The global federated learning market size is estimated to reach USD 297.5 million by 2030, registering to grow at a CAGR of 14.4% from 2025 to 2030 according to a new report by Grand View Research, Inc. The growth is primarily fueled by its unique capability to train machine learning (ML) models across decentralized devices while preserving data privacy. This approach allows multiple entities to collaborate on model training without sharing raw data, ensuring sensitive information remains on local devices. This privacy-centric paradigm aligns well with stringent data protection regulations and addresses growing concerns about data security. Concerns over data privacy and compliance with regulations drive the adoption of federated learning, as it allows for collaborative model training without sharing raw data, ensuring user privacy.
This unique approach attracts industries seeking a competitive edge. For instance, Google LLC has been a prominent advocate and practitioner of federated learning. One of its applications, Gboard, the virtual keyboard app, uses federated learning to improve predictive text suggestions without compromising user data. The market thrives due to fast-progressing ML methods and wider data availability. The proliferation of IoT devices and the rise of edge computing have propelled federated learning's adoption in the healthcare, finance, and IoT sectors. This approach allows collaborative model training across decentralized devices, ensuring data privacy while advancing AI capabilities. In healthcare, federated learning enables joint model development, improving diagnostics & treatments without compromising patient data privacy.
In finance, it facilitates secure analysis of transactional data across institutions, enhancing fraud detection. Its application in IoT utilizes distributed device data, empowering edge-based ML for improved device functionalities. North America, especially the U.S., is a center for technological innovation, led by Silicon Valley and various influential tech giants that propel progress. The region pioneers AI & ML advancements, cultivating an atmosphere that encourages the integration of advanced technologies, such as federated learning. There is a rising awareness among consumers in North America about data privacy & security. Federated learning, being a privacy-preserving technology, resonates with consumers' concerns, creating a demand for such privacy-centric solutions in various applications. These factors collectively contribute to the growing adoption & prominence of federated learning in North America, fostering an environment conducive to its continued expansion across industries.
Request a free sample copy or view report summary: Federated Learning Market Report
In terms of application, the Industrial Internet of Things segment dominates the market is anticipated to hold 24.8% in 2024.
The large enterprises segment accounted for the largest market revenue share in 2024.
The IT & telecommunications segment generated the highest market revenue in 2024.
North America dominated the market and accounted for 36.7% share in 2024.
Grand View Research has segmented the global federated learning market based on application, organization size, industry vertical, and region:
Federated Learning Application Outlook (Revenue, USD Million; 2018 - 2030)
Industrial Internet of Things
Drug Discovery
Risk Management
Augmented & Virtual Reality
Data Privacy Management
Others
Federated Learning Organization Size Outlook (Revenue, USD Million; 2018 - 2030)
Large Enterprises
SMEs
Federated Learning Industry Vertical Outlook (Revenue, USD Million; 2018 - 2030)
IT & Telecommunications
Healthcare & Life Sciences
BFSI
Retail & E-commerce
Automotive
Others
Federated Learning Regional Outlook (Revenue, USD Million; 2018 - 2030)
North America
U.S.
Canada
Mexico
Europe
UK
Germany
France
Asia Pacific
China
Japan
India
Australia
South Korea
Latin America
Brazil
Middle East & Africa (MEA)
KSA
UAE
South Africa
List of Key Players in Federated Learning Market
Acuratio, Inc.
Cloudera, Inc.
Edge Delta
Enveil
FedML
Google LLC
IBM Corporation
Intel Corporation
Lifebit
NVIDIA Corporation
Owkin, Inc.
"The quality of research they have done for us has been excellent..."