Automated Machine Learning Solution Market – Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028

Automated Machine Learning Solution Market – Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028


Global automated machine learning solution market is anticipated to thrive in the forecast period 2023-2028. The usage of predictive lead scoring systems for customer segmentation and targeting potential consumers is rising the demand for the automated machine learning (AutoML) solutions across the globe.

Many areas of the industry now depend heavily on machine learning (ML). On the other hand, developing high-performance machine learning systems requires highly specialised data scientists and subject matter specialists. By enabling domain experts to automatically create machine learning applications without extensive statistical and machine learning skills, automated machine learning (AutoML) aims to reduce the need for data scientists. The advancements in data science and artificial intelligence have improved automated machine learning's performance. Because businesses see this technology's promise, its adoption rate is expected to increase during the projected period. Customers may now employ automated machine learning solutions more easily since businesses are selling them as subscription services. Additionally, it provides pay-as-you-go flexibility.

Machine learning (ML) is being utilised more often in a variety of applications lately, but there aren't enough machine learning professionals to keep up with this increase. The goal of automated machine learning (AutoML) is to make machine learning more approachable. As a result, professionals should be able to install more machine learning systems, and using AutoML would need less skill than using ML directly. The technology's acceptance, nevertheless, is currently only moderate, which limits the global automated machine learning solution market expansion.

After the COVID-19 epidemic, organisations have been increasingly relying on intelligent solutions to automate their business operations, which is causing a rise in the use of AI. This pattern is anticipated to persist throughout the ensuing years, accelerating the adoption of AI in business operations.

Increasing Demand for Efficient Fraud Detection Solutions

Machine learning is used in a wide range of financial applications, including trading, process automation, credit scoring, and underwriting for loans and insurance. One of the major issues with financial security is financial fraud. Machine learning is currently being used for fraud detection applications to combat the rising danger of financial fraud. In order to make use of the massive data accessible from recently acquired digital channels, several firms in the financial services sector are now actively integrating AI and ML into their ecosystems. A paradigm change in customer behaviour and priorities brought about by the pandemic has also boosted its expansion, leading 54% of financial services companies with more least 5,000 workers to integrate the technology into their business practises. Businesses are increasingly in need of a fraud detection system that can provide real-time and actionable warnings as they progress towards accepting credit card payments online. These factors are driving the global automated machine learning solution market.

Demand for Intelligent Business Processes is Rising

Artificial Intelligence (AI) usage is increasing as businesses now turn to utilising next-generation technology. Businesses may employ artificial intelligence for a variety of purposes, including data collection and work process efficiency. As a result of the widespread use of AI analytics in off-the-shelf CRM platforms, sales teams can now provide insightful data on demand. Salesforce's Einstein AI technology, for instance, can forecast which customers are most likely to increase sales and to switch brands. With information like this, salespeople can concentrate their time and efforts where it counts the most. Additionally, the growing emphasis that businesses are placing on evaluating and improving customer services is fostering the expansion of AI-based processes within organisations. It gives businesses improved understanding of consumer preferences and purchasing trends, which in turn enables them to provide tailored product suggestions. The need for AI is rising as a result of the expanding deployment of robotics across a variety of industries, including manufacturing and warehousing, among others. Co-bots are aware of the people around them because to AI technologies like machine vision. They can respond appropriately, for instance by slowing down or turning around to avoid people. As a result, processes may be created to maximise the capabilities of both people and robots.

Slow Adoption of Automated Machine Learning Tools

Machine learning (ML) is being employed in a growing number of applications, but there aren't enough machine learning specialists to keep up with this expansion. The goal of automated machine learning (AutoML) is to make machine learning more approachable. As a result, specialists should be able to install more machine learning systems, and working with AutoML would need less skill than dealing with ML directly. The technology's acceptance, nevertheless, is currently moderate, which limits the automated machine learning solution market's expansion. First, there is a misconception that AutoML approaches are difficult to use and would demand a substantial initial investment to understand how to utilise them. Secondly, autoML systems occasionally have trouble working with user data but don't always identify the issue.. Concerns were also raised over the amount of processing power needed to use AutoML.

