From $346.2 million in 2020, the automated machine learning market is predicted to reach $14,830.8 million by 2030, demonstrating a CAGR of 45.6% from 2020 to 2030. The major factors driving the market are the burgeoning requirement for efficient fraud detection solutions, soaring demand for personalized product recommendations, and increasing need for predictive lead scoring.
The COVID-19 pandemic has contributed significantly to the evolution of digital business models, with many healthcare companies adopting machine-learning-enabled chatbots to enable the contactless screening of COVID-19 symptoms. Moreover, Clevy.io, which is a France-based start-up, and Amazon Web Services (AWS) have launched a chatbot for making the process of finding official government communications about the COVID-19 infection easy. Thus, the pandemic has positively impacted the market.
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Key Findings of Automated Machine Learning Market Report
- The service category, under the offering segment, is predicted to demonstrate the faster growth in the coming years. This is credited to the burgeoning requirement for implementation and integration, consulting, and maintenance services, as they assist in enhancing business productivity and augmenting coding activities. Additionally, these services aid in automating workflows, which, in turn, enables the mechanization of complex operations.
- The cloud category dominated the AutoML market, within the deployment type segment, in the past. Moreover, this category is predicted to grow rapidly in the forthcoming years on account of the flexibility and scalability provided by cloud-based automated machine learning (AutoML) solutions.
- Geographically, North America held the largest share in the past, and this trend is expected to continue in the coming years. This is credited to the soaring venture capital funding by artificial intelligence (AI) companies for research and development (R&D), in order to advance AutoML.
- Asia-Pacific (APAC) is predicted to be the fastest-growing region in the market in the forthcoming years. This is ascribed to the growing information technology (IT) investments and increasing fintech adoption in the region. In addition, the growing government focus on incorporating AI in multiple verticals is supporting the advance of the market in the region.
- Cloud-based automated machine learning platforms are becoming a major trend in the industry on account of their ability to provide greater scalability and flexibility and reduce the IT infrastructure costs.
- Players operating in the automated machine learning market are actively focusing on partnerships to gain an edge over their rivals.
Browse detailed report on AutoML Market Trends, Business Strategies, Regional Outlook, Challenges and Analysis Through 2030
For instance, in October 2021, Hivecell, which is an edge as a service company, entered into a partnership with DataRobot Inc. for solving bigger challenges and hurdles at the edge, by processing various ML models on site and outside the data closet. By incorporating the two solutions, businesses can make data-driven decisions more efficiently.
The major players in the AutoML market are DataRobot Inc., dotData Inc., H2O.ai Inc., Amazon Web Services Inc., Big Squid Inc., Microsoft Corporation, Determined.ai Inc., SAS Institute Inc., Squark, and EdgeVerve Systems Limited.
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Deep Learning Market – The rising need for drug discovery will also drive the deep learning market at a CAGR of 35.2% during the forecast period (2020–2030). The market was valued at $3.7 billion in 2019 and it is projected to generate $102.4 billion revenue by 2030.
Natural Language Processing Market – The APAC natural language processing market is expected to exhibit the fastest growth throughout the forecast period, owing to the mounting number of small and medium-sized enterprises (SMEs) and customer contact centers, rapid technological developments in India, Japan, and China, and surging use of cloud-enabled services and applications in the region.
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