Machine Learning Market Size, Share, Growth and Global Industry Analysis By Type & Application, Regional Insights and Forecast to 2024-2032
Growth Factors of Machine Learning (ML) Market
The machine learning (ML) market size was valued at USD 19.20 billion in 2022, and the market is now projected to grow from USD 26.03 billion in 2023 to USD 225.91 billion by 2030, exhibiting a CAGR of 36.2% during the forecast period of 2024-2032.
The COVID-19 outbreak improved the growth of the machine learning marketplace, a fashion anticipated to persist at some point of the assessment length. This surge is driven by the increasing adoption of ML technology across numerous sectors, inclusive of car, retail, and healthcare, enhancing operational efficiency and innovation.
ML era is extensively used in healthcare, leveraging thousands and thousands of statistics points to expect outcomes, offer rapid risk rankings, and allocate sources effectively. This era complements patient care by using studying giant datasets and enhancing decision-making tactics in healthcare settings.
In recent years, retail analytics has accelerated swiftly, with e-commerce giants like Alibaba, eBay, and Amazon the use of advanced records analytics to reinforce income and enhance customer satisfaction. Additionally, research and improvement in speech and voice popularity technology have led to cognitive speech coding processes based totally on Machine Learning standards.
Comprehensive Analysis of Machine Learning (ML) Market
The machine learning (ML) market growth is rising at an exponential rate due to its market segmentation. This marketplace enlargement successfully affords an in-depth local exam thinking about the dominant deliver and demand forces that effect the enterprise. These segmentations are methodically segregated by enterprise type analysis, by deployment analysis, by end-use industry analysis. By enterprise type analysis include, small & mid-sized enterprises and large enterprises. By deployment analysis include, cloud and on-premise.
The North America region lead the machine learning (ML) market share by benefitting a market size of USD 6.12 billion in 2022 due to availability of mounted IT infrastructure and big investments are anticipated to power the marketplace growth in North America.
The pinnacle players inside the market play a critical function in the enterprise assuring market growth and placing marketplace requirements. These players include, IBM Corporation (U.S.), SAP SE (Germany), Oracle Corporation (U.S.), Hewlett Packard Enterprise Company (U.S.), Microsoft Corporation (U.S.), Amazon, Inc. (U.S.), Intel Corporation (U.S.), Databricks (U.S.), SAS Institute Inc. (U.S.), BigML, Inc. (U.S.). These market players provide a level-playing competitive landscape.
In January 2022, Acquia added advanced retail ML models for its patron facts platform to boom purchaser lifetime fee. With this launch, the organization aimed to help stores gain a holistic view of their enterprise. Acquia assists outlets in understanding levers inside their advertising and sales efforts.
Segmentation Table
ATTRIBUTE DETAILS
Study Period 2019–2030
Base Year 2022
Estimated Year 2023
Forecast Period 2023–2030
Historical Period 2019–2021
Growth Rate CAGR of 36.2% from 2023 to 2030
Unit Value (USD billion)
Segmentation By Enterprise Type, Deployment, End-use Industry, and Region
By Enterprise Type Small and Mid-sized Enterprises (SMEs)
Large Enterprises
By Deployment Cloud
On-premise
By End-use Industry Healthcare
Retail
IT and Telecommunication
Banking, Financial Services and Insurance (BFSI)
Automotive & Transportation
Advertising & Media
Manufacturing
Others (Energy & Utilities)
By Region North America (By Enterprise Type, By Deployment, By End-use Industry, By Country)
- U.S.
- Canada
Europe (By Enterprise Type, By Deployment, By End-use Industry, By Country)
- U.K.
- Germany
- France
- Scandinavia
- Rest of Europe
Asia Pacific (By Enterprise Type, By Deployment, By End-use Industry, By Country)
- China
- Japan
- India
- Southeast Asia
- Rest of Asia Pacific
Middle East & Africa (By Enterprise Type, By Deployment, By End-use Industry, By Country)
- GCC
- South Africa
- Rest of the Middle East & Africa
Latin America (By Enterprise Type, By Deployment, By End-use Industry, By Country)
- Brazil
- Mexico
- Rest of Latin America
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- 1. Introduction
- 1.1. Definition, By Segment
- 1.2. Research Methodology/Approach
- 1.3. Data Sources
- 2. Executive Summary
- 3. Market Dynamics
- 3.1. Macro and Micro Economic Indicators
- 3.2. Drivers, Restraints, Opportunities and Trends
- 3.3. Impact of COVID-19
- 4. Competition Landscape
- 4.1. Business Strategies Adopted by Key Players
- 4.2. Consolidated SWOT Analysis of Key Players
- 4.3. Global Machine Learning (ML) Key Players Market Share/Ranking, 2022
- 5. Global Machine Learning (ML) Market Size Estimates and Forecasts, By Segments, 2019-2030
- 5.1. Key Findings
- 5.2. By Enterprise Type (USD)
- 5.2.1. Small and Mid-sized Enterprises (SMEs)
- 5.2.2. Large Enterprises
- 5.3. By Deployment (USD)
- 5.3.1. Cloud
- 5.3.2. On-premise
- 5.4. By End-Use Industry (USD)
- 5.4.1. Healthcare
- 5.4.2. Retail
- 5.4.3. IT & Telecommunication
- 5.4.4. Banking, Financial Services and Insurance (BFSI)
- 5.4.5. Automotive & Transportation
- 5.4.6. Advertising & Media
- 5.4.7. Manufacturing
- 5.4.8. Others (Energy & Utilities, etc.)
