NIH Bridge2AI Enters Stage 2 with $130M for Health AI Tools
March 5, 2026 · 2 min read
Claire Cummings
The NIH Council of Councils has approved the Bridge to Artificial Intelligence program to advance to its second stage, marking a critical pivot in the agency's $130 million initiative to embed AI across biomedical research.
The January 29 decision shifts Bridge2AI from its first-stage focus on creating ethically sourced, AI-ready datasets to a more ambitious mandate: building tools, devices, and safety frameworks that translate those datasets into clinical and research applications.
What Stage 2 Looks Like
The second phase funds two interconnected initiatives:
Innovation Funnels will support teams that use the AI-ready datasets generated in Stage 1 to create practical tools — diagnostic algorithms, drug discovery platforms, clinical decision support systems — that demonstrate measurable health impact. The emphasis is on moving from data curation to deployable AI.
Network for AI Health Science will develop safety measures, validation protocols, and responsible-use frameworks for AI in health research. This addresses growing concern among regulators and the research community about AI reliability in high-stakes medical contexts.
Bridge2AI's first stage has already produced results that justify the expansion. NIH-funded investigators demonstrated that AI can speed identification of genetic variations underlying Alzheimer's and rare diseases, read X-rays for earlier cancer detection, and assess heart disease risk through non-invasive eye imaging.
Where the Funding Opportunities Will Appear
Bridge2AI is a Common Fund program, meaning funding flows through the NIH Director's office rather than individual institutes. Stage 2 funding opportunities have not yet been posted to commonfund.nih.gov/bridge2ai/funding, but based on Stage 1's timeline, expect Requests for Applications by mid-2026.
The program fits within NIH's broader AI push. The agency's FY2026 budget of $48.7 billion includes sustained investment in computational biology and machine learning infrastructure, with the BRAIN Initiative and National Institute of Biomedical Imaging and Bioengineering running parallel AI-focused programs.
Researchers with expertise in both AI/ML methods and specific disease areas are best positioned. Bridge2AI explicitly values interdisciplinary teams that combine computational scientists with domain experts — a team structure that Granted can help you build by identifying complementary funding opportunities.
Detailed coverage of NIH's AI funding landscape and upcoming Bridge2AI solicitations is available on the Granted blog.