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Federated Learning Market

Global Federated Learning Market Size, Trends, Forecast: By Deployment Type: Cloud Based, On-premises; By Application: Industrial Internet of Things, Visual Object Detection, Drug Discovery, Risk Management, Augmented and Virtual Reality, Data Privacy Management, Others; By End Use; Regional Analysis; Competitive Landscape; 2024-2032

Global Federated Learning Market Outlook

The global federated learning market size reached nearly USD 131.40 million in 2023. The market is projected to grow at a CAGR of 10.7% between 2024 and 2032 to reach a value of around USD 328.04 million by 2032.

 

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.

 

Market Analysis

Based on deployment type, the market is segmented into cloud based and on-premises. On the basis of application, the market is classified into industrial internet of things, visual object detection, drug discovery, risk management, augmented and virtual reality, and data privacy management, among others.

 

The federated learning market segmentations, based on end use, include retail and e-commerce, automotive, IT and telecommunication, healthcare, BFSI, and manufacturing, among others. The major regional markets for federated learning include North America, Europe, the Asia Pacific, Latin America, and the Middle East and Africa.

 

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
  • Intel Corporation
  • Barron Associates Inc.
  • Sherpa.ai.
  • Apheris AI GmbH
  • IBM Corporation
  • Cloudera, Inc.
  • NVIDIA Corporation
  • Acuratio Inc.
  • Consilient Inc.
  • Others

 

Market Share by End Use

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

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 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. 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 Highlights of the Report

REPORT FEATURES DETAILS
Base Year 2023
Historical Period 2018-2023
Forecast Period 2024-2032
Scope of the Report

Historical and Forecast Trends, Industry Drivers and Constraints, Historical and Forecast Market Analysis by Segment:

  • Deployment Type
  • Application
  • End Use
  • Region
Breakup by Deployment Type
  • Cloud Based
  • On-premises
Breakup by Application
  • Industrial Internet of Things
  • Visual Object Detection
  • Drug Discovery
  • Risk Management
  • Augmented and Virtual Reality
  • Data Privacy Management
  • Others
Breakup by End Use
  • Retail and E-commerce
  • Automotive
  • IT and Telecommunication
  • Healthcare
  • BFSI
  • Manufacturing
  • Others
Breakup by Region
  • North America
    • United States of America 
    • Canada
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Others
  • Asia Pacific
    • China
    • Japan
    • India
    • ASEAN
    • Australia
    • Others
  • Latin America
    • Brazil
    • Argentina
    • Mexico
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • United Arab Emirates
    • Nigeria
    • South Africa
    • Others
Market Dynamics
  • SWOT
  • Porter's Five Forces Analysis
  • Key Indicators for Demand
  • Key Indicators for Price
Competitive Landscape
  • Market Structure
  • Company Profiles
    • Company Overview
    • Product Portfolio
    • Demographic Reach and Achievements
    • Certifications
Companies Covered
  • Google LLC
  • Intel Corporation
  • Barron Associates Inc.
  • Sherpa.ai.
  • Apheris AI GmbH
  • IBM Corporation
  • Cloudera, Inc.
  • NVIDIA Corporation
  • Acuratio Inc.
  • Consilient Inc.
  • Others

 

*At Expert Market Research, we strive to always give you current and accurate information. The numbers depicted in the description are indicative and may differ from the actual numbers in the final EMR report.

1    Preface
2    Report Coverage – Key Segmentation and Scope
3    Report Description

    3.1    Market Definition and Outlook
    3.2    Properties and Applications
    3.3    Market Analysis
    3.4    Key Players
4    Key Assumptions
5    Executive Summary

    5.1    Overview
    5.2    Key Drivers
    5.3    Key Developments
    5.4    Competitive Structure
    5.5    Key Industrial Trends
6    Market Snapshot
    6.1    Global
    6.2    Regional
7    Opportunities and Challenges in the Market
8    Global Federated Learning Market Analysis

