Published: November 2021 | Report Code: IM11843 | Available Format: PDF | Pages: 188
The global automated machine learning market was valued at $346.2 million in 2020, and it is expected to grow at a CAGR of 45.6% during 2020–2030. 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.
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 COVID-19.
The platform category held a larger share of the AutoML market in 2020, based on offering. This is majorly attributed to the increasing adoption of AutoML platforms across all verticals for fraud minimization, operational costs reduction, and enhanced customer service. In addition, the pandemic accelerated digital transformation in almost every sector, including manufacturing, healthcare, and banking and financial services, which led to the growing adoption of AutoML in those sectors.
The cloud category accounted for a higher share in the market in 2020, 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.
The large enterprise category dominated the market in 2020, based on enterprise size. This is mainly because of dispersed operations across the globe, increase in adoption of AutoML solutions by large enterprises for cost reduction, competitor analysis, customer retention, and effective marketing & sales strategies.
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 significantly using these platforms to gain insights into customer emotion, and further facilitate content personalization, lead scoring, customer segmentation, and customer engagement.
The healthcare category is projected to register the highest growth rate in the market for AutoML, during the forecast period, based on industry. This can be attributed to the surging demand for machine learning by healthcare organizations to improve early detection of diseases, research, training, and help in treating patients quickly and effectively, while saving time, money, and resources.
Geographically, North America generated the largest revenue in the market in 2020. 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.
On the other hand, the Asia-Pacific (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 most preferred destination for IT outsourcing. Owing to this, IT companies receive large-scale requests for application development, which further boosts the market growth.
Increasing preference toward cloud-based AutoML platforms is observed as a major trend in the AutoML 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 solutions 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, the worldwide public cloud services sector grew from nearly $230 billion in 2019 to almost $270 billion in 2020.
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, as per the U.S. Government Accountability Office, in 2018, improper payment (payment that should not have been made or that was made in an incorrect amount) totaled about $151 billion, an increase of about $10 billion as compared to the fiscal year 2017 ($141 billion). Furthermore, in India, as per the Reserve Bank of India, more than 6,800 cases of bank frauds amounting up to $10,079.0 million (INR 71,500 crores) were reported in 2018–2019.
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 average order value. For instance, as per McKinsey and Company Inc., in 2018, Amazon.Com Inc.’s product recommendation engine accounted for nearly 35% of its revenue. Furthermore, as per Forrester Research Inc., conversion to sales of on-site recommendations on Amazon reaches 60% in some cases based on the performance of other e-commerce platforms due to effective product recommendations.
|Base Year (2020) Market Size||$346.2 Million|
|Market Size Forecast in 2030||$14,830.8 Million|
|Forecast Period CAGR||45.6%|
|Report Coverage||Market Trends, Drivers, Restraints, and opportunity; Impact of COVID-19; Revenue Estimation and Forecast; Segmentation Analysis; Regional Breakdown; Country Analysis; Companies’ Strategic Developments; Company Profiling|
|Market Size by Segments||By Offering; By Deployment Type; By Enterprise Size; By Application; By Industry; By Region|
|Market Size of Geographies||North America; Europe; APAC; MEA; LATAM|
The AutoML industry is highly fragmented, due to the rapid development in digital technologies, such as AI, machine learning, and predictive analytics, and digital transformation of industries, which have increased market competition. In recent years, players in the market have been involved in mergers and acquisitions in order to attain a significant position. For instance:
The global automated machine learning market report offers comprehensive market segmentation analysis along with market estimation for the period 2015-2030.
Based on Offering
Based on Deployment Type
Based on Enterprise Size
Based on Application
Based on Industry
In 2030, the value of the automated machine learning market will be $14,830.8 million.
Platform is a larger category under the offering segment of the automated machine learning industry.
The major automated machine learning market drivers are the increasing demand for efficient fraud detection solutions, surging need for personalized product recommendations, and rising importance of predictive lead scoring.
North America is the largest and APAC is the fastest-growing automated machine learning market.
Most automated machine learning market players are adopting partnerships and collaborations strategies to sustain their business growth.
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