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Automated Machine Learning Market To Generate Revenue Worth $14,830.8 Million in 2030

Automated Machine Learning Market To Generate Revenue Worth $14,830.8 Million in 2030

Published: November 2021

The increasing demand for efficient fraud detection solutions, the growing need for personalized product recommendations, and the rising importance of predictive lead scoring are the major growth drivers for the global automated machine learning (AutoML) market. Due to the aforementioned factors, the industry is projected to generate $14,830.8 million revenue in 2030, advancing at a CAGR of 45.6% during 2020–2030.

Increment in the digital opening of new relationships (over 70%), usage of mobile pay applications (over 80%), and usage of contactless payments (over 30%) have pushed the market for automated machine learning. The first wave of pandemic triggered a 10–20% rise in online and mobile banking across the globe. The sound application and scale of the preventive artificial intelligence (AI) were particularly important during the pandemic situation, as fraud prevention activity levels up by more than 40% compared to pre-COVID-19 levels. Thereby, the trend toward the adoption of digital banking is expected to witness positive inclination in the future.

Service Category To Witness Faster Growth

The automated machine learning market is categorized into platform and service, based on offering. Of these, the service category is expected to witness faster growth during the forecast period. This can be mainly due to the increasing demand for integration and implementation, maintenance, and consulting services, as these services help in improving business productivity and acceleration of coding activities. In addition, the services help in the automation of workflow, which further promotes the mechanization of complex tasks.

Moreover, the market for automated machine learning is categorized into cloud and on-premises, based on deployment type. Out of these, the cloud category held a larger market share in 2020. The category is also expected to witness significant growth during the forecast period, owing to the increased scalability and flexibility of cloud-based AutoML platforms. In addition, as cloud-based deployment reduces operational and infrastructure costs, a large number of companies are increasingly adopting cloud-based solutions.

Geographically, the North American region held the largest share of the automated machine learning market, in 2020, and it is expected to maintain its position in the forecast period as well. This is mainly attributed to the increasing venture capital funding of AI companies on research and development (R&D) to enhance their offerings. 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).

Whereas, the Asia-Pacific (APAC) market is expected to witness the fastest growth during the forecast period. This can be mainly due to the increasing IT infrastructure investment and rising fintech adoption rate in the region. The regional market is also driven by the escalating governmental focus, which includes high adoption and implementation of AI across all verticals.

Partnerships Are Most-Effective Strategic Measures Taken by Players in the Market

Players in the global automated machine learning industry are frequently involved in partnerships to gain a significant position in the market. For instance, in October 2021, Hivecell, an edge-as-a-service company, partnered with DataRobot Inc. to solve bigger challenges at the edge by processing machine learning models on-site, outside of the data closet. By leveraging the two solutions, organizations could more efficiently make relevant, data-driven decisions. This collaboration would empower organizations of any size, industry, or resource to drive better business outcomes with AI by deploying onto Hivecell’s simple, scalable infrastructure.

Similarly, in September 2021, dotData Inc., a provider of full-cycle enterprise AI automation solutions, announced the partnership with Tableau Software LLC, the analytics platform, to enable Tableau users to leverage the power of dotData’s AI automation capabilities. As a result of this partnership, Tableau users would be able to build customized predictive analytics solutions faster and more easily. By combining Tableau’s data preparation and visualization capabilities with dotData’s augmented insights discovery and predictive modeling capabilities, Tableau users could perform full-cycle predictive analysis from raw data through data preparation and insight discovery through AI-based predictions and actionable dashboards.

The major players operating in the automated machine learning market include DataRobot Inc., H2O.ai Inc., dotData Inc., EdgeVerve Systems Limited, Amazon Web Services Inc., Squark, Big Squid Inc., SAS Institute Inc., Microsoft Corporation, and Determined.ai Inc.