    8.1    Key Industry Highlights
    8.2    Global Federated Learning Historical Market (2018-2023) 
    8.3    Global Federated Learning Market Forecast (2024-2032)
    8.4    Global Federated Learning Market by Deployment Type
        8.4.1    Cloud Based
            8.4.1.1    Historical Trend (2018-2023)
            8.4.1.2    Forecast Trend (2024-2032)
        8.4.2    On-premises
            8.4.2.1    Historical Trend (2018-2023)
            8.4.2.2    Forecast Trend (2024-2032)
    8.5    Global Federated Learning Market by Application
        8.5.1    Industrial Internet of Things
            8.5.1.1    Historical Trend (2018-2023)
            8.5.1.2    Forecast Trend (2024-2032)
        8.5.2    Visual Object Detection
            8.5.2.1    Historical Trend (2018-2023)
            8.5.2.2    Forecast Trend (2024-2032)
        8.5.3    Drug Discovery
            8.5.3.1    Historical Trend (2018-2023)
            8.5.3.2    Forecast Trend (2024-2032)
        8.5.4    Risk Management
            8.5.4.1    Historical Trend (2018-2023)
            8.5.4.2    Forecast Trend (2024-2032)
        8.5.5    Augmented and Virtual Reality
            8.5.5.1    Historical Trend (2018-2023)
            8.5.5.2    Forecast Trend (2024-2032)
        8.5.6    Data Privacy Management
            8.5.6.1    Historical Trend (2018-2023)
            8.5.6.2    Forecast Trend (2024-2032)
        8.5.7    Others 
    8.6    Global Federated Learning Market by End Use
        8.6.1    Retail and E-commerce
            8.6.1.1    Historical Trend (2018-2023)
            8.6.1.2    Forecast Trend (2024-2032)
        8.6.2    Automotive
            8.6.2.1    Historical Trend (2018-2023)
            8.6.2.2    Forecast Trend (2024-2032)
        8.6.3    IT and Telecommunication
            8.6.3.1    Historical Trend (2018-2023)
            8.6.3.2    Forecast Trend (2024-2032)
        8.6.4    Healthcare
            8.6.4.1    Historical Trend (2018-2023)
            8.6.4.2    Forecast Trend (2024-2032)
        8.6.5    BFSI
            8.6.5.1    Historical Trend (2018-2023)
            8.6.5.2    Forecast Trend (2024-2032)
        8.6.6    Manufacturing
            8.6.6.1    Historical Trend (2018-2023)
            8.6.6.2    Forecast Trend (2024-2032)
        8.6.7    Others
    8.7    Global Federated Learning Market by Region
        8.7.1    North America
            8.7.1.1    Historical Trend (2018-2023)
            8.7.1.2    Forecast Trend (2024-2032)
        8.7.2    Europe
            8.7.2.1    Historical Trend (2018-2023)
            8.7.2.2    Forecast Trend (2024-2032)
        8.7.3    Asia Pacific
            8.7.3.1    Historical Trend (2018-2023)
            8.7.3.2    Forecast Trend (2024-2032)
        8.7.4    Latin America
            8.7.4.1    Historical Trend (2018-2023)
            8.7.4.2    Forecast Trend (2024-2032)
        8.7.5    Middle East and Africa
            8.7.5.1    Historical Trend (2018-2023)
            8.7.5.2    Forecast Trend (2024-2032)
9    North America Federated Learning Market Analysis
    9.1    United States of America 
        9.1.1    Historical Trend (2018-2023)
        9.1.2    Forecast Trend (2024-2032)
    9.2    Canada
        9.2.1    Historical Trend (2018-2023)
        9.2.2    Forecast Trend (2024-2032)
10    Europe Federated Learning Market Analysis
    10.1    United Kingdom
        10.1.1    Historical Trend (2018-2023)
        10.1.2    Forecast Trend (2024-2032)
    10.2    Germany
        10.2.1    Historical Trend (2018-2023)
        10.2.2    Forecast Trend (2024-2032)
    10.3    France
        10.3.1    Historical Trend (2018-2023)
        10.3.2    Forecast Trend (2024-2032)
    10.4    Italy
        10.4.1    Historical Trend (2018-2023)
        10.4.2    Forecast Trend (2024-2032)
    10.5    Others
11    Asia Pacific Federated Learning Market Analysis
    11.1    China
        11.1.1    Historical Trend (2018-2023)
        11.1.2    Forecast Trend (2024-2032)
    11.2    Japan
        11.2.1    Historical Trend (2018-2023)
        11.2.2    Forecast Trend (2024-2032)
