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According to the latest market research study published by P&S Intelligence, the global automated machine learning market is experiencing significant growth and is expected to continue its rapid expansion, reaching an estimated value of USD 15.5 billion by 2030. This growth is substantial, considering the market was valued at USD 866.3 million in 2023, translating to a compound annual growth rate (CAGR) of 52.8% from 2024 to 2030. Key factors driving this growth include the increased demand for solutions like fraud detection, predictive lead scoring, and personalized recommendations across various industries.

AutoML’s rise is further fueled by the growing need for automation in machine learning processes. It enables organizations to optimize their data processing capabilities while significantly reducing the time and resources required to create machine learning models. This is especially valuable as businesses face a shortage of skilled data scientists and machine learning professionals, which creates a growing reliance on automated tools to fill this gap.

Cloud-based AutoML platforms have become a critical component of the market’s growth due to their scalability, cost-effectiveness, and accessibility for businesses of all sizes. These platforms allow companies to leverage advanced machine learning technologies without the need for extensive infrastructure or specialized expertise. As new technological innovations and advancements continue to emerge, the AutoML landscape is expected to evolve rapidly, driving competition and the continuous introduction of new solutions to meet market demands.

Key Insights

Rapid Market Expansion

The AutoML market is poised to grow exponentially, from USD 866.3 million in 2023 to USD 15.5 billion by 2030, reflecting a strong CAGR of 52.8%. This growth is primarily attributed to the increasing need for automated solutions in industries like finance, healthcare, retail, and e-commerce.

Dominant and Emerging Regions

North America is currently the largest market for AutoML, driven by the widespread adoption of AI technologies and the presence of key players such as Google, Microsoft, and IBM. However, the Asia Pacific region is expected to witness the fastest growth during the forecast period, supported by the rise in cloud adoption and the increasing number of technology startups in countries like China and India.

Cloud-Based AutoML Solutions

The shift toward cloud-based platforms has accelerated the growth of the AutoML market. Cloud solutions offer businesses flexibility and scalability, making them more appealing to organizations of all sizes. This trend is expected to continue, with many companies increasingly adopting cloud-based AutoML solutions to streamline their operations and reduce costs.

Sector-Specific Growth

The banking, financial services, and insurance (BFSI) sector remains the largest adopter of AutoML solutions, leveraging these technologies for enhanced fraud detection, risk management, and financial forecasting. In addition to BFSI, the healthcare industry is adopting AutoML to improve patient outcomes through predictive analytics, personalized treatment plans, and drug discovery. Retailers, too, are utilizing AutoML for targeted marketing, personalized recommendations, and demand forecasting.

Fraud Detection as a Key Driver

Fraud detection is a major factor driving the adoption of AutoML, particularly in the finance sector. With increasing cases of fraud globally, businesses are turning to AutoML solutions to help identify and mitigate fraudulent activities more efficiently. These solutions allow companies to process vast amounts of data in real-time and flag suspicious transactions instantly, preventing financial losses and boosting consumer trust.

Smarter Customer Recommendations

Personalization has become a critical component of modern business strategies. E-commerce companies, for instance, are leveraging AutoML to deliver personalized product recommendations based on consumer behavior, significantly improving customer satisfaction and conversion rates. AutoML can analyze vast datasets and customer interactions, providing deeper insights into preferences and helping businesses tailor their offerings more effectively.

Talent Shortage and Skill Gaps

The shortage of skilled machine learning professionals is a significant challenge for organizations looking to implement AI and machine learning technologies. As a result, companies are increasingly investing in AutoML solutions to bridge this skill gap and reduce the reliance on specialized talent. This trend presents an opportunity for AutoML providers to offer user-friendly tools that cater to a wider audience, including business analysts and operations teams, without the need for deep technical expertise.

Technological Advancements and Competition

The competition within the AutoML market is intensifying as major players like Microsoft, Google, Amazon, and IBM continue to enhance their platforms. For example, Amazon's SageMaker platform is increasingly popular due to its comprehensive suite of tools that simplify machine learning model creation and deployment. The rapid pace of technological advancements is encouraging continuous innovation, pushing smaller companies and startups to innovate and find niche applications for AutoML technologies.

Emerging Opportunities for New Entrants

The AutoML market is fragmented, with numerous small to medium-sized players emerging with specialized solutions. These players are targeting specific verticals, such as healthcare, logistics, or manufacturing, where machine learning can be applied to optimize specific processes. As the market continues to evolve, new entrants will have opportunities to innovate, offering tailored solutions to meet the specific needs of businesses in these sectors.

Key Market Players

Major companies operating in the AutoML market include Microsoft Corporation, Amazon Web Services, Google LLC, IBM Corporation, and H2O.ai. These companies are actively working on improving their AutoML platforms to make them more accessible, efficient, and feature-rich. The competitive landscape is continuously evolving as new startups and established tech giants introduce cutting-edge solutions to cater to the growing demand for machine learning automation.

As the demand for AutoML solutions continues to rise, businesses will increasingly seek out ways to integrate machine learning into their operations more efficiently. The growth of the market reflects the growing importance of automation and artificial intelligence in shaping business strategies and enhancing decision-making processes across multiple industries.