Growing Healthcare Applications

Many applications in the field of healthcare already make use of machine learning technology. This platform analyses millions of different data points from this sector vertical, forecasts results, and also offers rapid risk assessments and precise resource allocation.

The ability to diagnose and identify disorders and illnesses that might occasionally be challenging to recognise is one of this technology's most significant uses in healthcare. This can include a number of inherited conditions and tumours that are challenging to identify in the first stages. The IBM Watson Genomics is a notable illustration of this, demonstrating how genome-based tumour sequencing in conjunction with cognitive computing may facilitate cancer detection.

A major biopharmaceutical company called Berg, uses AI to provide medicinal treatments for diseases like cancer. All these factors are driving the market of global automated machine learning solution market.

Resistance among Users Regarding Automated Machine Learning Solutions

The market's delayed adoption of automated machine learning solutions is mostly due to the limited uptake of machine learning technologies. Companies struggle to obtain the domain experts they need since there is a significant demand for them in the machine learning proper ability. Additionally, because it is expensive to hire these professionals, businesses are even less likely to adopt cutting-edge technology like machine learning. The sorts of end users may also affect the resistance to using AutoML technologies. For instance, given that they manage citizen data, government organisations may show resistance to using automated machine learning solutions. As a result, concerns over privacy and the sensitivity of data may deter them from using such solutions, slowing the market's expansion. Additionally, people are reluctant to utilise such tools due to the limits of the technology, which have been noted by several industry professionals. These are issues with data and model application that AutoML encounters. For instance, inconsistent data during offline data processing and insufficiently high-quality labelled data would have negative impacts. Additionally, teams must do technical-demanding automated machine learning processing of unstructured and semi-structured data.

Market Segmentation

The automated machine learning solution market is segmented into offering, deployment, automation type, enterprise size, end-users, company, and region. Based on offering, the market is segmented into platform and service. Based on deployment, the market is segmented into on-premise and cloud. Based on automation type, the market is segmented into data processing, feature engineering, modeling, and visualization. Based on enterprise size, the market is segmented into large enterprise and SMEs. Based on end-users, the market is segmented into BFSI, retail and e-commerce, healthcare, and manufacturing. Based on region, the market is segmented into North America, Asia-Pacific, Europe, South America, and Middle East & Africa

Market Players

Some of the major market players in the global automated machine learning solution market are Datarobot Inc., Amazon Web Services Inc., dotData Inc., IBM Corporation, Dataiku, EdgeVerve Systems Limited, Big Squid Inc., SAS Institute Inc., Microsoft Corporation, and Determined.ai Inc.

Report Scope:

In this report, the global automated machine learning solution market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
  • Automated Machine Learning Solution Market, By Offering
  • Platform
  • Service
  • Automated Machine Learning Solution Market, By Deployment:
  • On-Premise
  • Cloud
  • Automated Machine Learning Solution Market, By Automation Type:
  • Data Processing
  • Feature Engineering
  • Modeling
  • Visualization
  • Automated Machine Learning Solution Market, By Enterprise Size:
  • Large Enterprises
  • SMEs
  • Automated Machine Learning Solution Market, By End-users:
  • BFSI
  • Retail and E-Commerce
  • Healthcare
  • Manufacturing
  • Automated Machine Learning Solution Market, By Region:
  • North America
  • United States
  • Canada
  • Mexico
  • Asia-Pacific
  • India
  • China
  • Japan
  • South Korea
  • Australia
  • Singapore
  • Malaysia
  • Europe
  • Germany
  • United Kingdom
  • France
  • Russia
  • Spain
  • Belgium
  • Italy
  • South America
  • Brazil
  • Argentina
  • Colombia
  • Peru
  • Chile
  • Middle East
  • Saudi Arabia
  • South Africa
  • UAE
  • Israel
  • Turkey
Competitive Landscape
Company Profiles: Detailed analysis of the major companies present in the global automated machine learning solution market.