    11.3    India
        11.3.1    Historical Trend (2018-2023)
        11.3.2    Forecast Trend (2024-2032)
    11.4    ASEAN
        11.4.1    Historical Trend (2018-2023)
        11.4.2    Forecast Trend (2024-2032)
    11.5    Australia
        11.5.1    Historical Trend (2018-2023)
        11.5.2    Forecast Trend (2024-2032)
    11.6    Others
12    Latin America Federated Learning Market Analysis
    12.1    Brazil
        12.1.1    Historical Trend (2018-2023)
        12.1.2    Forecast Trend (2024-2032)
    12.2    Argentina
        12.2.1    Historical Trend (2018-2023)
        12.2.2    Forecast Trend (2024-2032)
    12.3    Mexico
        12.3.1    Historical Trend (2018-2023)
        12.3.2    Forecast Trend (2024-2032)
    12.4    Others
13    Middle East and Africa Federated Learning Market Analysis
    13.1    Saudi Arabia
        13.1.1    Historical Trend (2018-2023)
        13.1.2    Forecast Trend (2024-2032)
    13.2    United Arab Emirates
        13.2.1    Historical Trend (2018-2023)
        13.2.2    Forecast Trend (2024-2032)
    13.3    Nigeria
        13.3.1    Historical Trend (2018-2023)
        13.3.2    Forecast Trend (2024-2032)
    13.4    South Africa
        13.4.1    Historical Trend (2018-2023)
        13.4.2    Forecast Trend (2024-2032)
    13.5    Others
14    Market Dynamics
    14.1    SWOT Analysis
        14.1.1    Strengths
        14.1.2    Weaknesses
        14.1.3    Opportunities
        14.1.4    Threats
    14.2    Porter’s Five Forces Analysis
        14.2.1    Supplier’s Power
        14.2.2    Buyer’s Power
        14.2.3    Threat of New Entrants
        14.2.4    Degree of Rivalry
        14.2.5    Threat of Substitutes
    14.3    Key Indicators for Demand
    14.4    Key Indicators for Price  
15    Competitive Landscape
    15.1    Market Structure
    15.2    Company Profiles
        15.2.1    Google LLC
            15.2.1.1    Company Overview
            15.2.1.2    Product Portfolio
            15.2.1.3    Demographic Reach and Achievements
            15.2.1.4    Certifications
        15.2.2    Intel Corporation
            15.2.2.1    Company Overview
            15.2.2.2    Product Portfolio
            15.2.2.3    Demographic Reach and Achievements
            15.2.2.4    Certifications
        15.2.3    Barron Associates Inc.
            15.2.3.1    Company Overview
            15.2.3.2    Product Portfolio
            15.2.3.3    Demographic Reach and Achievements
            15.2.3.4    Certifications
        15.2.4    Sherpa.ai.
            15.2.4.1    Company Overview
            15.2.4.2    Product Portfolio
            15.2.4.3    Demographic Reach and Achievements
            15.2.4.4    Certifications
        15.2.5    Apheris AI GmbH
            15.2.5.1    Company Overview
            15.2.5.2    Product Portfolio
            15.2.5.3    Demographic Reach and Achievements
            15.2.5.4    Certifications
        15.2.6    IBM Corporation
            15.2.6.1    Company Overview
            15.2.6.2    Product Portfolio
            15.2.6.3    Demographic Reach and Achievements
            15.2.6.4    Certifications
        15.2.7    Cloudera, Inc.
            15.2.7.1    Company Overview
            15.2.7.2    Product Portfolio
            15.2.7.3    Demographic Reach and Achievements
            15.2.7.4    Certifications
        15.2.8    NVIDIA Corporation
            15.2.8.1    Company Overview
            15.2.8.2    Product Portfolio
            15.2.8.3    Demographic Reach and Achievements
            15.2.8.4    Certifications
        15.2.9    Acuratio Inc.
            15.2.9.1    Company Overview
            15.2.9.2    Product Portfolio
            15.2.9.3    Demographic Reach and Achievements
            15.2.9.4    Certifications
        15.2.10    Consilient Inc.
            15.2.10.1    Company Overview
            15.2.10.2    Product Portfolio
            15.2.10.3    Demographic Reach and Achievements
            15.2.10.4    Certifications
        15.2.11    Others
16    Key Trends and Developments in the Market


