Machine Learning, Market - Global Industry Size, Share, Trends, Opportunity, and Forecast. Segmented By Component, By Enterprises Size, By Deployment, By End-User, By Region & Competition, 2021-2031F

Description

The Global Machine Learning (ML) Market is projected to expand significantly, growing from USD 76.13 Billion in 2025 to USD 579.39 Billion by 2031, reflecting a CAGR of 40.25%. Defined as a specialized subset of artificial intelligence, machine learning utilizes algorithms to identify patterns and refine performance using data rather than explicit programming instructions. This market growth is fundamentally propelled by the exponential availability of big data and the democratization of powerful computing through cloud infrastructure, enabling enterprises across various sectors to automate complex workflows and derive actionable intelligence.

Market Overview
Forecast Period	2027-2031
Market Size 2025	USD 76.13 Billion
Market Size 2031	USD 579.39 Billion
CAGR 2026-2031	40.25%
Fastest Growing Segment	Cloud
Largest Market	North America

A major obstacle hindering faster market development is the shortage of skilled professionals qualified to build and maintain complex model architectures. This talent gap creates operational bottlenecks for organizations attempting to scale their initiatives and leads to increased labor costs. Despite these challenges, the technology remains a top strategic priority for executives; according to the Institute of Electrical and Electronics Engineers, 65 percent of global technology leaders in 2024 identified artificial intelligence and machine learning as the most critical technology area for the year.

Market Driver

The integration of generative AI for intelligent automation and content creation is fundamentally reshaping the Global Machine Learning (ML) Market by extending utility beyond standard predictive tasks. This driver has triggered a surge in capital allocation as enterprises aim to utilize models capable of synthesizing text, code, and media to streamline operations and boost productivity. The focus has moved from experimental pilots to scalable deployments where algorithms autonomously handle complex workflows; according to the Stanford Institute for Human-Centered Artificial Intelligence's '2025 AI Index Report' from April 2025, private investment in generative AI hit $33.9 billion in 2024, fueling the development of sophisticated neural architectures.

Concurrently, the widespread adoption of cloud-based Machine Learning as a Service (MLaaS) is democratizing access to these advanced tools by eliminating the prohibitive costs of on-premises hardware. Cloud platforms offer the scalable infrastructure necessary for organizations of all sizes to train and deploy models efficiently, allowing businesses to integrate AI capabilities directly into existing digital ecosystems without heavy upfront capital expenditure. Highlighting this demand, SiliconANGLE reported in August 2025 that Microsoft's Azure AI services generated approximately $3 billion in quarterly revenue, while an OpenAI report titled 'The state of enterprise AI' in December 2025 noted that 75 percent of workers experienced improved output speed or quality using AI.

Market Challenge

The shortage of skilled professionals acts as a primary barrier to the scalable expansion of the Global Machine Learning Market. Organizations face significant difficulties in securing the technical expertise necessary to develop and maintain complex model architectures, resulting in immediate operational bottlenecks. This deficit in talent leads to inflated labor costs and extended project timelines, often forcing enterprises to delay or downsize their automation strategies, which directly reduces the realizable value of machine learning investments and slows broader commercial adoption.

This gap between technological capability and workforce readiness places a substantial restraint on market momentum. According to the World Economic Forum, 94 percent of business leaders in 2025 reported facing shortages in talent critical for artificial intelligence functions. This statistic emphasizes the severity of the bottleneck, as available computing power and data cannot be effectively leveraged without qualified human oversight, creating a structural ceiling on growth where the demand for machine learning solutions remains unfulfilled due to the practical incapacity to implement them.

Market Trends

The Global Machine Learning Market is undergoing a transformative shift from passive predictive models to agentic systems capable of autonomous planning and executing multi-step workflows without human intervention. This evolution enables enterprises to deploy digital workers that reason through complex business processes independently, advancing capabilities significantly beyond simple content generation. This technology has become a strategic priority driving immediate capital allocation; according to UiPath's '2025 Agentic AI Research Report' from February 2025, 45 percent of U.S. IT executives indicated readiness to invest in agentic AI during the year to enhance operational automation.

Simultaneously, organizations are aggressively adopting Edge AI to process data locally on devices, thereby reducing latency and mitigating privacy risks associated with centralized cloud storage. This decentralization facilitates real-time decision-making for industrial IoT and mobile applications while ensuring functionality in disconnected environments. This architectural move toward on-device processing is reflected in corporate spending; according to ZEDEDA's 'Edge AI Matures' report from May 2025, 90 percent of organizations plan to increase their edge AI budgets for 2025 to scale these distributed capabilities and support efficient, low-latency computing.

Key Market Players

Amazon Web Services, Inc
Baidu, Inc
Domino Data Lab, Inc
Microsoft Corporation
Google, Inc
Alpine Data
IBM Corporation
SAP SE
Intel Corporation
SAS Institute Inc.

