90% of University Staff Are Already Using AI. Does Anyone Know Where?

Leading AI with Intention: A Working Session for University Leaders

Nine in ten university staff are already using AI at work. Most of their institutions could not tell you where, how, or to what effect.

That gap, between the scale of adoption and the absence of institutional visibility, is the starting point for Leading AI with Intention, a half-day workshop taking place on Wednesday 2 December for university leaders, led by Nina Huntemann and Laurie Forcier of EDT&Partners.

The problem is not adoption

According to EDT&Partners’ April 2026 report, Leading AI with Intention: A Guide for University Leaders, institutional AI adoption climbed 17 percentage points in a single year, and staff usage now sits above 90%. On paper, that looks like a success story. In practice, the report argues, it is a governance problem in disguise.

Most of that growth has happened through individual initiative: a lecturer testing a new tool, a department building its own workaround, a team quietly automating a process nobody else knows about. Useful in isolation, but invisible in aggregate. Universities are not short of AI use. They are short of a clear picture of what is actually happening across their own institution, and who is accountable for it.

What the workshop covers

The workshop is built directly from the report’s AI Management System (AIMS) framework, and it is designed as a working session rather than a lecture. Participants spend the time mapping their own institution’s position, not listening to someone else’s.

The framework rests on three diagnostic dimensions:

• Visibility – Do you actually know where AI is being used across the institution?
• Shared Capability – Is what people are learning compounding into institutional knowledge, or staying locked in silos?
• Continuous Oversight – Are people still making the decisions that matter, or has that quietly shifted to the tools?

A fourth dimension, AI Stewardship, sits above the other three and frames the underlying leadership question: what kind of institution is this becoming, and is that happening by design or by default?

Each block of the workshop pairs a short facilitated input with structured peer discussion and individual planning time. Participants map their own institution against each dimension, work through real-world case examples (including one institution that has treated AI as operating infrastructure rather than a collection of tools), and leave with a concrete action plan for one governance priority they can act on straight away.

About the facilitators

Nina Huntemann brings more than two decades of experience at the intersection of higher education and edtech. She has held academic leadership roles at edX, where she led the Learning team as Vice President of Learning, and served as Chief Academic Officer at Chegg. Before moving into edtech, she was a tenured professor at Suffolk University, teaching communication and media studies. She holds a PhD in Communication from the University of Massachusetts Amherst.

Laurie Forcier is Vice President of Strategy at EDT&Partners, with over 25 years in education and a particular focus on the future of skills, work, and technology in learning. She holds a Master’s in Higher Education from the Harvard Graduate School of Education, where she worked for a decade, and previously led global thought leadership at Pearson. She also consults for ISTE and Educate Ventures Research, and speaks widely on AI in education.

Together, Huntemann and Forcier bring both the research behind the AIMS framework and years of hands-on experience helping institutions turn scattered AI activity into deliberate strategy.

Seats are limited, secure your place now.

Written for OEB 2026.