Key Dates

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Issued by

Office of The Director, National Institutes of Health (OD)

Purpose

Purpose
NIH is developing an institute-wide AI strategy that charts a progression from today’s data-science-driven analytics through semi-autonomous AI agents to fully autonomous, self-documenting biomedical AI beings. To inform this effort, NIH invites public comment on themes, pillars, and specific actions that should shape the forthcoming NIH AI Strategic Plan and its early one-year action plan.

Background
There is a need for a unified, OD-level AI structure to build synergy across program silos, improve transparency, and accelerate R&D and translation of AI discoveries to patient benefit. In parallel, a number of department wide and federal efforts on AI from R&D to operational use are in development. The NIH AI Strategy will align with these and build on prior efforts.

Information Requested
NIH welcomes input on any relevant topic, especially the areas below. Respondents need not address every bullet.

1. Strategic Architecture
   • Foundational themes (e.g., Data Readiness, Trust, Translation, Workforce) and pillars that should anchor the plan.
   • Potential actions and milestones for transitioning from analytics to semi-autonomous agents and, ultimately, AI beings capable of hypothesis generation, reproducibility studies, and continuous learning.
2. Research & Innovation Actions
   • High-impact use-cases for AI in biomedical discovery, public-health protection, and clinical decision-support.
   • Mechanisms to enhance reproducibility, reporting, and benchmarking of AI models in biomedicine.
3. Intramural–Extramural Synergy
   • Ways NIH intramural AI tools, models, and datasets can seed extramural innovation and vice versa.
   • Models for shared governance, licensing, and maintenance of jointly developed AI assets.
4. Operational Excellence
   • Opportunities for AI to improve NIH “customer” experiences (e.g., grant submission, peer review, clinical-center workflows, stakeholder engagement).
   • Metrics NIH should use to evaluate operational AI pilots.
5. Facilitating & Validating AI in Healthcare Delivery
   • Best-practice frameworks, testbeds, and regulatory-science collaborations (e.g., with FDA, VA) to evaluate safety, efficacy, and equity of clinical AI tools.
6. Reproducibility & Trust
   • Community-driven standards, audit trails, or other approaches that can facilitate reproducibility and enhance transparency as well as trust across the AI life cycle.
7. Partnerships & Ecosystem Building
   • Preferred modalities for NIH to collaborate with other federal agencies, state/local partners, international bodies, patient organizations, industry, and/or philanthropic entities.
   • Governance approaches that balance open science, privacy, national security/competitiveness, and intellectual-property considerations.

How to Submit a Response
Email: [email protected]
Subject Line: “RFI Response - NIH AI Strategy”
Format: 7 pages (PDF, Word, or plain-text); include section headers that correspond to the bullets, such as those above, when feasible.
Responses must be received by 11:59 p.m. ET on July 15, 2025. All submissions are voluntary; do not include proprietary, classified, or personally identifiable information you do not wish to make public. NIH may post anonymized summaries or use content to inform future solicitations or policy documents.

Web Resource
Updates on the strategy process will appear at ai.nih.gov.

Inquiries

Questions about this notice may be directed to ai-rfi @nih.gov

This RFI is for planning purposes only and shall not be construed as a solicitation or as obligating NIH to award funds or otherwise enter into agreements.