Transfer Learning Market Size, Share and Trends 2026 to 2035

Revenue, 2025

USD 2.93 Bn

Forecast Year, 2035

USD 23.64 Bn

CAGR, 2026 - 2035

23.22%

Report Coverage

Global

What is the Transfer Learning Market Size?

The global transfer learning market size was calculated at USD 2.93 billion in 2025 and is predicted to increase from USD 3.61 billion in 2026 to approximately USD 23.64 billion by 2035, expanding at a CAGR of 23.22% from 2026 to 2035. The transfer learning market is experiencing growth due to the high deployment of AI models without incurring additional costs. Such functionalities are highly preferred by organizations to maintain their economic charts along with high-tech trained AI/ML models, further propelling the growth of the market. Reduced computational costs and easy overcoming of data scarcity in specialized applications are other major benefits observed during the growth of the market.

Market Highlights

• North America led the transfer learning market, accounting for a share of approximately 42% in 2025.
• Asia Pacific is observed to be the fastest-growing region with the highest CAGR in the forecast period.
• By learning type, the fine-tuning segment holding a share of approximately 44% led the market in 2025.
• By learning type, domain adaptation transfer learning segment is observed to be the fastest growing in the forecast period.
• By component, the software tools/platforms segment led the transfer learning market by accounting for a share of approximately 73% in 2025.
• By component, the services segment is observed to be the fastest-growing sector in the foreseen period with the highest CAGR.
• By end-use industry, the IT & telecom segment led the market by accounting for a share of approximately 18% in 2025.
• By end-use industry, the healthcare & life sciences segment is observed to be the fastest-growing segment in the foreseen period.

What is the Transfer Learning Market?

The market includes AI technologies, platforms, and services that enable the reuse of pre-trained models (or learned representations) to accelerate the development of new AI/ML models for related tasks with limited labeled data. Transfer learning reduces training time, computational costs, and dataset requirements, and is widely used in computer vision, NLP, speech, and multimodal applications. The market spans transfer learning software frameworks, MLOps integrations, model hubs, APIs, and professional services, driven by rapid enterprise Artificial Intelligenceadoption, growth in generative AI, and the need for faster model deployment across industries.

The transfer learning market is also observing growth due to trained AI/ML models, which are helpful for organizations to achieve results faster, which were time-consuming before. The technology is highly useful in domains that require much time in collecting crucial datasets, such as medical imaging or special manufacturing. The new technology is also a cost-effective and accessible approach for smaller organizations, further fueling the growth of the market.

Transfer Learning Market Trends

• Useful for Smaller Organizations- learning helps smaller organizations to use well-equipped AI/ML models with massive datasets or computational power, fueling the growth of the market.
• Economical Option- major organizations use pre-trained AI models to speed up ML deployment and cut additional development costs, further fueling the growth of the market.
• Versatile Approach- use of transfer learning in various domains for different purposes, such as in banking, healthcare, automotive, finance, and other domains, also helps to fuel the growth of the market.
• For instance, in November 2025, a medical article published in November 2025 stated that transfer learning can adapt established models to new settings, which can be helpful for cardiac as well as neurology patients.

Technological Shifts observed in the Transfer Learning Market

Progressive technological shifts adopted by various organizations are helping to fuel the growth of the market. Use of pre-trained models instead of custom models by organizations is a cost-effective method helpful for the growth of the market. The rise of generative AI models allows organizations to use pre-trained AI models for the organization's growth without training them from scratch, further fueling the growth of the market. Advanced techniques reducing the domain gap and allowing models to transfer knowledge effectively in relatable environments are another technological shift helpful for the growth of the transfer learning industry. Transfer learning is also a highly used technology in domains such as healthcare, with limited data, by leveraging knowledge from large datasets.

Market Scope

Segmental Insights

Learning Insights

Which Learning Segment led the Transfer Learning Market in 2025?

The fine-tuning segment, accounting for a share of approximately 44%, led the market in 2025. The segment has observed growth due to higher demand for AI/ML in various domains, with the requirement of pre-trained models to avoid training them from scratch. It helps to save time as well as cost, which is further helpful for the growth of the market. Fine-tuning is essential for domains with limited datasets, such as healthcare, finance, and manufacturing. Use of fine-tuning models such as VGG16, ResNet50, or YOLO, and large language models such as BERT, GPT, RoBERTa for specific tasks also helps to fuel the growth of the market.

The domain adaptation transfer learning segment is observed to be the fastest-growing segment in the foreseen period, with a higher CAGR. The segment signifies a specialized area of transfer learning where a model trained on one data distribution performs poorly on another domain due to differences in data features, which is helpful for the growth of the market. It grabs knowledge from the source domain to use it for the target domain. It helps organizations to save the additional costs of providing training to the models from scratch, further fueling the growth of the transfer learning market in the foreseeable period.

Component Type Insights

Which Component Segment led the Market in 2025?

The software tools/platforms segment led the transfer learning market, accounting for a share of approximately 73% in 2025. The market observes growth due to higher requirements for high-precision AI models, with limited datasets, and lower computation costs. Such software tools are used by developers for accessing, fine-tuning, and deploying pre-trained models. Such tools also help to accelerate the AI development lifecycle and model deployment for enterprises, further fueling the growth of the industry. Higher demand for specialized tools providing pre-trained models helpful for cost-saving is another major factor helpful for the growth of the market.

The services segment is observed to be the fastest-growing in the foreseen period. The market is observed to grow due to the adoption of pre-trained models by the organizations to avoid training them from scratch, use them for efficient working and results in new domains, and omit the additional training costs, as well. Services like custom model development and fine-tuning help pre-trained models to adapt to the working style of the required domain, to lower the time required for scratch training, further fueling the growth of the market. Services such as selecting the right pre-trained base model and evaluating domain compatibility to avoid negative transfer also help to fuel the growth of the transfer learning market in the foreseeable period.

