The Global Automated Machine Learning Market size is expected to reach $9.1 billion by 2029, rising at a market growth of 42.9% CAGR during the forecast period.
Model selection is one of the major applications of automated machine learning. AutoML tools can expedite the prototyping and iteration phase of machine learning projects. By quickly exploring different models and configurations, data scientists can iterate and refine their models more efficiently. This agility enables faster experimentation and iteration cycles, ultimately accelerating the development of high-quality machine learning solutions. Thereby, Model Selection acquired $111 million revenue in 2022.
The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. or instance, In August, 2022, Alibaba Cloud entered into a collaboration agreement with the Hong Kong University of Science and Technology (HKUST) for supporting the research work of the HKUST researchers, etc. The partnership reflects Alibaba Cloud's commitment to nurturing technology talent and supporting local innovation ecosystems. Additionally, In March, 2023, AWS came into collaboration with NVIDIA for training sophisticated large language models (LLMs) and developing generative AI applications.
Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation, and Google LLC (Alphabet Inc.) are the forerunners in the Market. In May, 2023, Google Cloud extended its partnership with SAP for jointly building the future of open data and AI, and bringing in a full-fledged open data offering developed to make data landscapes easier. This offering allows users to build data could. Companies such as Amazon Web Services, Inc. (Amazon.com, Inc.), Oracle Corporation, and Hewlett-Packard Enterprise Company are some of the key innovators in Market.
There is a rising need for intelligent business processes as organizations depend increasingly on data to inform decisions and boost operational effectiveness. These procedures use machine learning algorithms to automate decision-making and streamline corporate operations, which boosts productivity and profits. By utilizing AutoML, companies can increase performance, lower costs, and streamline operations, giving them a competitive advantage. In addition, AI-powered automation has been demonstrated to significantly increase productivity. By automating the creation and deployment of machine learning models, the market can assist firms in achieving these types of outcomes.
The AutoML market has enormous potential due to the improved use of machine learning. Machine learning has always required substantial statistics, programming, and data analysis knowledge and has been extremely specialized. Organizations no longer require a staff of data scientists and machine learning specialists to construct and implement AI solutions due to the introduction of AutoML technologies. AutoML technologies, on the other hand, allow businesses to make more accessible use of machine learning, thereby rendering it more available to a wider range of customers and use cases. Furthermore, the democratization of machine learning can help companies expand their offers and tap into new markets, boosting sales and market share.
A primary restriction impeding the expansion of the AutoML sector is the delayed uptake of these tools. Many businesses are hesitant to implement AutoML despite its many advantages, such as improved productivity, accuracy, and scalability. One of the main causes of this sluggish acceptance is that people are unaware of the automated machine learning (AutoML) market or its capabilities. The adoption of AutoML may be hampered by the fact that many corporate leaders and decision-makers may not be aware of its advantages and the potential effects on their industry. Therefore, it is anticipated that the lack of adoption because of the low implementation cost and the low awareness will impede market expansion.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships & Collaborations.
Based on offering, the market is segmented into solutions and services. The services segment acquired a substantial revenue share in the market in 2022. Users of autoML services can automate a number of processes involved in creating and implementing machine learning models, including feature engineering, tweaking hyperparameters, model selection, and deployment. These services are created to make it simpler for companies and individuals to utilize the potential of machine learning without needing a deep understanding of or expertise in the subject.
Under the solutions type, the market is bifurcated into platform and software. The platform segment held the highest revenue share in the market in 2022. Business users of all skill levels and organizations of all sizes may quickly and simply use the potential of AI and machine learning to solve challenges due to automated machine learning platforms. Companies from all industries can use these platforms to enhance operations, boost client retention, and pinpoint crucial variables that affect everything from loan default to medical treatment requirements.
