USD 6.4 billion by 2028, at a CAGR of 44.6% during the forecast period, according to a new report by MarketsandMarkets™. No code and low code platforms have revolutionized the way businesses approach machine learning. They allow users with little to no programming experience to build and deploy machine learning models quickly and easily. AutoML tools in no code and low code platforms offer a streamlined approach to automate and optimize the model-building process.
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324 - Tables
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347 - Pages
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Scope of the Report
| Report Metrics | Details |
| Market size available for years | 2017–2028 |
| Base year considered | 2023 |
| Forecast period | 2023–2028 |
| Forecast units | Value (USD Million/Billion) |
| Segments covered | Offering, Application, Vertical And Region |
| Regions covered | North America, Europe, Asia Pacific, Middle East & Africa, and Latin America |
| Companies covered | IBM (US), Oracle (US), Microsoft (US), ServiceNow (US), Google (US), Baidu (China), AWS (US), Alteryx (US), Salesforce (US), Altair (US), Teradata (US), H2O.ai (US), DataRobot (US), BigML (US), Databricks (US), Dataiku (France), Alibaba Cloud (China), Appier (Taiwan), Squark (US), Aible (US), Datafold (US), Boost.ai (Norway), Tazi.ai (US), Akkio (US), Valohai (Finland), dotData (US), Qlik (US), Mathworks (US), HPE (US), and SparkCognition (US). |
Based on offering, the market for Automated Machine Learning is segmented into solutions and services. The solutions segment is expected to grow at a higher Compound Annual Growth Rate (CAGR) during the forecast period. The solutions segment is bifurcated based on type and deployment. By type, the segment studies platforms and software applications. By deployment it is further bifurcated into cloud and on-premises. AutoML solutions are designed to automate many of the tasks involved in developing and deploying machine learning models, making it easier for organizations to leverage the power of machine learning without requiring significant expertise in data science or machine learning. AutoML solutions are becoming an increasingly important tool for organizations looking to leverage the power of machine learning to gain insights from their data and make better decisions.
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Based on application, the market is segmented into data processing, feature engineering, model selection, hyperparameter optimization and tuning, model assembling, and other applications (Evaluation metric selection, monitoring and problem checking, and result analysis). These capabilities are crucial to the success of AutoML platforms as they enable users to create accurate and reliable models without the need for extensive knowledge of machine learning algorithms. AutoML platforms that provide these capabilities allow domain experts to build machine learning applications without significant knowledge of statistics and machine learning, thus increasing the speed and efficiency of model creation.
Based on vertical, the automated machine learning market is segmented into BFSI, retail & eCommerce, telecommunications, manufacturing, healthcare & life sciences, IT/ITeS, automotive, transportation, and logistics, government & defense, media & entertainment, and other verticals (education and transportation and logistics). Many businesses are rapidly using machine learning and artificial intelligence (AI). There is an increasing trend in investment banking to replace human labor with this new technology, especially when it comes to processing and assimilation of massive volumes of data. For instance, several investment banks have replaced entry-level financial analysts with automated systems to analyze financial data and generate insightful conclusions. Data validation and ensuring that data sources from various systems are synced is done using AI bots. The healthcare & life sciences industry verticals are expected to grow at the highest CAGR during the forecast period.
The Automated Machine Learning market is segmented into five regions: North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America. The presence of various players and the growing adoption of AI and ML technologies by businesses are some of the key factors favoring the growth of the AutoML market in North America. Europe is steadily adopting AutoML solutions and services within its market. Europe is expected to be second in terms of market size and share during the forecast period. The growing demand for AutoML solutions that can automate the machine learning process and make it more accessible to businesses boosts the growth of the market in Europe. Asia Pacific is expected to record the fastest growth rate during the forecast period. The AutoML market is expected to witness considerable developments and adoption of solutions across Asia Pacific during the forecast period. The growing investment in IT infrastructure along with the rapid adoption of emerging technologies across several business verticals are expected to drive the AutoML market.
Frequently Asked Questions (FAQ)
What is Automated Machine Learning?
Automated Machine Learning (AutoML) is a process that automates many tasks involved in building machine learning models. It applies algorithms to handle tasks such as feature engineering, hyperparameter tuning, and model selection, making it more user-friendly and efficient. AutoML is a valuable tool for businesses and individuals looking to leverage the benefits of machine learning without requiring extensive knowledge or expertise.
Which are the key drivers supporting the market growth for Automated Machine Learning?
The key drivers supporting the market growth for Automated Machine Learning include Growing demand for improved customer satisfaction and personalized product recommendations through AutoML, increasing need for accurate fraud detection, Growing data volume and complexity, Rising need to transform businesses with Intelligent automation using AutoML.
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