End-Use Industry Insights

Which Segment of the End-Use Industry led the Market in 2025?

The IT & telecom segment, accounting for a share of approximately 18%, led the market in 2025. The advanced technology helps to cut the costs and time required for training models to adapt to the work culture of the current domain. The market also observes growth as it helps in 5G/6G deployments, enhances customer experience, aids predictive maintenance, and fraud detection, further fueling the growth of the market. The IT and telecom industries generate a huge amount of crucial data, requiring AI onset pre-trained models for saving time and additional costs, which is helpful for the growth of the market.

For instance, in July 2025, A high-level committee approved the framework to enable the transfer of surplus land and buildings held by telecom PSUs. The proposal allows any central government organization with an interest in such assets to inform within 90 days from the asset's listing on the government's asset monetization portal.

The healthcare & life sciences segment is expected to grow in the foreseeable period due to higher usage of pre-trained models that don't require additional training to work on huge datasets. The technology helps to tackle major issues in the healthcare domain, such as data scarcity for rare diseases, which is helpful for the growth of the market in the foreseeable period. Pre-trained models also help to detect diseases from MRI, CT, PET, and X-ray scans with over 99% accuracy, also propelling the growth of the transfer learning market in the foreseeable period.

• For instance, in January 2026, an article published on skin disease diagnostics stated that transfer learning is used to train AI models with dense neural networks (DNN) for skin disease detection.

Regional Insights

How Big is the North America Transfer Learning Market Size?

The North America transfer learning market size is estimated at USD 1.23 billion in 2025 and is projected to reach approximately USD 10.05 billion by 2035, with a 23.37% CAGR from 2026 to 2035.

How did North America lead the Transfer Learning Market?

North America led the market with a revenue of approximately 42% in 2025, mainly due to progressive factors such as deep learning and automated machine learning. The market also observes growth due to major investments in AI by big names of the region, such as Google, Microsoft, and NVIDIA. Higher adoption of pre-trained AI models to save time and costs of the organization in the region is a major factor fueling the growth of the market. The market is also propelled due to the higher requirement of handling smaller and specialized datasets in domains such as healthcare and finance for elevated security.

What is the Size of the U.S. Transfer Learning Market?

The U.S. transfer learning market size is calculated at USD 0.94 billion in 2025 and is expected to reach nearly USD 7.64 billion in 2035, accelerating at a strong CAGR of 23.31% between 2026 and 2035.

U.S. Transfer Learning Market Trends

The U.S. has a major contribution to the growth of the market due to factors such as broader integration into AI, deep learning, and ML frameworks, fueling the growth of the market. The region also uses transfer learning to improve model performance in natural language processing and computer vision for the growth of the transfer learning industry. The market also observes growth due to higher demand for AI models to overcome data limitations, reduce long training times, and lower the cost of AI development.

For instance, in January 2026, the US Army announced that it will soon launch a dedicated career path for officers specializing in AI and ML. The official area will involve the service's shift towards a data-driven, AI-enabled force.

Why is the Asia Pacific observed as the fastest-growing region in the Foreseen Period?

Asia Pacific is observed to be the fastest-growing region in the transfer learning market in the foreseen period, mainly due to factors such as AI adoption, digital transformation, and higher adoption of e-learning in the region. Corporate training and organizations leveraging the AI models for efficient working are another major factor fueling the growth of the market. Growing digital infrastructure in various domains such as schools, colleges, and organizations is also a major factor fueling the growth of the market. Transfer learning is also highly used in the region to train employees in AI, enhance cybersecurity, and also for data analytics. Smarter payment and digital systems also help to fuel the growth of the market in the foreseeable period.

China Transfer Learning Market Trends

China has a major contribution to the growth of the market due to the booming domains of the region, such as e-learning, corporate training, and the use of pre-trained AI/ML models for upskilling, personalized education, and technological advancement. Government initiatives to boost AI learning and a supportive framework for digital growth involving the use of AI/ML models also help to fuel the market growth in the region. Flexible and tailored experiences also help to fuel the growth of the market.

Who are the Major Players in the Transfer Learning Market?

The major players in the transfer learning market includeGoogle (Alphabet Inc.), Microsoft Corporation, NVIDIA Corporation, Amazon Web Services (AWS), IBM Corporation, Meta Platforms, Inc. (Facebook), Hugging Face, Baidu, Inc., H2O.ai , DataRobot:, Appen Ltd., and Owkin Inc.

Recent Developments in the Transfer Learning Market

• In July 2025, DeepSeek, a Chinese startup, released its new AI model known as R1. The company claims that the model requires less cost and less computing power compared to American tech firm models. (Source- https://www.iss.europa.eu)
• In January 2025, Investing.com launched ProPicks AI with extended coverage to NSE and BSE stocks. The AI model analyzes 4000+ Indian companies with 250+ financial metrics to allow people choose the best investment option.(Source- https://in.investing.com)

Segments Covered in the Report

By Learning Type

• Fine-tuning (full/partial)
• Feature Extraction / Frozen Layers Transfer
• Domain Adaptation Transfer Learning
• Multi-task / Meta-learning Transfer Approaches

By Component

• Software Tools / Platforms
  • Transfer learning frameworks
  • Model hubs & repositories
  • APIs & SDKs
• Services
  • Consulting & implementation
  • Custom fine-tuning services
  • Support & training

By End-Use Industry

• IT & Telecom
• BFSI
• Healthcare & Life Sciences
• Retail & E-commerce
• Manufacturing
• Automotive & Mobility
• Media & Entertainment
• Government & Defense
• Other Industries

By Region

• North America
• Europe
• Asia-Pacific
• Latin America
• Middle East & Africa