Company Information
  • Detailed analysis and profiling of additional market players (up to five).
Please Note: Report will be updated with the latest data and delivered to you within 3-5 working days of order. Single User license will be delivered in PDF format without printing rights


1. Service Overview
2. Research Methodology
3. Impact of COVID-19 on Global Automated Machine Learning Solution Market
4. Executive Summary
5. Voice of Customers
6. Global Automated Machine Learning Solution Market Outlook
6.1. Market Size & Forecast
6.1.1. By Value
6.2. Market Share & Forecast
6.2.1. By Offering( Platform, Service)
6.2.2. By Deployment (On-Premise, Cloud)
6.2.3. By Automation Type (Data Processing, Feature Engineering, Modeling, Visualization)
6.2.4. By Enterprise Size(Large Enterprises, SMEs)
6.2.5. By End-users (BFSI, Retail and E-Commerce, Healthcare, Manufacturing)
6.2.6. By Region
6.3. By Company (2022)
6.4. Market Map
7. North America Automated Machine Learning Solution Market Outlook
7.1. Market Size & Forecast
7.1.1. By Value
7.2. Market Share & Forecast
7.2.1. By Offering
7.2.2. By Deployment
7.2.3. By Automation Type
7.2.4. By Enterprise Size
7.2.5. By End-users
7.2.6. By Country
7.3. North America: Country Analysis
7.3.1. United States Automated Machine Learning Solution Market Outlook
7.3.1.1. Market Size & Forecast
7.3.1.1.1. By Value
7.3.1.2. Market Share & Forecast
7.3.1.2.1. By Offering
7.3.1.2.2. By Deployment
7.3.1.2.3. By Automation Type
7.3.1.2.4. By Enterprise Size
7.3.1.2.5. By End-users
7.3.2. Canada Automated Machine Learning Solution Market Outlook
7.3.2.1. Market Size & Forecast
7.3.2.1.1. By Value
7.3.2.2. Market Share & Forecast
7.3.2.2.1. By Offering
7.3.2.2.2. By Deployment
7.3.2.2.3. By Automation Type
7.3.2.2.4. By Enterprise Size
7.3.2.2.5. By End-users
7.3.3. Mexico Automated Machine Learning Solution Market Outlook
7.3.3.1. Market Size & Forecast
7.3.3.1.1. By Value
7.3.3.2. Market Share & Forecast
7.3.3.2.1. By Offering
7.3.3.2.2. By Deployment
7.3.3.2.3. By Automation Type
7.3.3.2.4. By Enterprise Size
7.3.3.2.5. By End-users
8. Asia-Pacific Automated Machine Learning Solution Market Outlook
8.1. Market Size & Forecast
8.1.1. By Value
8.2. Market Share & Forecast
8.2.1. By Offering
8.2.2. By Deployment
8.2.3. By Automation Type
8.2.4. By Enterprise Size
8.2.5. By End-users
8.2.6. By Country
8.3. Asia-Pacific: Country Analysis
8.3.1. China Automated Machine Learning Solution Market Outlook
8.3.1.1. Market Size & Forecast
8.3.1.1.1. By Value
8.3.1.2. Market Share & Forecast
8.3.1.2.1. By Offering
8.3.1.2.2. By Deployment
8.3.1.2.3. By Automation Type
8.3.1.2.4. By Enterprise Size
8.3.1.2.5. By End-users
8.3.2. India Automated Machine Learning Solution Market Outlook
8.3.2.1. Market Size & Forecast
8.3.2.1.1. By Value
8.3.2.2. Market Share & Forecast
8.3.2.2.1. By Offering
8.3.2.2.2. By Deployment
8.3.2.2.3. By Automation Type
8.3.2.2.4. By Enterprise Size
8.3.2.2.5. By End-users
8.3.3. Japan Automated Machine Learning Solution Market Outlook
