AI Pillar Leads and Working Groups
UAB’s AI Strategic Initiative is organized around a shared leadership model that brings together expertise from across the enterprise. AI Pillar Leads help guide work within major mission areas and connect related efforts across academic, research, clinical, and administrative domains.
This structure supports coordination, reduces duplication, and helps ensure that AI-related opportunities, needs, and risks are addressed through the right expertise. Each pillar includes working groups focused on priority areas where additional planning, stakeholder input, and implementation support are needed.
Academic mission
Teaching and Learning Pillar
The Teaching and Learning Pillar focuses on how AI can support faculty, students, curriculum development, instructional innovation, and responsible use in academic settings.
Pillar leads: Amy Chatham, Scott Phillips, and Megan Malone
- Faculty Development on AI in Teaching: Supports faculty awareness, training, and practical guidance for using AI in teaching and learning.
- AI Policy and Curriculum Development: Helps identify academic policy needs and explores how AI-related skills and expectations can be reflected in curriculum planning.
- Responsible Student Use of AI: Provides guidance on student use of AI tools, academic integrity considerations, and responsible engagement with emerging technologies.
Research mission
Research Pillar
The Research Pillar focuses on AI opportunities that strengthen research discovery, infrastructure, data access, compliance alignment, and responsible innovation. Research pillar leads will help identify priority working groups based on the needs of the research community, existing efforts already underway, and areas where enterprise coordination can accelerate progress.
Pillar leads: Yuliang Zheng, Jim Cimino, and Matt Might
- Access to AI tools, platforms, and infrastructure for researchers.
- Responsible use of data in AI-enabled research.
- De-identified data pathways and research acceleration.
- Training and support for AI-enabled research methods.
- Coordination across schools, centers, institutes, and the health system.
Clinical mission
Clinical Pillar
The Clinical Pillar focuses on AI opportunities in clinical operations, care delivery, quality, safety, clinical research, and coordination with health system technology and governance processes.
Pillar leads: Eric Wallace, Ryan Melvin
- Clinical AI Governance and Health System Coordination: Supports alignment between clinical AI priorities, health system technology processes, governance, safety, and operational readiness.
- Clinical Research Involving AI: Focuses on responsible pathways for clinical research use cases that involve AI, including data access, compliance, and review considerations.
Administrative mission
Administrative Pillar
The Administrative Pillar focuses on how AI can improve business processes, service delivery, workforce readiness, operational efficiency, and administrative decision support.
Pillar leads: Amy Ellis, Mike Matthews, Marylyn West, Rahul Thadani, Kathleen Stallings, and Evan Thrailkill
- Administrative AI Use Case Inventory and Approval Pathway: Helps identify, organize, and route administrative AI use cases through appropriate intake, review, and support processes.
- Workforce Development and AI Readiness: Supports training, change management, and practical guidance to help staff understand and use AI responsibly in their work.
- Enrollment AI Applications: Explores responsible AI use in enrollment-related processes, with attention to service, efficiency, transparency, and appropriate safeguards.
Operating model
How the Working Groups Will Operate
Working groups will build on existing efforts wherever possible rather than creating duplicative structures. Their role is to identify needs, gather stakeholder input, recommend practical next steps, and support responsible implementation within their area of focus.
This approach allows UAB to balance enterprise coordination with local expertise. The AI Integration Hub will serve as the central connection point, while pillar leads and working groups help ensure that AI adoption reflects the needs, opportunities, and risks within each pillar.