List of Key Figures and Tables

1.    Global Federated Learning Market: Key Industry Highlights, 2018 and 2032
2.    Global Federated Learning Historical Market: Breakup by Deployment Type (USD Million), 2018-2023
3.    Global Federated Learning Market Forecast: Breakup by Deployment Type (USD Million), 2024-2032
4.    Global Federated Learning Historical Market: Breakup by Application (USD Million), 2018-2023
5.    Global Federated Learning Market Forecast: Breakup by Application (USD Million), 2024-2032
6.    Global Federated Learning Historical Market: Breakup by End Use (USD Million), 2018-2023
7.    Global Federated Learning Market Forecast: Breakup by End Use (USD Million), 2024-2032
8.    Global Federated Learning Historical Market: Breakup by Region (USD Million), 2018-2023
9.    Global Federated Learning Market Forecast: Breakup by Region (USD Million), 2024-2032
10.    North America Federated Learning Historical Market: Breakup by Country (USD Million), 2018-2023
11.    North America Federated Learning Market Forecast: Breakup by Country (USD Million), 2024-2032
12.    Europe Federated Learning Historical Market: Breakup by Country (USD Million), 2018-2023
13.    Europe Federated Learning Market Forecast: Breakup by Country (USD Million), 2024-2032
14.    Asia Pacific Federated Learning Historical Market: Breakup by Country (USD Million), 2018-2023
15.    Asia Pacific Federated Learning Market Forecast: Breakup by Country (USD Million), 2024-2032
16.    Latin America Federated Learning Historical Market: Breakup by Country (USD Million), 2018-2023
17.    Latin America Federated Learning Market Forecast: Breakup by Country (USD Million), 2024-2032
18.    Middle East and Africa Federated Learning Historical Market: Breakup by Country (USD Million), 2018-2023
19.    Middle East and Africa Federated Learning Market Forecast: Breakup by Country (USD Million), 2024-2032
20.    Global Federated Learning Market Structure

Key Questions Answered in the Report

The market reached a value of nearly USD 131.40 million in 2023.

The market is estimated to grow at a CAGR of 10.7% between 2024 and 2032.

The market is estimated to witness a healthy growth in the forecast period of 2024-2032 to reach a value of around USD 328.04 million by 2032.

The growing use of AI and IoT in the manufacturing sector, the increasing incorporation of federated learning in the metaverse, and the increasing application of virtual and augmented reality across various sectors are the major drivers of the market.

The key trends in the market include the growing use of federated learning in the healthcare sector to boost drug discovery processes and heightening demand for self-driving cars.

Cloud based and on-premises are the different deployment types of federated learning.

Industrial internet of things, visual object detection, drug discovery, risk management, augmented and virtual reality, and data privacy management, among others, are the major applications of federated learning.

Google LLC, Intel Corporation, Barron Associates Inc., Sherpa.ai., Apheris AI GmbH, IBM Corporation, Cloudera, Inc., NVIDIA Corporation, Acuratio Inc., and Consilient Inc., among others, are the key market players.

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