- 5.5. By Region (USD)
- 5.5.1. North America
- 5.5.2. Europe
- 5.5.3. Asia Pacific
- 5.5.4. Middle East & Africa
- 5.5.5. Latin America
- 6. North America Machine Learning (ML) Market Size Estimates and Forecasts, By Segments, 2019-2030
- 6.1. Key Findings
- 6.2. By Enterprise Type (USD)
- 6.2.1. Small and Mid-sized Enterprises (SMEs)
- 6.2.2. Large Enterprises
- 6.3. By Deployment (USD)
- 6.3.1. Cloud
- 6.3.2. On-premise
- 6.4. By End-Use Industry (USD)
- 6.4.1. Healthcare
- 6.4.2. Retail
- 6.4.3. IT & Telecommunication
- 6.4.4. Banking, Financial Services and Insurance (BFSI)
- 6.4.5. Automotive & Transportation
- 6.4.6. Advertising & Media
- 6.4.7. Manufacturing
- 6.4.8. Others (Energy & Utilities, etc.)
- 6.5. By Country (USD)
- 6.5.1. United States
- 6.5.2. Canada
- 7. Europe Machine Learning (ML) Market Size Estimates and Forecasts, By Segments, 2019-2030
- 7.1. Key Findings
- 7.2. By Enterprise Type (USD)
- 7.2.1. Small and Mid-sized Enterprises (SMEs)
- 7.2.2. Large Enterprises
- 7.3. By Deployment (USD)
- 7.3.1. Cloud
- 7.3.2. On-premise
- 7.4. By End-Use Industry (USD)
- 7.4.1. Healthcare
- 7.4.2. Retail
- 7.4.3. IT & Telecommunication
- 7.4.4. Banking, Financial Services and Insurance (BFSI)
- 7.4.5. Automotive & Transportation
- 7.4.6. Advertising & Media
- 7.4.7. Manufacturing
- 7.4.8. Others (Energy & Utilities, etc.)
- 7.5. By Country (USD)
- 7.5.1. United Kingdom
- 7.5.2. Germany
- 7.5.3. France
- 7.5.4. Scandinavia
- 7.5.5. Rest of Europe
- 8. Asia Pacific Machine Learning (ML) Market Size Estimates and Forecasts, By Segments, 2019-2030
- 8.1. Key Findings
- 8.2. By Enterprise Type (USD)
- 8.2.1. Small and Mid-sized Enterprises (SMEs)
- 8.2.2. Large Enterprises
- 8.3. By Deployment (USD)
- 8.3.1. Cloud
- 8.3.2. On-premise
- 8.4. By End-Use Industry (USD)
- 8.4.1. Healthcare
- 8.4.2. Retail
- 8.4.3. IT & Telecommunication
- 8.4.4. Banking, Financial Services and Insurance (BFSI)
- 8.4.5. Automotive & Transportation
- 8.4.6. Advertising & Media
- 8.4.7. Manufacturing
- 8.4.8. Others (Energy & Utilities, etc.)
- 8.5. By Country (USD)
- 8.5.1. China
- 8.5.2. Japan
- 8.5.3. India
- 8.5.4. Southeast Asia
- 8.5.5. Rest of Asia Pacific
- 9. Middle East & Africa Machine Learning (ML) Market Size Estimates and Forecasts, By Segments, 2019-2030
- 9.1. Key Findings
- 9.2. By Enterprise Type (USD)
- 9.2.1. Small and Mid-sized Enterprises (SMEs)
- 9.2.2. Large Enterprises
- 9.3. By Deployment (USD)
- 9.3.1. Cloud
- 9.3.2. On-premise
- 9.4. By End-Use Industry (USD)
- 9.4.1. Healthcare
- 9.4.2. Retail
- 9.4.3. IT & Telecommunication
- 9.4.4. Banking, Financial Services and Insurance (BFSI)
- 9.4.5. Automotive & Transportation
- 9.4.6. Advertising & Media
- 9.4.7. Manufacturing
- 9.4.8. Others (Energy & Utilities, etc.)
