AutoML Industry Trends and Forecast Report, 2030

According to the latest market research study published by P&S Intelligence, the AutoML industry is witnessing growth and is projected to reach 15,499.3 million by 2030.

The market is driven by the growing need for effective scam recognition solutions, the rising requirement for tailored product recommendations, and the increasing importance of predictive lead scoring.

Cloud computing is broadly accepted to create greater competitiveness through superior cost efficiency, agility, scalability, and resource use optimization. Unlike any other technology that can be summed up or viewed in its totality, cloud computing comprises many parts that when put together, serve a greater cause.

It provides access to cloud-native tech, advances the style of operation, and creates conditions for ML and AI development and addition. It is demonstrated as the main direction in the market growth that the demand for cloud-based platforms is increasing.

Cloud-based solutions consist of a SaaS model, which gives users the possibility to remotely access automatically generated machine learning solutions via an internet service. The fact that the solution is cloud-deployed ensures a better level of flexibility and scalability alongside an affordable price and reduces the IT infrastructure costs.

Finding and forestalling frauds are one of the most challenging activities in the industrial world for every company in every sector. This results in more numerous instances of fraud detection schemes that are leading to an increased market of AutoML. Similarly, Federal Agencies are estimated to have improperly paid up to 247 billion dollars in just the fiscal year of 2022, and since the fiscal year 2003, improper payments are estimated to be around USD 2.4 trillion.

Regional Outlook

• In 2023, the large enterprises category dominated in revenue generation, propelled by AutoML acceptance for cost decreases and strategic purposes.

• SMEs are estimated to advance quickly at a 51.6% CAGR, mainly because of AutoML's role in advancing customer prospecting effectiveness.

• The sales & marketing management category is projected for fast development because of wide usage for client insights and emotional analysis.

• The application comprises content personalization, lead generation, client segmentation, and advanced customer engagement.

• The BFSI category dominates AutoML acceptance for scam detection, credit hazard analysis, and modified services, propelling significant revenue.

• The future of the healthcare industry with AutoML is certainly promising; using it will improve disease diagnosis, research, and patient care.

• The sales & marketing management category is poised for quick development, using AutoML for client insights, content personalization, and engagement strategies.

• Multinational businesses tend to turn to AutoML to cut costs, analyze competitors, and guide sales and marketing decisions, while small and medium enterprises tend to implement AutoML faster with a focus on identifying customers.

• In 2023, the North American region dominated AutoML revenue because of enhanced IT infrastructure and major industry existence, such as BFSI, IT & telecom, and healthcare.

• Substantial venture capital (VC) backing in AI techs since 2013 has boosted industry development, with U.S. AI-associated VC investments touching USD 99.5 billion in 2018.

• California led the way with USD 510 billion AI investments and then Massachusetts took the second place with USD 247 billion followed by New York with USD 110 billion.

• IT spending, technical progress, and government measures are the factors which benefit AI environment and industry development in North America, therefore, they make North America strong AI environment and industry giants.