8.3.3.1. Market Size & Forecast
8.3.3.1.1. By Value
8.3.3.2. Market Share & Forecast
8.3.3.2.1. By Offering
8.3.3.2.2. By Deployment
8.3.3.2.3. By Automation Type
8.3.3.2.4. By Enterprise Size
8.3.3.2.5. By End-users
8.3.4. South Korea Automated Machine Learning Solution Market Outlook
8.3.4.1. Market Size & Forecast
8.3.4.1.1. By Value
8.3.4.2. Market Share & Forecast
8.3.4.2.1. By Offering
8.3.4.2.2. By Deployment
8.3.4.2.3. By Automation Type
8.3.4.2.4. By Enterprise Size
8.3.4.2.5. By End-users
8.3.5. Australia Automated Machine Learning Solution Market Outlook
8.3.5.1. Market Size & Forecast
8.3.5.1.1. By Value
8.3.5.2. Market Share & Forecast
8.3.5.2.1. By Offering
8.3.5.2.2. By Deployment
8.3.5.2.3. By Automation Type
8.3.5.2.4. By Enterprise Size
8.3.5.2.5. By End-users
8.3.6. Singapore Automated Machine Learning Solution Market Outlook
8.3.6.1. Market Size & Forecast
8.3.6.1.1. By Value
8.3.6.2. Market Share & Forecast
8.3.6.2.1. By Offering
8.3.6.2.2. By Deployment
8.3.6.2.3. By Automation Type
8.3.6.2.4. By Enterprise Size
8.3.6.2.5. By End-users
8.3.7. Malaysia Automated Machine Learning Solution Market Outlook
8.3.7.1. Market Size & Forecast
8.3.7.1.1. By Value
8.3.7.2. Market Share & Forecast
8.3.7.2.1. By Offering
8.3.7.2.2. By Deployment
8.3.7.2.3. By Automation Type
8.3.7.2.4. By Enterprise Size
8.3.7.2.5. By End-users
9. Europe Automated Machine Learning Solution Market Outlook
9.1. Market Size & Forecast
9.1.1. By Value
9.2. Market Share & Forecast
9.2.1. By Offering
9.2.2. By Deployment
9.2.3. By Automation Type
9.2.4. By Enterprise Size
9.2.5. By End-users
9.2.6. By Country
9.3. Europe: Country Analysis
9.3.1. Germany Automated Machine Learning Solution Market Outlook
9.3.1.1. Market Size & Forecast
9.3.1.1.1. By Value
9.3.1.2. Market Share & Forecast
9.3.1.2.1. By Offering
9.3.1.2.2. By Deployment
9.3.1.2.3. By Automation Type
9.3.1.2.4. By Enterprise Size
9.3.1.2.5. By End-users
9.3.2. United Kingdom Automated Machine Learning Solution Market Outlook
9.3.2.1. Market Size & Forecast
9.3.2.1.1. By Value
9.3.2.2. Market Share & Forecast
9.3.2.2.1. By Offering
9.3.2.2.2. By Deployment
9.3.2.2.3. By Automation Type
9.3.2.2.4. By Enterprise Size
9.3.2.2.5. By End-users
9.3.3. France Automated Machine Learning Solution Market Outlook
9.3.3.1. Market Size & Forecast
9.3.3.1.1. By Value
9.3.3.2. Market Share & Forecast
9.3.3.2.1. By Offering
9.3.3.2.2. By Deployment
9.3.3.2.3. By Automation Type
9.3.3.2.4. By Enterprise Size
9.3.3.2.5. By End-users
9.3.4. Russia Automated Machine Learning Solution Market Outlook
9.3.4.1. Market Size & Forecast
9.3.4.1.1. By Value
9.3.4.2. Market Share & Forecast
9.3.4.2.1. By Offering
9.3.4.2.2. By Deployment
9.3.4.2.3. By Automation Type
9.3.4.2.4. By Enterprise Size
9.3.4.2.5. By End-users
9.3.5. Spain Automated Machine Learning Solution Market Outlook
9.3.5.1. Market Size & Forecast
9.3.5.1.1. By Value
9.3.5.2. Market Share & Forecast
9.3.5.2.1. By Offering
9.3.5.2.2. By Deployment
9.3.5.2.3. By Automation Type