Report Scope

In this report, the Global Machine Learning (ML) Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Machine Learning (ML) Market, By Component

Services
Solutions

Machine Learning (ML) Market, By Enterprises Size

SMEs
Large Enterprises

Machine Learning (ML) Market, By Deployment

Cloud
On-premises

Machine Learning (ML) Market, By End-User

Healthcare
Retailer
IT & Telecom
Automotive and Transports
Advertising & Media
BFSI
Government
Defense
Others

Machine Learning (ML) Market, By Region

North America
- United States
- Canada
- Mexico
Europe
- France
- United Kingdom
- Italy
- Germany
- Spain
Asia Pacific
- China
- India
- Japan
- Australia
- South Korea
South America
- Brazil
- Argentina
- Colombia
Middle East & Africa
- South Africa
- Saudi Arabia
- UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Machine Learning (ML) Market.

Available Customizations:

Global Machine Learning (ML) Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

1. Product Overview

1.1. Market Definition
1.2. Scope of the Market
- 1.2.1. Markets Covered
- 1.2.2. Years Considered for Study
- 1.2.3. Key Market Segmentations

2. Research Methodology

2.1. Objective of the Study
2.2. Baseline Methodology
2.3. Key Industry Partners
2.4. Major Association and Secondary Sources
2.5. Forecasting Methodology
2.6. Data Triangulation & Validation
2.7. Assumptions and Limitations

3. Executive Summary

3.1. Overview of the Market
3.2. Overview of Key Market Segmentations
3.3. Overview of Key Market Players
3.4. Overview of Key Regions/Countries
3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global Machine Learning (ML) Market Outlook

5.1. Market Size & Forecast
- 5.1.1. By Value
5.2. Market Share & Forecast
- 5.2.1. By Component (Services & Solutions)
- 5.2.2. By Enterprises Size (SMEs, Large Enterprises)
- 5.2.3. By Deployment (Cloud, On-premises)
- 5.2.4. By End-User (Healthcare, Retailer, IT & Telecom, Automotive and Transports, Advertising & Media, BFSI, Government, Defense, Others)
- 5.2.5. By Region
- 5.2.6. By Company (2025)
5.3. Market Map

6. North America Machine Learning (ML) Market Outlook

6.1. Market Size & Forecast
- 6.1.1. By Value
6.2. Market Share & Forecast
- 6.2.1. By Component
- 6.2.2. By Enterprises Size
- 6.2.3. By Deployment
- 6.2.4. By End-User
- 6.2.5. By Country
6.3. North America: Country Analysis
- 6.3.1. United States Machine Learning (ML) Market Outlook
  - 6.3.1.1. Market Size & Forecast
    - 6.3.1.1.1. By Value
  - 6.3.1.2. Market Share & Forecast
    - 6.3.1.2.1. By Component
    - 6.3.1.2.2. By Enterprises Size
    - 6.3.1.2.3. By Deployment
    - 6.3.1.2.4. By End-User
- 6.3.2. Canada Machine Learning (ML) Market Outlook
  - 6.3.2.1. Market Size & Forecast
    - 6.3.2.1.1. By Value
  - 6.3.2.2. Market Share & Forecast
    - 6.3.2.2.1. By Component
    - 6.3.2.2.2. By Enterprises Size
    - 6.3.2.2.3. By Deployment
    - 6.3.2.2.4. By End-User
- 6.3.3. Mexico Machine Learning (ML) Market Outlook
  - 6.3.3.1. Market Size & Forecast
    - 6.3.3.1.1. By Value
  - 6.3.3.2. Market Share & Forecast
    - 6.3.3.2.1. By Component
    - 6.3.3.2.2. By Enterprises Size
    - 6.3.3.2.3. By Deployment
    - 6.3.3.2.4. By End-User

7. Europe Machine Learning (ML) Market Outlook

7.1. Market Size & Forecast
- 7.1.1. By Value
7.2. Market Share & Forecast
- 7.2.1. By Component
- 7.2.2. By Enterprises Size
- 7.2.3. By Deployment
- 7.2.4. By End-User
- 7.2.5. By Country
7.3. Europe: Country Analysis
- 7.3.1. Germany Machine Learning (ML) 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 Component
    - 7.3.1.2.2. By Enterprises Size
    - 7.3.1.2.3. By Deployment
    - 7.3.1.2.4. By End-User
- 7.3.2. France Machine Learning (ML) 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 Component
    - 7.3.2.2.2. By Enterprises Size
    - 7.3.2.2.3. By Deployment
    - 7.3.2.2.4. By End-User
- 7.3.3. United Kingdom Machine Learning (ML) 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 Component
    - 7.3.3.2.2. By Enterprises Size
    - 7.3.3.2.3. By Deployment
    - 7.3.3.2.4. By End-User
- 7.3.4. Italy Machine Learning (ML) Market Outlook
  - 7.3.4.1. Market Size & Forecast
    - 7.3.4.1.1. By Value
  - 7.3.4.2. Market Share & Forecast
    - 7.3.4.2.1. By Component
    - 7.3.4.2.2. By Enterprises Size
    - 7.3.4.2.3. By Deployment
    - 7.3.4.2.4. By End-User
- 7.3.5. Spain Machine Learning (ML) Market Outlook
  - 7.3.5.1. Market Size & Forecast
    - 7.3.5.1.1. By Value
  - 7.3.5.2. Market Share & Forecast
    - 7.3.5.2.1. By Component
    - 7.3.5.2.2. By Enterprises Size
    - 7.3.5.2.3. By Deployment
    - 7.3.5.2.4. By End-User

8. Asia Pacific Machine Learning (ML) Market Outlook

8.1. Market Size & Forecast
- 8.1.1. By Value
8.2. Market Share & Forecast
- 8.2.1. By Component
- 8.2.2. By Enterprises Size
- 8.2.3. By Deployment
- 8.2.4. By End-User
- 8.2.5. By Country
8.3. Asia Pacific: Country Analysis
- 8.3.1. China Machine Learning (ML) 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 Component
    - 8.3.1.2.2. By Enterprises Size
    - 8.3.1.2.3. By Deployment
    - 8.3.1.2.4. By End-User
- 8.3.2. India Machine Learning (ML) 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 Component
    - 8.3.2.2.2. By Enterprises Size
    - 8.3.2.2.3. By Deployment
    - 8.3.2.2.4. By End-User
- 8.3.3. Japan Machine Learning (ML) 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 Component
    - 8.3.3.2.2. By Enterprises Size
    - 8.3.3.2.3. By Deployment
    - 8.3.3.2.4. By End-User
- 8.3.4. South Korea Machine Learning (ML) 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 Component
    - 8.3.4.2.2. By Enterprises Size
    - 8.3.4.2.3. By Deployment
    - 8.3.4.2.4. By End-User
- 8.3.5. Australia Machine Learning (ML) 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 Component
    - 8.3.5.2.2. By Enterprises Size
    - 8.3.5.2.3. By Deployment
    - 8.3.5.2.4. By End-User

9. Middle East & Africa Machine Learning (ML) Market Outlook

9.1. Market Size & Forecast
- 9.1.1. By Value
9.2. Market Share & Forecast
- 9.2.1. By Component
- 9.2.2. By Enterprises Size
- 9.2.3. By Deployment
- 9.2.4. By End-User
- 9.2.5. By Country
9.3. Middle East & Africa: Country Analysis
- 9.3.1. Saudi Arabia Machine Learning (ML) 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 Component
    - 9.3.1.2.2. By Enterprises Size
    - 9.3.1.2.3. By Deployment
    - 9.3.1.2.4. By End-User
- 9.3.2. UAE Machine Learning (ML) 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 Component
    - 9.3.2.2.2. By Enterprises Size
    - 9.3.2.2.3. By Deployment
    - 9.3.2.2.4. By End-User
- 9.3.3. South Africa Machine Learning (ML) 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 Component
    - 9.3.3.2.2. By Enterprises Size
    - 9.3.3.2.3. By Deployment
    - 9.3.3.2.4. By End-User

10. South America Machine Learning (ML) Market Outlook

10.1. Market Size & Forecast
- 10.1.1. By Value
10.2. Market Share & Forecast
- 10.2.1. By Component
- 10.2.2. By Enterprises Size
- 10.2.3. By Deployment
- 10.2.4. By End-User
- 10.2.5. By Country
10.3. South America: Country Analysis
- 10.3.1. Brazil Machine Learning (ML) 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 Component
    - 10.3.1.2.2. By Enterprises Size
    - 10.3.1.2.3. By Deployment
    - 10.3.1.2.4. By End-User
- 10.3.2. Colombia Machine Learning (ML) 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 Component
    - 10.3.2.2.2. By Enterprises Size
    - 10.3.2.2.3. By Deployment
    - 10.3.2.2.4. By End-User
- 10.3.3. Argentina Machine Learning (ML) 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 Component
    - 10.3.3.2.2. By Enterprises Size
    - 10.3.3.2.3. By Deployment
    - 10.3.3.2.4. By End-User

11. Market Dynamics

11.1. Drivers
11.2. Challenges

12. Market Trends & Developments

12.1. Merger & Acquisition (If Any)
12.2. Product Launches (If Any)
12.3. Recent Developments

13. Global Machine Learning (ML) Market: SWOT Analysis

14. Porter's Five Forces Analysis

14.1. Competition in the Industry
14.2. Potential of New Entrants
14.3. Power of Suppliers
14.4. Power of Customers
14.5. Threat of Substitute Products

15. Competitive Landscape

15.1. Amazon Web Services, Inc
- 15.1.1. Business Overview
- 15.1.2. Products & Services
- 15.1.3. Recent Developments
- 15.1.4. Key Personnel
- 15.1.5. SWOT Analysis
15.2. Baidu, Inc
15.3. Domino Data Lab, Inc
15.4. Microsoft Corporation
15.5. Google, Inc
15.6. Alpine Data
15.7. IBM Corporation
15.8. SAP SE
15.9. Intel Corporation
15.10. SAS Institute Inc.