The automated machine learning market is growing rapidly and is expected to reach $15,499.3 million by 2030. This growth is driven by the rising need for effective fraud detection, personalized product recommendations, and predictive lead scoring solutions.

Cloud computing is a key enabler of this growth, offering improved cost efficiency, agility, scalability, and optimized resource use. Unlike standalone technologies, cloud computing is a blend of components that together drive innovation and competitiveness.

The cloud provides access to native technologies, enabling the development of machine learning (ML) and artificial intelligence (AI) solutions. The increasing demand for cloud-based platforms is one of the primary drivers of market expansion.

Cloud-based AutoML solutions, particularly those deployed through Software as a Service (SaaS) models, allow users to remotely access machine learning capabilities via the internet. These solutions offer flexibility, scalability, and cost-efficiency by reducing IT infrastructure expenses.

Fraud detection remains one of the most challenging tasks across industries, leading to a growing demand for AutoML solutions. In fact, U.S. federal agencies were estimated to have improperly paid $247 billion in fiscal 2022, adding to a cumulative $2.4 trillion in improper payments since 2003, further driving the need for advanced fraud detection systems.

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Regional Insights:

  • In 2023, large enterprises led revenue generation, leveraging AutoML for cost reduction and strategic benefits.
  • Small and medium-sized enterprises (SMEs) are expected to grow at a 51.6% CAGR, with AutoML improving customer prospecting.
  • The sales and marketing management sector is projected to experience significant growth due to AutoML’s applications in customer insights and emotional analysis.
  • AutoML is widely used in content personalization, lead generation, and customer segmentation.
  • The banking, financial services, and insurance (BFSI) sector leads AutoML adoption for fraud detection, credit risk analysis, and personalized services, driving significant revenue.
  • The healthcare industry shows promise with AutoML, enhancing disease diagnosis, research, and patient care.
  • Multinational corporations use AutoML to reduce costs, analyze competitors, and guide sales and marketing strategies, while SMEs focus on customer identification and targeting.
  • In 2023, North America dominated the AutoML market due to strong IT infrastructure and the presence of major industries like BFSI, IT & telecom, and healthcare.
  • AI venture capital (VC) investments have fueled the industry’s growth, with U.S. AI-related VC investments reaching $99.5 billion in 2018.
  • California leads with $510 billion in AI investments, followed by Massachusetts with $247 billion and New York with $110 billion.
  • IT spending, technological advancements, and government initiatives contribute to North America's strong AI ecosystem and industry leadership.
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Pramod has around 7 years of experience in market research and consulting services for healthcare industry. He holds varied experience in market sizing and forecasting with varied models, competition landscape, consumer behavior analysis, opportunity analysis, product/company benchmarking, data mining and others.
He has successfully delivered multiple projects on go-to-market strategies, pricing strategy, price point analysis, Business Expansion, market entry and exit, share analysis and others. Prior to joining P&S Intelligence, he worked with different research companies, including Transparency Market Research and MarketsandMarkets Pvt Ltd.
Some of the projects delivered by him include Scar Treatment Market, Skin Replacement and Substitutes Market, and Energy-Based Aesthetic Devices Market.

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