Automated Machine Learning (AutoML) Market Forecasts to 2028 – Global Analysis By Offering (Platform and Service), Deployment Type (Cloud and On-Premises), Automation Type, Enterprise Size, Application, End User and By Geography

Automated Machine Learning (AutoML) Market Forecasts to 2028 – Global Analysis By Offering (Platform and Service), Deployment Type (Cloud and On-Premises), Automation Type, Enterprise Size, Application, End User and By Geography

According to Stratistics MRC, the Global Automated Machine Learning (AutoML) Market is accounted for $0.82 billion in 2022 and is expected to reach $7.58 billion by 2028 growing at a CAGR of 44.8% during the forecast period. Automated machine learning (AutoML) is a process that automates the more complex or basic steps of the machine-learning lifecycle. This makes it easier for people to engage in the development of AI without having a theoretical background or any prior expertise with machine learning. It benefits both the beginners and advanced AI practitioners. Users may upload data to training algorithms and have the system automatically choose the appropriate neural network design for a particular problem. Efficiency, scalability, and the elimination of recurring mistakes are all facilitated via AutoML.

According to a survey by O’Reilly found that only 20% of respondents reported using automated machine learning tools, while 48% had never heard of the technology.

Market Dynamics:

Driver:

Growing user-friendly machine learning software

Expert-level machine learning knowledge is in high demand, yet there is a shortage. This may be seen in the fact that there are considerably more competent applicants than there are vacant positions. AutoML intends to close this gap by automating procedures that would otherwise be beyond the capabilities of anybody except a subject-matter expert. Anyone with basic technical expertise and learners may use AutoML as it is a user-friendly machine learning program with straightforward interfaces.

Restraint:

Shortage of skilled expertise

AutoML platforms demand users with solid backgrounds in programming, data science, and machine learning. Finding the necessary skills to create, implement, and manage AutoML models is a challenge for businesses. People that use AutoML platforms must always improve their skills and stay aware of the most recent developments in the industry. Due to a lack of qualified candidates, businesses are in severe rivalry with their competitors. The expansion of the market is being hampered by the skill scarcity in the fields of data management, data visualization, and cloud computing.

Opportunity:

Raising operational efficiency & cost savings

Machine learning is becoming more widely available, which resulted in huge cost reductions for enterprises. Businesses may save the expenses of investing in expensive infrastructure and employing specialist people by adopting AutoML solutions. Additionally, quicker AI solution development and implementation is boosting operational effectiveness and enhancing decision-making. Businesses may extend their offers and tap into new markets owing to the democratization of machine learning, which boosts profits and market share.

Threat:

Lack of awareness on AutoML

Many businesses are hesitant to implement AutoML despite its numerous benefits, including improved accuracy, scalability, and efficiency. The advantages of AutoML and the potential effects it might have on businesses may not be well-known to many corporate executives and decision-makers. The poor uptake of automated machine learning (AutoML) solutions is a major barrier to the market's expansion.

Covid-19 Impact

Organizations have relied more on intelligent solutions to automate their corporate processes during the COVID-19 outbreak. It is used in the methods for identifying COVID-19 instances. It has excelled in the areas of viral drug development as well as diagnostics, prognosis assessment, and epidemic forecasting. Numerous machine learning (ML) models that estimate the likelihood that a patient will survive a COVID-19 infection have been developed and compared using automated machine learning (autoML), and the top model has been determined. It evolved into a helpful tool for physicians to stratify patients in hospitals.

The data processing segment is expected to be the largest during the forecast period

The data processing segment is estimated to have a lucrative growth. The process of finding and fixing data problems may be automated with autoML. This involves finding missing numbers, fixing formatting issues with the data, and eliminating outliers. It involves methods that can be automatically applied to the data, such as normalization and standardization. By transforming the data into a more suitable format, the likelihood of mistakes and inconsistencies is decreased. It takes less time and effort to process data manually.

The cloud segment is expected to have the highest CAGR during the forecast period

The cloud segment is anticipated to witness the fastest CAGR growth during the forecast period, due to increasing internet connections. AutoML systems that are cloud-based provide more scalability and flexibility. When the workload or amount of data varies, they can simply scaled up or down as necessary. They often provide a pay-as-you-go pricing structure, which can be more economical for businesses with fluctuating workloads. It offers complete capability at a fair price with no initial outlay of funds.

Region with largest share:

North America is projected to hold the largest market share during the forecast period. It has significantly aided in the growth and development of the market for automated machine learning. US is one of the most developed countries in the region. In the US, the AutoML industry is expanding quickly, with several major businesses providing a range of products and services, from completely automated platforms to tools that help data scientists create machine learning models. In the US, usage of AutoML solutions has significantly increased, particularly in sectors like healthcare, banking, and retail.

Region with highest CAGR:

Asia Pacific is projected to have the highest CAGR over the forecast period, owing to its growing technological advancements. APAC countries are the most preferred destination for IT outsourcing. The rapid economic expansion, rising investments in IT infrastructure, growing uptake of innovative technologies, and expanding number of government efforts for the advancement of AI technologies may all be attributed to the market growth in this area.

Key players in the market

Some of the key players profiled in the Automated Machine Learning (AutoML) Market include Amazon Web Services Inc, DataRobot Inc., Qlik Technologies Inc, Microsoft Corporation, dotData Inc, Gnosis DA S.A., SAS Institute Inc, Google LLC, H2O.ai Inc, TAZI AI, RapidMiner, Squark, BigML Inc, Determined.ai Inc, Dataiku, IBM Corporation, EdgeVerve Systems Limited, Oracle and Enhencer LLC.

Key Developments:

In February 2023, IBM integrated StepZen's technology into its portfolio, with the aims to provide its clients with an end-to-end solution for building, connecting, and managing APIs and data sources, enabling them to innovate faster and generate more value from their data.

In November 2022, Amazon Web Services, Inc. has launched AWS Asia Pacific (Hyderabad) Region, its second such facility to augment services to customers in India. The jobs will be part of the AWS supply chain in India, including construction, facility maintenance, engineering, telecommunications and jobs within the country’s broader economy.

In November 2022, Microsoft announced that pre-orders for new Surface products, Surface Laptop 5 and Surface Pro 9, will commence in India via Amazon.in, Reliance Digital, Croma, Vijay Sales and select multi brand stores. The new Surface product launches bring the best of Microsoft together on a single device, enabling all users to participate, be seen, heard, and express their creativity.

In October 2022, Oracle partnered with NVIDIA, which enabled Oracle to offer its customers access to Nvidia's GPUs for use in machine learning workloads, enhancing the performance and capabilities of Oracle's machine learning tools.

In June 2022, Google LLC announced the expansion of its commitment in the United States with the creation of Google Public Sector, a new Google division that will focus on helping U.S. public sector institutions—including federal, state, and local governments, and educational institutions—accelerate their digital transformations.

Offerings Covered:
• Platform
• Service

Deployment Types Covered:
• Cloud
• On-Premises

Automation Types Covered:
• Feature Engineering
• Data Processing
• Hyperparameter Optimization & Tuning
• Model Ensembling
• Model Selection
• Visualization

Enterprise Sizes Covered:
• Small Enterprise
• Medium Enterprise
• Large Enterprise

Applications Covered:
• Fraud Detection
• Medical Testing
• Sales & Marketing Management
• Transport Optimization
• Other Applications

End Users Covered:
• BFSI
• Healthcare
• IT & Telecom
• Retail
• E-Commerce
• Manufacturing
• Government
• Other End Users

Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa

What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2020, 2021, 2022, 2025, and 2028
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements