Artificial Intelligence at NIH

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The National Institutes of Health (NIH) makes a wealth of biomedical data available to research communities and aims to make these data findable, accessible, interoperable, and reusable—or FAIR. Additionally, the NIH seeks to make these data usable with artificial intelligence and machine learning (AI/ML) applications.

NIH has unique needs that can drive the development of novel approaches and application of existing tools in AI/ML. From electronic health record data, omics data, imaging data, disease-specific data, and beyond, NIH is poised to create and implement large and far-reaching applications using AI and its components.

Learn more about artificial intelligence activities at the NIH and relevant policies below.

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ODSS-Led Initiatives

Catalyzing new opportunities in AI and data science

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Networking and Information Technology Research and Development (NITRD)

Coordinates IT R&D activities of 23 Federal agencies.

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Bridge2AI

Propelling biomedical research by setting the stage for widespread adoption of AI 

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AI/ML Consortium to Advance Health Equity and Researcher Diversity

Increasing the participation and representation of researchers and communities currently underrepresented in the development of AI/ML models

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Policy Considerations and Guidance

Policies, guidelines, and best practices that should be considered as investigators pursue development and use of AI in biomedical and behavioral research

Multimodal AI

Advancing Health Research through Multimodal AI

Develops data-driven multimodal AI approaches

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Institute- and Center-Funded Initiatives

Developing and implementing AI/ML technologies across biomedical research domains

This page last reviewed on March 11, 2025