Award Structure and Funding
Innovation Incubator Awards
These awards fund multidisciplinary Mayo Clinic teams collaborating on significant AI-centered educational innovations. Teams receive recognition and tailored strategic support, including mentoring, visibility, and community participation.
- Tier 2: Breakthrough Project
One larger-scale, advanced project demonstrating significant innovation, interdisciplinary collaboration, and clearly defined pathways from educational improvements to measurable clinical outcomes.
Award: 1 project funded at $100,000
- Tier 1: Inception Projects
Early-stage, exploratory projects piloting innovative ideas with substantial potential to enhance educational methodologies and ultimately improve healthcare delivery.
Awards: 2 projects funded at $25,000 each
Individual Awards
Awarded to exceptional Mayo Clinic individuals — learners, faculty, or staff — pursuing innovative, entrepreneurial AI-driven educational projects designed to significantly elevate patient care and clinical outcomes.
Each award winner receives mentorship, strategic visibility, and support tailored to maximize project impact within one year.
Awards: 2 projects funded at $50,000 each
Strategic fit
The Richard M. Schulze Innovation Awards in Artificial Intelligence strategically align with Mayo Clinic’s comprehensive Bold. Forward. vision, emphasizing educational innovation as essential for sustained clinical and operational excellence.
These awards enhance Mayo Clinic’s global leadership role by fostering advanced educational practices that translate directly into superior patient outcomes and clinical excellence, reinforcing the organization's pioneering approach to responsible and ethical AI application.
Scope and focus areas
Awarded projects must demonstrate how educational AI innovation translates into measurable clinical improvements.
Proposals should explicitly define pathways from educational enhancements to tangible improvements in healthcare delivery, such as:
- Revolutionizing personalized education and clinical training
- Implementing innovative AI platforms to enhance clinical reasoning and diagnostic accuracy
- Fostering interdisciplinary educational collaboration
- Establishing scalable frameworks promoting responsible AI integration, equity, safety, and governance in educational contexts