Automated Machine Learning Market Soars to $15.5 Billion by 2030
The automated machine learning (AutoML) market is experiencing significant growth and is expected to reach USD 15,499.3 million by 2030. This expansion is fueled by the increasing demand for advanced fraud detection solutions, the growing need for personalized product recommendations, and the rising significance of predictive lead scoring.
Cloud computing is widely embraced for its ability to enhance competitiveness through cost efficiency, agility, scalability, and optimized resource usage. Unlike other technologies that can be encapsulated easily, cloud computing consists of multiple components that, when integrated, deliver substantial benefits. It provides access to cloud-native technology, improves operational efficiency, and fosters the development of machine learning (ML) and artificial intelligence (AI). As demand for cloud-based platforms grows, it has become a key driver of market expansion.
Cloud-based solutions, such as Software-as-a-Service (SaaS), allow users to remotely access automated machine learning tools via internet services. This model offers flexibility, scalability, cost-effectiveness, and reduces IT infrastructure expenses.
Fraud detection remains a critical challenge for companies across industries. This need has led to an increased focus on AutoML solutions, as fraud detection systems become more prevalent. For instance, U.S. Federal Agencies were found to have made improper payments totaling USD 247 billion in 2022, with improper payments since 2003 reaching approximately USD 2.4 trillion, further driving the need for AutoML solutions.
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Regional Insights
In 2023, large enterprises dominated the AutoML market, driven by the adoption of these technologies to reduce costs and improve strategic decision-making.
Small and medium enterprises (SMEs) are expected to grow at a compound annual growth rate (CAGR) of 51.6%, leveraging AutoML to enhance customer prospecting.
The sales and marketing management sector is set for rapid growth, utilizing AutoML for customer insights, emotional analysis, and personalized engagement.
AutoML applications span content personalization, lead generation, customer segmentation, and advanced customer engagement.
The banking, financial services, and insurance (BFSI) sector leads AutoML adoption, particularly for fraud detection, credit risk analysis, and tailored services, contributing to substantial market revenue.
The healthcare industry is also poised for a breakthrough with AutoML, which is expected to improve disease diagnosis, research, and patient care.
In 2023, North America dominated the AutoML market, driven by its robust IT infrastructure and the presence of key industries such as BFSI, IT & telecom, and healthcare.
Venture capital investments in AI technologies have significantly contributed to market growth. The U.S. recorded AI-related VC funding of USD 99.5 billion in 2018, with California, Massachusetts, and New York leading the charge in AI investments.
IT spending, technological advancements, and government initiatives have strengthened the AI ecosystem in North America, positioning the region as a major hub for AI and AutoML development.