On the basis of application, the market is divided into data processing, feature engineering, model selection, hyperparameter optimization & tuning, model ensembling and others. The data processing segment registered the highest revenue share in the market in 2022. Data normalization, cleaning, and transformation are just a few of the many components of data processing that may be automated with the help of autoML. Data mistake detection and correction can be automated using automated machine learning (AutoML). This includes figuring out where values are missing, fixing data formatting issues, and eliminating outliers that can compromise the precision of machine learning models.
By vertical, the market is classified into BFSI, retail & ecommerce, healthcare & life sciences, IT & telecom, government & defense, manufacturing, automotive, transportations, & logistics, media & entertainment and others. The BFSI segment led the market by generating the maximum revenue share in 2022. The BFSI sector has recently implemented AI and ML technologies at a faster rate to boost operational effectiveness and enhance the customer experience. The need for machine learning in BFSI applications increases as data receives more attention. With a lot of data, inexpensive computing power, and cheap storage, automated machine learning can generate accurate and quick results.
Based on the solution deployment, the market is bifurcated into cloud and on-premise. The cloud segment witnessed the largest revenue share in the market in 2022. Since internet connections have become more dependable and remote work has become more common, cloud computing has become more widely used. In comparison to on-premises systems, cloud-based AutoML solutions are more flexible and scalable since they are simple to scale up or down to match changes in workload or data volume. Additionally, pay-as-you-go pricing is frequently available with cloud-based systems, which can be more economical for businesses with varying workloads.
| Report Attribute | Details |
|---|---|
| Market size value in 2022 | USD 773.2 Million |
| Market size forecast in 2029 | USD 9.1 Billion |
| Base Year | 2022 |
| Historical Period | 2019 to 2021 |
| Forecast Period | 2023 to 2029 |
| Revenue Growth Rate | CAGR of 42.9% from 2023 to 2029 |
| Number of Pages | 361 |
| Number of Table | 593 |
| Report coverage | Market Trends, Revenue Estimation and Forecast, Segmentation Analysis, Regional and Country Breakdown, Market Share Analysis, Competitive Landscape, Companies Strategic Developments, Company Profiling |
| Segments covered | Offering, Application, Vertical, Region |
| Country scope | US, Canada, Mexico, Germany, UK, France, Russia, Spain, Italy, China, Japan, India, South Korea, Singapore, Malaysia, Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria |
| Growth Drivers |
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| Restraints |
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Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America region generated the highest revenue share in the market in 2022. The nations in the region rank among the most developed in the world. In the region, the autoML market is expanding quickly. Several major providers are providing a variety of solutions, from fully automated systems to those that help data scientists create machine learning models. The market is being pushed by the need for quicker and more effective ways to develop and deploy machine learning models, as well as a growing need for artificial intelligence solutions across various industries.
Free Valuable Insights: Global Automated Machine Learning Market size to reach USD 9.1 Billion by 2029
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Oracle Corporation, IBM Corporation, Microsoft Corporation, Google LLC (Alphabet Inc.), Amazon Web Services, Inc. (Amazon.com, Inc.), Salesforce, Inc., Hewlett-Packard enterprise Company, Teradata Corporation, Alibaba Cloud (Alibaba Group Holding Limited) and Databricks, Inc.
By Application
By Offering
By Vertical
By Geography
The Market size is projected to reach USD 9.1 billion by 2029.
Using potential for quicker decision-making and cost reduction are driving the Market in coming years, however, The adoption of ML tools is slow restraints the growth of the Market.
Oracle Corporation, IBM Corporation, Microsoft Corporation, Google LLC (Alphabet Inc.), Amazon Web Services, Inc. (Amazon.com, Inc.), Salesforce, Inc., Hewlett-Packard enterprise Company, Teradata Corporation, Alibaba Cloud (Alibaba Group Holding Limited) and Databricks, Inc.
The Solution segment acquired maximum revenue share in the Market by Offering in 2022 thereby, achieving a market value of $6.6 billion by 2029.
The North America market dominated the Market by Region in 2022 and would continue to be a dominant market till 2029; thereby, achieving a market value of $3.5 billion by 2029.
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