Global Automated Machine Learning Market is valued at approximately USD 0.87 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 43.90% during the forecast period 2024-2032. Automated Machine Learning refers to the process of automating the end-to-end process of applying machine learning to real-world problems. The purpose of automated machine learning is to make machine learning more accessible to non-experts and streamline the workflow for experienced practitioners. It involves automating various steps in the machine learning pipeline, including data preprocessing, feature engineering, model selection, hyperparameter tuning, and model deployment. The Automated Machine Learning Market is expanding because of factors such as the growing volume of data and rising demand for machine-learning-powered chatbots. As a result, the demand for Automated Machine Learning has progressively increased in the international market during the forecast period 2024-2032.

Large datasets frequently include more complicated connections and patterns, and automated machine learning is getting access to large amounts of data, and can handle and record complex data structures, resulting in more sophisticated and accurate models. According to Statista, in 2020, the global volume of data accounts for 64.2 zettabytes and is projected to reach up to 181 zettabytes by the year 2025. Another important factor that drives the Automated Machine Learning Market is the increasing demand for the machine-learning-powered chatbot. Machine-learning-powered chatbots often require the deployment of models that can understand and generate human-like responses. Automated Machine Learning tools facilitate rapid model development and deployment, allowing organizations to quickly implement chatbot solutions without the need for extensive manual model tuning. In addition, as per Statista, the global chatbot market is projected to reach up to USD 1.25 billion by the year 2025. Moreover, the rising trend of cloud-based machine learning models and government initiatives towards the adoption of fraud detection technology is anticipated to create a lucrative growth opportunity for the market over the forecast period. However, the lack of standardization and rising threat to data privacy is going to impede overall market growth throughout the forecast period of 2024-2032.

The key regions considered for the Global Automated Machine Learning Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the increasing demand for artificial intelligence solutions in the region. The growing demand for quick turnaround times in deploying AI applications is addressed by AutoML. Automated processes speed up model development, allowing organizations to bring AI solutions to the market faster. This agility is crucial in industries where timely implementation of AI can provide a competitive advantage. The region's dominant performance is anticipated to propel the overall demand for Automated Machine Learning. Furthermore, Asia Pacific is expected to grow fastest over the forecast period, owing to factors such as supportive government initiatives towards the expansion of artificial intelligence in the region.

Major market player included in this report are:
DataRobot, Inc
Amazon Web Services, Inc
DotData, Inc
Internatinal Business Machine Corporation
Dataiku Inc
SAS Institute Inc
Microsoft Corporation
Google LLC
H2O.ai Inc
Aible Inc
Recent Developments in the Market:
In September 2023, Fujitsu Limited and the Linux Foundation launched automated machine learning and artificial intelligence technologies. The two projects are going to provide customers with software that automatically develops code for new machine learning models, as well as technology that eliminates latent biases in training data. The Linux Foundation approved the incubation of two new projects, "SapientML" and "Intersectional Fairness," to encourage developers around the world to continue experimenting and innovating with AI and machine learning technologies, with plans to host future activities such as hackathons to engage and build a community to promote open-source AI. These projects are going to further democratise AI, resulting in a world in which developers around the world can easily and securely use cutting-edge technologies on open platforms to create new applications and find innovative solutions to business and societal challenges.
Global Automated Machine Learning Market Report Scope:
Historical Data - 2020 - 2021
Base Year for Estimation - 2022
Forecast period - 2024-2032
Report Coverage - Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered - Solution, Automation Type, End Users, Region
Regional Scope - North America; Europe; Asia Pacific; Latin America; Middle East & Africa
Customization Scope - Free report customization (equivalent up to 8 analyst's working hours) with purchase. Addition or alteration to country, regional & segment scope*
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Solution
Standalone or On-Premise
Cloud
By Automation Type
Data Processing
Feature Engineering
Modeling
Visualization
By End Users
BFSI
Retail and E-Commerce
Healthcare
Manufacturing
Other End Users
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa