
Federated Learning Market Report and Forecast 2025-2034
Description
The global federated learning market size reached nearly USD 131.40 Million in 2024. The market is projected to grow at a CAGR of 10.70% between 2025 and 2034 to reach a value of around USD 363.14 Million by 2034.
Key Trends in the Market
Federated learning, also known as collaborative learning, refers to learning models that are used to train machine learning or artificial intelligence (AI) models on decentralised platforms. It uses various datasets and eliminates the requirement for centralising and sharing data, hence reducing the risk of data breaches.
The EMR’s report titled “Federated Learning Market Report and Forecast 2025-2034 offers a detailed analysis of the market based on the following segments:
Market Breakup by Deployment Type
The automotive sector accounts for a significant portion of the federated learning market share. Federated learning is witnessing a heightened deployment in self-driving cars to enhance the precision of autonomous driving calculations.
In addition, growing efforts by leading automotive manufacturers towards augmenting real-time response and reducing the latency of autonomous vehicles are further fuelling the segment’s growth. The anticipated increase in the demand for autonomous vehicles, coupled with rising disposable incomes, is expected to garner the segment’s growth in the coming years.
Market Share by Region
According to the federated learning market analysis, Europe holds a significant share of the market. Leading healthcare players across Europe are adopting federated learning solutions to boost the drug discovery processes. Moreover, the usage of machine learning in the pharmaceutical sector in well-established economies of Europe to enhance medical innovations is further boosting the demand for federated learning.
Over the forecast period, the anticipated surge in the incorporation of artificial intelligence in hospitals, owing to the growing shortage of healthcare professionals, is further aiding the federated learning market growth.
Competitive Landscape
The comprehensive EMR report provides an in-depth assessment of the market based on the Porter's five forces model along with giving a SWOT analysis. The report gives a detailed analysis of the key players in the global federated learning market, covering their competitive landscape and latest developments like mergers, acquisitions, investments and expansion plans.
Google LLC
Google LLC is one of the largest multinational technology companies around the world which offers artificial intelligence (AI) and online advertising services, and computer software systems, among others. It was founded in 1998 and is headquartered in California, the United States.
Intel Corporation
Intel Corporation is a multinational corporation which offers data centre solutions, IoT, smart and connected digital services, and federated learning, among others. The company was founded in 1968 and is headquartered in California, the United States.
Barron Associates Inc.
Barron Associates Inc. is a company which offers technological solutions to various sectors, including healthcare, defence, and aerospace, among others. The company was established in 1983 and is headquartered in Virginia, the United States.
Other federated learning market players include Sherpa.ai., Apheris AI GmbH, IBM Corporation, Cloudera, Inc., NVIDIA Corporation, Acuratio Inc., and Consilient Inc., among others.
Key Trends in the Market
Federated learning, also known as collaborative learning, refers to learning models that are used to train machine learning or artificial intelligence (AI) models on decentralised platforms. It uses various datasets and eliminates the requirement for centralising and sharing data, hence reducing the risk of data breaches.
- The growing use of artificial intelligence (AI), machine learning (ML), and the Internet of things (IoT), among other advanced technologies, in the manufacturing sector is a crucial federated learning market trend.
- Increasing deployment of federated learning in the metaverse for reducing the requirement for high computing power is adding to the market growth. In addition, growing concerns pertaining to user privacy and data security are likely to heighten the application of federated learning in the metaverse in the forecast period.
- The increasing application of virtual and augmented reality across various sectors, including education, gaming, event management, and healthcare, among others, is anticipated to propel the federated learning market growth in the coming years.
The EMR’s report titled “Federated Learning Market Report and Forecast 2025-2034 offers a detailed analysis of the market based on the following segments:
Market Breakup by Deployment Type
- Cloud Based
- On-premises
- Industrial Internet of Things
- Visual Object Detection
- Drug Discovery
- Risk Management
- Augmented and Virtual Reality
- Data Privacy Management
- Others
- Retail and E-commerce
- Automotive
- IT and Telecommunication
- Healthcare
- BFSI
- Manufacturing
- Others
- North America
- Europe
- Asia Pacific
- Latin America
- Middle East and Africa
The automotive sector accounts for a significant portion of the federated learning market share. Federated learning is witnessing a heightened deployment in self-driving cars to enhance the precision of autonomous driving calculations.
In addition, growing efforts by leading automotive manufacturers towards augmenting real-time response and reducing the latency of autonomous vehicles are further fuelling the segment’s growth. The anticipated increase in the demand for autonomous vehicles, coupled with rising disposable incomes, is expected to garner the segment’s growth in the coming years.
Market Share by Region
According to the federated learning market analysis, Europe holds a significant share of the market. Leading healthcare players across Europe are adopting federated learning solutions to boost the drug discovery processes. Moreover, the usage of machine learning in the pharmaceutical sector in well-established economies of Europe to enhance medical innovations is further boosting the demand for federated learning.
Over the forecast period, the anticipated surge in the incorporation of artificial intelligence in hospitals, owing to the growing shortage of healthcare professionals, is further aiding the federated learning market growth.
Competitive Landscape
The comprehensive EMR report provides an in-depth assessment of the market based on the Porter's five forces model along with giving a SWOT analysis. The report gives a detailed analysis of the key players in the global federated learning market, covering their competitive landscape and latest developments like mergers, acquisitions, investments and expansion plans.
Google LLC
Google LLC is one of the largest multinational technology companies around the world which offers artificial intelligence (AI) and online advertising services, and computer software systems, among others. It was founded in 1998 and is headquartered in California, the United States.
Intel Corporation
Intel Corporation is a multinational corporation which offers data centre solutions, IoT, smart and connected digital services, and federated learning, among others. The company was founded in 1968 and is headquartered in California, the United States.
Barron Associates Inc.
Barron Associates Inc. is a company which offers technological solutions to various sectors, including healthcare, defence, and aerospace, among others. The company was established in 1983 and is headquartered in Virginia, the United States.
Other federated learning market players include Sherpa.ai., Apheris AI GmbH, IBM Corporation, Cloudera, Inc., NVIDIA Corporation, Acuratio Inc., and Consilient Inc., among others.
Table of Contents
154 Pages
- 1 Executive Summary
- 1.1 Market Size 2024-2025
- 1.2 Market Growth 2025(F)-2034(F)
- 1.3 Key Demand Drivers
- 1.4 Key Players and Competitive Structure
- 1.5 Industry Best Practices
- 1.6 Recent Trends and Developments
- 1.7 Industry Outlook
- 2 Market Overview and Stakeholder Insights
- 2.1 Market Trends
- 2.2 Key Verticals
- 2.3 Key Regions
- 2.4 Supplier Power
- 2.5 Buyer Power
- 2.6 Key Market Opportunities and Risks
- 2.7 Key Initiatives by Stakeholders
- 3 Economic Summary
- 3.1 GDP Outlook
- 3.2 GDP Per Capita Growth
- 3.3 Inflation Trends
- 3.4 Democracy Index
- 3.5 Gross Public Debt Ratios
- 3.6 Balance of Payment (BoP) Position
- 3.7 Population Outlook
- 3.8 Urbanisation Trends
- 4 Country Risk Profiles
- 4.1 Country Risk
- 4.2 Business Climate
- 5 Global Federated Learning Market Analysis
- 5.1 Key Industry Highlights
- 5.2 Global Federated Learning Historical Market (2018-2024)
- 5.3 Global Federated Learning Market Forecast (2025-2034)
- 5.4 Global Federated Learning Market by Deployment Type
- 5.4.1 Cloud Based
- 5.4.1.1 Historical Trend (2018-2024)
- 5.4.1.2 Forecast Trend (2025-2034)
- 5.4.2 On-premises
- 5.4.2.1 Historical Trend (2018-2024)
- 5.4.2.2 Forecast Trend (2025-2034)
- 5.5 Global Federated Learning Market by Application
- 5.5.1 Industrial Internet of Things
- 5.5.1.1 Historical Trend (2018-2024)
- 5.5.1.2 Forecast Trend (2025-2034)
- 5.5.2 Visual Object Detection
- 5.5.2.1 Historical Trend (2018-2024)
- 5.5.2.2 Forecast Trend (2025-2034)
- 5.5.3 Drug Discovery
- 5.5.3.1 Historical Trend (2018-2024)
- 5.5.3.2 Forecast Trend (2025-2034)
- 5.5.4 Risk Management
- 5.5.4.1 Historical Trend (2018-2024)
- 5.5.4.2 Forecast Trend (2025-2034)
- 5.5.5 Augmented and Virtual Reality
- 5.5.5.1 Historical Trend (2018-2024)
- 5.5.5.2 Forecast Trend (2025-2034)
- 5.5.6 Data Privacy Management
- 5.5.6.1 Historical Trend (2018-2024)
- 5.5.6.2 Forecast Trend (2025-2034)
- 5.5.7 Others
- 5.6 Global Federated Learning Market by End Use
- 5.6.1 Retail and E-commerce
- 5.6.1.1 Historical Trend (2018-2024)
- 5.6.1.2 Forecast Trend (2025-2034)
- 5.6.2 Automotive
- 5.6.2.1 Historical Trend (2018-2024)
- 5.6.2.2 Forecast Trend (2025-2034)
- 5.6.3 IT and Telecommunication
- 5.6.3.1 Historical Trend (2018-2024)
- 5.6.3.2 Forecast Trend (2025-2034)
- 5.6.4 Healthcare
- 5.6.4.1 Historical Trend (2018-2024)
- 5.6.4.2 Forecast Trend (2025-2034)
- 5.6.5 BFSI
- 5.6.5.1 Historical Trend (2018-2024)
- 5.6.5.2 Forecast Trend (2025-2034)
- 5.6.6 Manufacturing
- 5.6.6.1 Historical Trend (2018-2024)
- 5.6.6.2 Forecast Trend (2025-2034)
- 5.6.7 Others
- 5.7 Global Federated Learning Market by Region
- 5.7.1 North America
- 5.7.1.1 Historical Trend (2018-2024)
- 5.7.1.2 Forecast Trend (2025-2034)
- 5.7.2 Europe
- 5.7.2.1 Historical Trend (2018-2024)
- 5.7.2.2 Forecast Trend (2025-2034)
- 5.7.3 Asia Pacific
- 5.7.3.1 Historical Trend (2018-2024)
- 5.7.3.2 Forecast Trend (2025-2034)
- 5.7.4 Latin America
- 5.7.4.1 Historical Trend (2018-2024)
- 5.7.4.2 Forecast Trend (2025-2034)
- 5.7.5 Middle East and Africa
- 5.7.5.1 Historical Trend (2018-2024)
- 5.7.5.2 Forecast Trend (2025-2034)
- 6 North America Federated Learning Market Analysis
- 6.1 United States of America
- 6.1.1 Historical Trend (2018-2024)
- 6.1.2 Forecast Trend (2025-2034)
- 6.2 Canada
- 6.2.1 Historical Trend (2018-2024)
- 6.2.2 Forecast Trend (2025-2034)
- 7 Europe Federated Learning Market Analysis
- 7.1 United Kingdom
- 7.1.1 Historical Trend (2018-2024)
- 7.1.2 Forecast Trend (2025-2034)
- 7.2 Germany
- 7.2.1 Historical Trend (2018-2024)
- 7.2.2 Forecast Trend (2025-2034)
- 7.3 France
- 7.3.1 Historical Trend (2018-2024)
- 7.3.2 Forecast Trend (2025-2034)
- 7.4 Italy
- 7.4.1 Historical Trend (2018-2024)
- 7.4.2 Forecast Trend (2025-2034)
- 7.5 Others
- 8 Asia Pacific Federated Learning Market Analysis
- 8.1 China
- 8.1.1 Historical Trend (2018-2024)
- 8.1.2 Forecast Trend (2025-2034)
- 8.2 Japan
- 8.2.1 Historical Trend (2018-2024)
- 8.2.2 Forecast Trend (2025-2034)
- 8.3 India
- 8.3.1 Historical Trend (2018-2024)
- 8.3.2 Forecast Trend (2025-2034)
- 8.4 ASEAN
- 8.4.1 Historical Trend (2018-2024)
- 8.4.2 Forecast Trend (2025-2034)
- 8.5 Australia
- 8.5.1 Historical Trend (2018-2024)
- 8.5.2 Forecast Trend (2025-2034)
- 8.6 Others
- 9 Latin America Federated Learning Market Analysis
- 9.1 Brazil
- 9.1.1 Historical Trend (2018-2024)
- 9.1.2 Forecast Trend (2025-2034)
- 9.2 Argentina
- 9.2.1 Historical Trend (2018-2024)
- 9.2.2 Forecast Trend (2025-2034)
- 9.3 Mexico
- 9.3.1 Historical Trend (2018-2024)
- 9.3.2 Forecast Trend (2025-2034)
- 9.4 Others
- 10 Middle East and Africa Federated Learning Market Analysis
- 10.1 Saudi Arabia
- 10.1.1 Historical Trend (2018-2024)
- 10.1.2 Forecast Trend (2025-2034)
- 10.2 United Arab Emirates
- 10.2.1 Historical Trend (2018-2024)
- 10.2.2 Forecast Trend (2025-2034)
- 10.3 Nigeria
- 10.3.1 Historical Trend (2018-2024)
- 10.3.2 Forecast Trend (2025-2034)
- 10.4 South Africa
- 10.4.1 Historical Trend (2018-2024)
- 10.4.2 Forecast Trend (2025-2034)
- 10.5 Others
- 11 Market Dynamics
- 11.1 SWOT Analysis
- 11.1.1 Strengths
- 11.1.2 Weaknesses
- 11.1.3 Opportunities
- 11.1.4 Threats
- 11.2 Porter’s Five Forces Analysis
- 11.2.1 Supplier’s Power
- 11.2.2 Buyer’s Power
- 11.2.3 Threat of New Entrants
- 11.2.4 Degree of Rivalry
- 11.2.5 Threat of Substitutes
- 11.3 Key Indicators for Demand
- 11.4 Key Indicators for Price
- 12 Competitive Landscape
- 12.1 Supplier Selection
- 12.2 Key Global Players
- 12.3 Key Regional Players
- 12.4 Key Player Strategies
- 12.5 Company Profiles
- 12.5.1 Google LLC
- 12.5.1.1 Company Overview
- 12.5.1.2 Product Portfolio
- 12.5.1.3 Demographic Reach and Achievements
- 12.5.1.4 Certifications
- 12.5.2 Intel Corporation
- 12.5.2.1 Company Overview
- 12.5.2.2 Product Portfolio
- 12.5.2.3 Demographic Reach and Achievements
- 12.5.2.4 Certifications
- 12.5.3 Barron Associates Inc.
- 12.5.3.1 Company Overview
- 12.5.3.2 Product Portfolio
- 12.5.3.3 Demographic Reach and Achievements
- 12.5.3.4 Certifications
- 12.5.4 Sherpa.ai.
- 12.5.4.1 Company Overview
- 12.5.4.2 Product Portfolio
- 12.5.4.3 Demographic Reach and Achievements
- 12.5.4.4 Certifications
- 12.5.5 Apheris AI GmbH
- 12.5.5.1 Company Overview
- 12.5.5.2 Product Portfolio
- 12.5.5.3 Demographic Reach and Achievements
- 12.5.5.4 Certifications
- 12.5.6 IBM Corporation
- 12.5.6.1 Company Overview
- 12.5.6.2 Product Portfolio
- 12.5.6.3 Demographic Reach and Achievements
- 12.5.6.4 Certifications
- 12.5.7 Cloudera, Inc.
- 12.5.7.1 Company Overview
- 12.5.7.2 Product Portfolio
- 12.5.7.3 Demographic Reach and Achievements
- 12.5.7.4 Certifications
- 12.5.8 NVIDIA Corporation
- 12.5.8.1 Company Overview
- 12.5.8.2 Product Portfolio
- 12.5.8.3 Demographic Reach and Achievements
- 12.5.8.4 Certifications
- 12.5.9 Acuratio Inc.
- 12.5.9.1 Company Overview
- 12.5.9.2 Product Portfolio
- 12.5.9.3 Demographic Reach and Achievements
- 12.5.9.4 Certifications
- 12.5.10 Consilient Inc.
- 12.5.10.1 Company Overview
- 12.5.10.2 Product Portfolio
- 12.5.10.3 Demographic Reach and Achievements
- 12.5.10.4 Certifications
- 12.5.11 Others
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