- 9.5. By Country (USD)
- 9.5.1. GCC
- 9.5.2. South Africa
- 9.5.3. Rest of MEA
- 10. Latin America Machine Learning (ML) Market Size Estimates and Forecasts, By Segments, 2019-2030
- 10.1. Key Findings
- 10.2. By Enterprise Type (USD)
- 10.2.1. Small and Mid-sized Enterprises (SMEs)
- 10.2.2. Large Enterprises
- 10.3. By Deployment (USD)
- 10.3.1. Cloud
- 10.3.2. On-premise
- 10.4. By End-Use Industry (USD)
- 10.4.1. Healthcare
- 10.4.2. Retail
- 10.4.3. IT & Telecommunication
- 10.4.4. Banking, Financial Services and Insurance (BFSI)
- 10.4.5. Automotive & Transportation
- 10.4.6. Advertising & Media
- 10.4.7. Manufacturing
- 10.4.8. Others (Energy & Utilities, etc.)
- 10.5. By Country (USD)
- 10.5.1. Brazil
- 10.5.2. Mexico
- 10.5.3. Rest of Latin America
- 11. Company Profiles for Top 10 Players (Based on data availability in public domain and/or on paid databases)
- 11.1. IBM Corporation
- 11.1.1. Overview
- 11.1.1.1. Key Management
- 11.1.1.2. Headquarters
- 11.1.1.3. Offerings/Business Segments
- 11.1.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.1.2.1. Employee Size
- 11.1.2.2. Past and Current Revenue
- 11.1.2.3. Geographical Share
- 11.1.2.4. Business Segment Share
- 11.1.2.5. Recent Developments
- 11.2. SAP SE
- 11.2.1. Overview
- 11.2.1.1. Key Management
- 11.2.1.2. Headquarters
- 11.2.1.3. Offerings/Business Segments
- 11.2.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.2.2.1. Employee Size
- 11.2.2.2. Past and Current Revenue
- 11.2.2.3. Geographical Share
- 11.2.2.4. Business Segment Share
- 11.2.2.5. Recent Developments
- 11.3. Oracle Corporation
- 11.3.1. Overview
- 11.3.1.1. Key Management
- 11.3.1.2. Headquarters
- 11.3.1.3. Offerings/Business Segments
- 11.3.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.3.2.1. Employee Size
- 11.3.2.2. Past and Current Revenue
- 11.3.2.3. Geographical Share
- 11.3.2.4. Business Segment Share
- 11.3.2.5. Recent Developments
- 11.4. Hewlett Packard Enterprise Company
- 11.4.1. Overview
- 11.4.1.1. Key Management
- 11.4.1.2. Headquarters
- 11.4.1.3. Offerings/Business Segments
- 11.4.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.4.2.1. Employee Size
- 11.4.2.2. Past and Current Revenue
- 11.4.2.3. Geographical Share
- 11.4.2.4. Business Segment Share
- 11.4.2.5. Recent Developments
- 11.5. Microsoft Corporation
- 11.5.1. Overview
- 11.5.1.1. Key Management
- 11.5.1.2. Headquarters
- 11.5.1.3. Offerings/Business Segments
- 11.5.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.5.2.1. Employee Size
- 11.5.2.2. Past and Current Revenue
- 11.5.2.3. Geographical Share
- 11.5.2.4. Business Segment Share
- 11.5.2.5. Recent Developments
- 11.6. Amazon Inc.
- 11.6.1. Overview
- 11.6.1.1. Key Management
- 11.6.1.2. Headquarters
- 11.6.1.3. Offerings/Business Segments
- 11.6.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.6.2.1. Employee Size
- 11.6.2.2. Past and Current Revenue
- 11.6.2.3. Geographical Share
- 11.6.2.4. Business Segment Share
- 11.6.2.5. Recent Developments
- 11.7. Intel Corporation
- 11.7.1. Overview
- 11.7.1.1. Key Management
- 11.7.1.2. Headquarters
- 11.7.1.3. Offerings/Business Segments
- 11.7.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.7.2.1. Employee Size
- 11.7.2.2. Past and Current Revenue
- 11.7.2.3. Geographical Share
- 11.7.2.4. Business Segment Share
- 11.7.2.5. Recent Developments
- 11.8. Databricks
- 11.8.1. Overview
- 11.8.1.1. Key Management
- 11.8.1.2. Headquarters
- 11.8.1.3. Offerings/Business Segments
- 11.8.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.8.2.1. Employee Size
- 11.8.2.2. Past and Current Revenue
- 11.8.2.3. Geographical Share
- 11.8.2.4. Business Segment Share
- 11.8.2.5. Recent Developments
- 11.9. SAS Institute Inc.
- 11.9.1. Overview
- 11.9.1.1. Key Management
- 11.9.1.2. Headquarters
- 11.9.1.3. Offerings/Business Segments
- 11.9.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.9.2.1. Employee Size
- 11.9.2.2. Past and Current Revenue
- 11.9.2.3. Geographical Share
- 11.9.2.4. Business Segment Share
- 11.9.2.5. Recent Developments
- 11.10. BigML Inc.
- 11.10.1. Overview
- 11.10.1.1. Key Management
- 11.10.1.2. Headquarters
- 11.10.1.3. Offerings/Business Segments
- 11.10.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.10.2.1. Employee Size
- 11.10.2.2. Past and Current Revenue
- 11.10.2.3. Geographical Share
- 11.10.2.4. Business Segment Share
- 11.10.2.5. Recent Developments
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