Stats Up AI Winter 2027
AI Leadership Academy (AILA)
Leading Statistics and Data Science
in the Age of AI
A two-day intensive program that equips academic and industry leaders with the vision, tools, and long-term community needed to drive sustainable AI innovation within their institutions.
Rice University, Houston, TX • January 7 – 8, 2027
Applications open October 1, 2026 • Deadline November 5, 2026
Cohort limited to 30 participants, selected through an application process.
Organized By
ASA Stats Up AI Interest Group
, hosted by the Department of Statistics, Rice University.
Overview
The current AI landscape is shifting rapidly, and academic and industry leaders in statistics at all levels—from emerging team leads to senior administrators—are proactively seeking to adapt their research, education, and team management to be AI-aware.
The AI Leadership Academy (AILA) is a two-day intensive program designed to facilitate this evolution by focusing on practical applications of AI for research and education, while providing strategies to support team members in AI-aware and/or AI-augmented roles and guiding the development of tailored institutional initiatives.
By fostering a collaborative network that extends beyond the academy through ongoing virtual check-ins, office hours, and a reunion at JSM 2027, we equip participants with the vision, tools, and long-term community necessary to drive sustainable AI innovation within their institutions.
Participants & Mentors
Participant Profile
- Academic scholars, educators, and industry leaders in statistics and data science.
- Department chairs, program directors, and research executives seeking to pilot AI initiatives in education, research, or institutional administration.
- The cohort is intentionally limited (max. 30 academy participants) to ensure high-engagement discourse and mentorship between academic and industry peers.
- Participants will be selected through an application process, with the cohort curated to ensure a balance across career stages, leadership roles, and sectors.
Speakers and Mentors
Speakers and mentors will be experienced statistical leaders who have led AI teams and initiatives.
Meet the speakers →The academy is guided by an Advisory Board of leaders from academia, industry, and the profession.
AI Leadership Learning Objectives
By the end of this two-day academy, participants will be able to:
Articulate the integration of statistical principles into modern AI frameworks and identify opportunities to apply statistical expertise in AI development.
Consider, adopt, and design approaches to evolve statistical curricula to be AI-aware and promote an AI-inclusive research culture.
Define practical strategies for managing cross-disciplinary AI research teams.
Develop clear messaging to communicate the value of rigorous statistical methodology to research design, data-driven inquiries, and uncertainty-aware decision making to diverse AI stakeholders.
Identify actionable strategies to support the professional growth and leadership development of team members in AI-focused, AI-augmented, and/or AI-aware roles.
Thursday, January 7, 2027
Focuses on exploring the intersection of statistics and AI, featuring expert insights, collaborative sharing of research and education challenges, and community-building activities to foster leadership adaptability.
Friday, January 8, 2027
Transition & Synthesis: Building on Day 1 discussions regarding key research pain points and education strategy, Day 2 transitions into actionable design and resource planning for institutional initiatives.
Post-Academy
- Continue being connected with mentors and peer-collaborators.
- Ongoing community: monthly Zoom check-ins for participants and an informal gathering at JSM 2027.
How to Apply
Admission is competitive and curated, with the cohort limited to approximately 30 participants.
