We are pleased to invite members of the Alliance for Artificial Intelligence in Healthcare (AAIH) to a focused webinar, “
Critical Considerations for AI Model Licensing Agreements and Data Ownership.” Tailored for biopharma, medtech, provider, and payer stakeholders, this session will address the contracting nuances that matter most when AI models and health data intersect—where regulatory expectations, patient privacy, and commercial strategy must align.
This program will go beyond general AI licensing concepts to highlight healthcare-specific deal points, with practical guidance for structuring agreements that support clinical validation, real world deployment, and responsible scaling across diverse care settings.
What we will cover:
- Data Ownership and Restrictions: Understanding who owns the data and the limitations on its use.
- Right to Train Own In-House Model: Discussing the rights and limitations around training your own AI models.
- Bias – Understanding the Underlying Dataset: Identifying and addressing potential biases in data.
- Field of Use Restrictions: Defining the specific applications and industries where the AI model can be utilized.
- Inability to Return Training Data: Navigating challenges related to the non-returnable nature of training data.
- Market Differentiation and Vendor Selection in a Crowded Landscape: Demanding objective evidence of technical and clinical differentiation—such as independent benchmarking against public baselines, reproducibility of results on external datasets, clarity on unique data access or moats, defensible IP around methods and data, and credible customer references.
Designed for the AAIH and Foley Hoag communities, this session will be especially valuable for legal, clinical, data science, and product leaders who negotiate with health systems, CROs, and biopharma partners; who manage de identification, governance, and consent frameworks; and who are building compliant, scalable pathways from research to regulated deployment.
