Pre-Conference Workshop A1

A1 - Leading AI with Intention: A Working Session for University Leaders

Date Wednesday, 2 Dec Time 14:30 – 17:30 Price: 95.00 € Status: places available

Laurie Forcier

VP of Strategy, EDT&Partners

Laurie Forcier works at the intersection of education, innovation, and systems change. Over two decades, she has helped EdTech startups, universities, large corporates, and think tanks make sense of complexity and move good ideas forward - across K–12, higher education, and skills. She has led global teams, launched new initiatives, and built partnerships at scale. As a communicator and
editorial strategist, she is often the public voice for the organizations she represents, and specializes in making complex ideas clear and actionable. That approach shaped her contribution to Intelligence Unleashed, one of the most widely cited reports on AI in education.

Nina Huntemann

Senior Consultant North America, EDT&Partners

Nina Huntemann has spent two decades helping organizations get learning right at moments of growth, transformation, and technological change. As Chief Academic Officer at Chegg, she led product strategy through the integration of AI into the student experience, pushing teams beyond engagement metrics toward proficiency, confidence, and independence. As VP of Learning at edX, she led learning strategy across 160+ university partners, 3,300+ courses, and 40 million learners. At EDT&Partners, she advises EdTech companies and higher education institutions on product-market fit, go-to-market strategy, and positioning across US higher education and K–12. She is a founding member of Women Applying AI.

Over 90% of university staff now use AI in their work, and institutional adoption jumped 17 percentage points in a single year. Yet much of this adoption remains invisible to institutional leadership. Staff are experimenting with AI in their everyday work, while institutions are still developing the structures needed to understand, coordinate and govern what is already taking place. The challenge is no longer whether AI will be adopted, but how universities can shape that adoption intentionally.

In this interactive, hands-on working session, university leaders will explore the AI Management System (AIMS) framework and three key dimensions of institutional AI governance: Visibility (do you know where AI is operating?), Shared Capability (is institutional knowledge compounding or staying siloed?) and Continuous Oversight (are people, not algorithms, driving the decisions that matter?). A fourth dimension, AI Stewardship, frames the leadership question underneath all three: what kind of institution are you becoming, and is that a deliberate choice? Participants will assess where their own institution currently stands, identify gaps and challenges, and compare perspectives with peers facing similar questions.

Working in small groups, participants will then take a live governance challenge from their own institution and use a structured canvas to design a practical response. Real-world implementation examples will illustrate the decisions, trade-offs and approaches behind effective institutional AI governance. Participants will leave with a working governance framework, a concrete action plan and one prioritised AI governance challenge to address within 30 days.

Agenda:

Welcome & Icebreaker (10 min)
From AI Adoption to Institutional Intention (30 min)
Institutional AI Governance: Diagnostic & Peer Reflection (45 min)
Coffee Break (15 min)
Hands-on: Designing Your Institutional Response (45 min)
Peer Exchange & What Good Looks Like (25 min)
From Insight to Action (10 min)

Target Audience: University Leaders, Higher Education Executives, Academic Leaders, Digital and AI Strategy Leaders, Institutional Decision-Makers

Target Audience Sector: Higher Education

Prerequisite Knowledge: Some prior experience with AI adoption, digital transformation or institutional strategy in higher education. No technical AI expertise is required.

Expected Outcomes:

Assess their institution’s current position across key dimensions of AI governance.
Understand the AI Management System (AIMS) framework and its application at institutional scale.
Identify practical approaches to improving visibility, shared capability and continuous oversight.
Design a concrete response to an institutional AI governance challenge.
Define one prioritised governance action to take forward within 30 days.