9.3.5.2.4. By Enterprise Size
9.3.5.2.5. By End-users
9.3.6. Belgium Automated Machine Learning Solution Market Outlook
9.3.6.1. Market Size & Forecast
9.3.6.1.1. By Value
9.3.6.2. Market Share & Forecast
9.3.6.2.1. By Offering
9.3.6.2.2. By Deployment
9.3.6.2.3. By Automation Type
9.3.6.2.4. By Enterprise Size
9.3.6.2.5. By End-users
9.3.7. Italy Automated Machine Learning Solution Market Outlook
9.3.7.1. Market Size & Forecast
9.3.7.1.1. By Value
9.3.7.2. Market Share & Forecast
9.3.7.2.1. By Offering
9.3.7.2.2. By Deployment
9.3.7.2.3. By Automation Type
9.3.7.2.4. By Enterprise Size
9.3.7.2.5. By End-users
10. South America Automated Machine Learning Solution Market Outlook
10.1. Market Size & Forecast
10.1.1. By Value
10.2. Market Share & Forecast
10.2.1. By Offering
10.2.2. By Deployment
10.2.3. By Automation Type
10.2.4. By Enterprise Size
10.2.5. By End-users
10.2.6. By Country
10.3. South America: Country Analysis
10.3.1. Brazil Automated Machine Learning Solution Market Outlook
10.3.1.1. Market Size & Forecast
10.3.1.1.1. By Value
10.3.1.2. Market Share & Forecast
10.3.1.2.1. By Offering
10.3.1.2.2. By Deployment
10.3.1.2.3. By Automation Type
10.3.1.2.4. By Enterprise Size
10.3.1.2.5. By End-users
10.3.2. Argentina Automated Machine Learning Solution Market Outlook
10.3.2.1. Market Size & Forecast
10.3.2.1.1. By Value
10.3.2.2. Market Share & Forecast
10.3.2.2.1. By Offering
10.3.2.2.2. By Deployment
10.3.2.2.3. By Automation Type
10.3.2.2.4. By Enterprise Size
10.3.2.2.5. By End-users
10.3.3. Colombia Automated Machine Learning Solution Market Outlook
10.3.3.1. Market Size & Forecast
10.3.3.1.1. By Value
10.3.3.2. Market Share & Forecast
10.3.3.2.1. By Offering
10.3.3.2.2. By Deployment
10.3.3.2.3. By Automation Type
10.3.3.2.4. By Enterprise Size
10.3.3.2.5. By End-users
10.3.4. Peru Automated Machine Learning Solution Market Outlook
10.3.4.1. Market Size & Forecast
10.3.4.1.1. By Value
10.3.4.2. Market Share & Forecast
10.3.4.2.1. By Offering
10.3.4.2.2. By Deployment
10.3.4.2.3. By Automation Type
10.3.4.2.4. By Enterprise Size
10.3.4.2.5. By End-users
10.3.5. Chile Automated Machine Learning Solution Market Outlook
10.3.5.1. Market Size & Forecast
10.3.5.1.1. By Value
10.3.5.2. Market Share & Forecast
10.3.5.2.1. By Offering
10.3.5.2.2. By Deployment
10.3.5.2.3. By Automation Type
10.3.5.2.4. By Enterprise Size
10.3.5.2.5. By End-users
11. Middle East & Africa Automated Machine Learning Solution Market Outlook
11.1. Market Size & Forecast
11.1.1. By Value
11.2. Market Share & Forecast
11.2.1. By Offering
11.2.2. By Deployment
11.2.3. By Automation Type
11.2.4. By Enterprise Size
11.2.5. By End-users
11.2.6. By Country
11.3. Middle East & Africa: Country Analysis
11.3.1. Saudi Arabia Automated Machine Learning Solution Market Outlook
11.3.1.1. Market Size & Forecast
11.3.1.1.1. By Value
11.3.1.2. Market Share & Forecast
11.3.1.2.1. By Offering
11.3.1.2.2. By Deployment
11.3.1.2.3. By Automation Type
11.3.1.2.4. By Enterprise Size
11.3.1.2.5. By End-users
