Automated Machine Learning (AutoML) Market Report: Size and Share Analysis, Trends, Forecasts (2024-2030)

The global automated machine learning market generated a revenue of $866.3 million in 2023, and it is expected to grow at a CAGR of 52.8% during 2024–2030. The key factors responsible for the growth of the industry include the increasing demand for efficient fraud detection solutions, surging need for personalized product recommendations, and rising importance of predictive lead scoring.

• The global AutoML market is increasingly getting competitive as several new players are entering the market. As such, the strategies adopted by existing players to capture a greater number of customers, coupled with the emergence of new players, are increasing the competition in the market.
• Conclusively, the market under study encompasses a high degree of competition and is expected to remain highly competitive over the coming years.
• For instance, in December 2022, Amazon.com Inc. launched eight new capabilities for Amazon SageMaker, an end-to-end ML service.
• Developers, data scientists, and business analysts use Amazon SageMaker to build, train, and deploy ML models quickly and easily, using its fully managed infrastructure, tools, and workflows.
• During the COVID-19 pandemic, financial services evolved and transformed digital business models, with new circumstances. The adoption of new business models has positively affected the market for AutoML.
• In addition, many healthcare and government institutions have included machine learning-enabled chatbots for contactless screening of COVID-19 symptoms. For instance, Clevy.io, a French start-up and Amazon Web Services (AWS) customer, has launched a chatbot to make it easier for people to find official government communications about the pandemic.

AutoML Market Trend & Drivers

Increasing Preference for Cloud-Based AutoML Platform Is a Key Market Trend

Cloud computing has been credited with increasing competitiveness through cost savings, greater flexibility, elasticity, and optimal resource utilization. As a technology, is much more than the sum of its parts.

• It opens doors to cloud-native technologies, supports more-efficient ways of working, and enables emerging capabilities in machine learning (ML) and artificial intelligence (AI).
• Increasing preference toward cloud-based platforms is observed as a major trend in the market.
• Cloud-based solutions involve a software-as-a-service (SaaS) model, in which users can access AutoML solutions virtually, through a secured platform over the internet. Cloud deployment of the solution offers greater flexibility, scalability, and affordability, and reduces IT infrastructure costs.
• As a result, large enterprises, as well as SMEs, are increasingly adopting cloud-based AutoML solutions. For instance, in 2022, the worldwide public cloud services market surpassed $500 Billion, growing 22.9% year-on-year.

Growing Need for Fraud Detection Solutions, and Personalized Content Recommendations Are Key Market Drivers

• The detection and prevention of frauds are a huge challenge for all organizations across all verticals. Thus, the growing need for fraud detection solutions is leading to significant growth of the market for AutoML.
• For instance, Federal agencies projected that $247 billion in improper payments was done in fiscal year 2022, and cumulative federal improper payment estimates have totaled about $2.4 trillion since fiscal year 2003.
• Furthermore, in India, according to the Reserve Bank of India (RBI), in 2022-23 year-on-year, the number of frauds in the banking sector went up to 13,530. Of this, around 50% cases were in the digital payment (card/internet) category. Moreover, in the last two years, the highest number of fraud cases were in loan portfolios of banks.
• Moreover, with the increasing popularity of online shopping, the demand for personalized content is increasing as customers prefer products that they can identify or meet their specific needs. Personalized product recommendations help companies to increase the average order value.
• Thus, to meet the evolving need and preference of customers for updated products, companies are investing heavily in new technologies to offer best-product recommendations. AutoML solutions find patterns in customer behavior from clickstream data, prior purchases, demographics, browsing history, and previous product searches, and create 1:1 best-personalized-product recommendations that match their needs and preference. Therefore, the demand for AutoML solutions is increasing for personalized product recommendations in several verticals.

Shortage of technologically skilled personnel

The increase in the demand & supply gap with regard to skilled professionals may act as a challenge for this market. The ML technology is an advanced application of information technology, which requires technologically skilled employees for operating, upgrading, and accessing data. Thus, the market is likely to witness hurdles in growth due to the shortage of skilled professionals.

• According to the Bureau of Labor Statistics, by 2026, in the U.S., the scarcity of developers will surpass 1.2 million. Additionally, till that time, 0.5 million of the current software engineering workforces will have left the market.
• However, to address the skill gap, governments are taking multiple initiatives at global level. For instance, SkillsFuture, Singapore; Tamkeen, Bahrain; SDS Fund, Scotland; HRDF, Malaysia; Springboard, Ireland; and Tech Partnership, U.K., are among the initiatives aimed at bridging the gap in skilled resources in IT industry. These initiatives are likely to reduce the skill gap and support the market growth in the coming years.

In-Depth Segmentation Analysis

Enterprise Size Insights

Large enterprise category generated a higher revenue in 2023. With the dispersed operations across the globe, large enterprises are increasingly adopting AutoML solutions for cost reduction, competitor analysis, customer retention, and effective marketing & sales strategies. Whereas, the SME category is expected to witness faster growth, progressing at a CAGR of 51.6%, during the forecast period. This can be attributed to the increasing adoption of AutoML technology by SMEs for effective customer prospecting.

Enterprise Size covered in the report include:

• Large Enterprise (Larger Category)
• SME (Faster-Growing Category)

Application Overview

The sales & marketing management category is projected to register the fastest growth during the forecast period, based on application. This can be mainly due to a large number of companies across all verticals using these platforms to gain insights of customer emotion, and further facilitate content personalization, lead scoring, customer segmentation, and customer engagement.

The following applications are included in the report:

• Fraud Detection
• Sales & Marketing Management (Largest and Fastest-Growing Category)
• Medical Testing
• Transport Optimization
• Others

Industry Analysis

The BFSI category accounted for the largest revenue in 2023. Financial institutes use AutoML platforms for efficient fraud detection, anti-money laundering, credit risk scoring, and customer churn prediction. In addition, AutoML technology helps organizations offer customer-specific personalized products and services, which, in turn, increase sales and retain existing customer base.

The healthcare category is expected to witness the fastest growth in the market, progressing at a CAGR of around 51.7%, during the forecast period. This can be majorly ascribed to the surging demand for machine learning by healthcare organizations to improve early detection of diseases, research, training, and help in treating patients quicky and effectively, while saving time, money, and resources.

Industry covered in the report are:

• BFSI (Largest Category)
• IT & Telecom
• Healthcare (Fastest-Growing Category)
• Government
• Retail
• Manufacturing
• Others

Deployment Type Overview

The cloud category accounted for a higher share in the market in 2023, based on deployment type. This is because of the enhanced scalability and flexibility of cloud-based AutoML platforms, where clients can customize solutions and services as per their requirements. In addition, as cloud-based deployment reduces operational and infrastructure costs, a large number of companies are increasingly adopting cloud-based solutions.

It is further classified as:

• Cloud (Larger and Faster-Growing Category)
• On-Premises

North America Leads the Global Market

North America generated the largest revenue in the market in 2023. Technological advancement, developed information technology (IT) infrastructure, presence of key AutoML platform providers, and well-developed banking, financial services, & insurance (BFSI), IT & telecom, and healthcare industries are the major factors driving the growth of the market in the region.

• Increasing venture capital (VC) funding on AI technologies is a prime factor supporting the growth of the market in the region. Since 2013, VC investments in AI startups have regularly increased over the years.
• For instance, in 2018, U.S. companies raised $99.5 billion through VC funding for AI, which was the highest since 2000 ($119.6 billion). Among these, AI companies raised $9.3 billion funding in 2018, which increased by 72% as compared to 2017. In the U.S., California led the AI-related investment with nearly 53 deals (about $1,719 million AI investment), followed by Massachusetts ($247 million), and New York ($110 million). With the increasing VC funding, AI companies are spending more money on research and development (R&D) to enhance their offerings.
• Furthermore, surging IT spending and technological development are some other factors supporting the growth of the market in the region. The region has the strongest AI ecosystem in terms of government initiatives, funding, number of companies (almost 45% of all AI companies are based in North America), and global reach.
• Moreover, widespread AI implementation across a number of sectors including government organizations is also fueling the growth of the market in the region. For instance, as per International Development Research Center (IDRC), in global government AI readiness index, North American countries, U.S. (4th rank) and Canada (6th rank), are better placed in terms of AI adoption by government bodies across the world.
• On the other hand, the APAC market is expected to witness the fastest growth in the AutoML market during the forecast period. This can be ascribed to the rising economic growth, increasing investment in IT infrastructure, growing adoption of emerging technologies, and surging government initiatives toward the development of artificial intelligence (AI) technology. Furthermore, APAC countries are the preferred destination for IT outsourcing. Owing to this, IT companies receive large-scale requests for application development, which further boosts the market growth.
• Europe market is also growing significantly. This can be attributed to the high adoption of AI technologies and the rising number of initiatives by industries and governments of European countries.
• In terms of AI transaction activity, there has been a consistent growth trend over the past 10 years across the region. For instance, between 2008 and 2017, Europe witnessed an investment of almost $10.5 billion, almost 75% by private equity (PEs) and VCs. Among all European countries, the U.K., France, and Germany have attracted almost 85% of the total investment.
• Germany had around 23% share in AutoML market, in 2023. In 2019, the country held the fourth position in the global AI readiness index. In addition, in 2018, the German government adopted ambitious national AI strategies in order to further strengthen AI capabilities of the country. Under this strategy, the government aimed to spend more than $3.33 billion (€3 billion) on AI by 2025.

Further, regions and countries analyzed for this report include:

• North America (Largest Regional Market)
  • U.S. (Larger and Faster-Growing Country Market)
  • Canada
• Europe
  • Germany
  • U.K. (Largest and Fastest-Growing Country Market)
  • France
  • Italy
  • Spain
  • Rest of Europe
• Asia-Pacific (APAC) (Fastest-Growing Regional Market)
  • China (Largest and Fastest-Growing Country Market)
  • Japan
  • India
  • South Korea
  • Australia
  • Rest of APAC
• Latin America (LATAM)
  • Brazil (Largest and Fastest-Growing Country Market)
  • Mexico
  • Rest of LATAM
• Middle East and Africa (MEA)
  • Saudi Arabia (Largest and Fastest-Growing Country Market)
  • South Africa
  • U.A.E.
  • Rest of MEA

Competitive Landscape

The automated machine learning market is rapidly evolving with players offering solutions to simplify and accelerate the ML model development process. The market has strong competition, and major players are launching new products and expanding their existing portfolios to gain a competitive edge. They are also involved in mergers, acquisitions, and partnerships to stay ahead of their rivals. Moreover, the majority of players are involved in technological advancements to gain a significant position in the market.