11.3.2. South Africa Automated Machine Learning Solution Market Outlook
11.3.2.1. Market Size & Forecast
11.3.2.1.1. By Value
11.3.2.2. Market Share & Forecast
11.3.2.2.1. By Offering
11.3.2.2.2. By Deployment
11.3.2.2.3. By Automation Type
11.3.2.2.4. By Enterprise Size
11.3.2.2.5. By End-users
11.3.3. UAE Automated Machine Learning Solution Market Outlook
11.3.3.1. Market Size & Forecast
11.3.3.1.1. By Value
11.3.3.2. Market Share & Forecast
11.3.3.2.1. By Offering
11.3.3.2.2. By Deployment
11.3.3.2.3. By Automation Type
11.3.3.2.4. By Enterprise Size
11.3.3.2.5. By End-users
11.3.4. Israel Automated Machine Learning Solution Market Outlook
11.3.4.1. Market Size & Forecast
11.3.4.1.1. By Value
11.3.4.2. Market Share & Forecast
11.3.4.2.1. By Offering
11.3.4.2.2. By Deployment
11.3.4.2.3. By Automation Type
11.3.4.2.4. By Enterprise Size
11.3.4.2.5. By End-users
11.3.5. Turkey Automated Machine Learning Solution Market Outlook
11.3.5.1. Market Size & Forecast
11.3.5.1.1. By Value
11.3.5.2. Market Share & Forecast
11.3.5.2.1. By Offering
11.3.5.2.2. By Deployment
11.3.5.2.3. By Automation Type
11.3.5.2.4. By Enterprise Size
11.3.5.2.5. By End-users
12. Market Dynamics
12.1. Drivers
12.2. Challenges
13. Market Trends & Developments
14. Company Profiles
14.1. Datarobot Inc.
14.1.1. Business Overview
14.1.2. Key Revenue and Financials
14.1.3. Recent Developments
14.1.4. Key Personnel
14.1.5. Key Product/Services
14.2. Amazon Web Services Inc.
14.2.1. Business Overview
14.2.2. Key Revenue and Financials
14.2.3. Recent Developments
14.2.4. Key Personnel
14.2.5. Key Product/Services
14.3. dotData Inc.
14.3.1. Business Overview
14.3.2. Key Revenue and Financials
14.3.3. Recent Developments
14.3.4. Key Personnel
14.3.5. Key Product/Services
14.4. IBM Corporation
14.4.1. Business Overview
14.4.2. Key Revenue and Financials
14.4.3. Recent Developments
14.4.4. Key Personnel
14.4.5. Key Product/Services
14.5. Dataiku
14.5.1. Business Overview
14.5.2. Key Revenue and Financials
14.5.3. Recent Developments
14.5.4. Key Personnel
14.5.5. Key Product/Services
14.6. EdgeVerve Systems Limited
14.6.1. Business Overview
14.6.2. Key Revenue and Financials
14.6.3. Recent Developments
14.6.4. Key Personnel
14.6.5. Key Product/Services
14.7. Big Squid Inc.
14.7.1. Business Overview
14.7.2. Key Revenue and Financials
14.7.3. Recent Developments
14.7.4. Key Personnel
14.7.5. Key Product/Services
14.8. SAS Institute Inc.
14.8.1. Business Overview
14.8.2. Key Revenue and Financials
14.8.3. Recent Developments
14.8.4. Key Personnel
14.8.5. Key Product/Services
14.9. Microsoft Corporation
14.9.1. Business Overview
14.9.2. Key Revenue and Financials
14.9.3. Recent Developments
14.9.4. Key Personnel
14.9.5. Key Product/Services
14.10. Determined.ai Inc
14.10.1. Business Overview
14.10.2. Key Revenue and Financials
14.10.3. Recent Developments
14.10.4. Key Personnel
14.10.5. Key Product/Services
15. Strategic Recommendations
16. About Us & Disclaimer

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