The 2027 EDUCAUSE Top 10 List Isn’t Really About Technology
by Claire L. Brady, EdD
Every year, I look forward to the EDUCAUSE Top 10 because it offers a useful snapshot of what technology leaders across higher education are wrestling with. The newly released 2027 EDUCAUSE Top 10 in Higher Ed Technology is framed around navigating an “age of perpetual change,” and the list includes plenty of topics we would expect: AI, cybersecurity, data governance, enrollment, digital experiences, and increasingly constrained resources. But when I read all ten together, something else jumped out at me:
This list isn't really about technology. It’s about leadership.
Look at the first two priorities: determining where AI adds real value and future-proofing students for a volatile world. EDUCAUSE describes a shift from asking whether we could use AI toward more intentionally asking whether, why, and how we should use it. At the same time, institutions need to prepare students with durable abilities to think, adapt, exercise judgment, and keep learning as technologies change.
That combination matters.
From Adoption to Judgment
For the last few years, much of higher ed's AI conversation has understandably focused on access and adoption. What tools should we provide? What policies do we need? How do we train people to use them? The 2027 list suggests we are entering a more mature phase. The question isn't simply Can we use AI here? It is Does using AI here actually make something better?
That requires judgment. Institutions need ways to distinguish an exciting demo from meaningful institutional value and experimentation from something ready to scale. They also need governance structures that create enough guardrails to protect people and data without making responsible experimentation impossible. EDUCAUSE explicitly calls for balancing standards and institutional values with spaces for autonomy and experimentation.
The Human Themes Are Everywhere
What struck me even more is how often people, trust, and experience appear across a technology list. Cybersecurity requires balancing boundaries with autonomy and trust. Technology design needs to be human-centered, accessible, and responsive to actual users. AI support must meet people at different levels of readiness rather than assuming everyone is equally enthusiastic—or equally terrified. And institutions should reduce technological friction so students and employees can spend less energy navigating systems and more energy doing the work that matters. Pasted text Pasted text
That is not primarily a technology challenge. It is an organizational one.
I especially appreciate EDUCAUSE's invitation to listen to AI skeptics and resistors rather than dismiss them. Skepticism can surface risks, assumptions, and consequences that enthusiasm misses. The goal shouldn't be getting everyone to the same level of excitement about AI. It should be building enough understanding and trust that we can make thoughtful decisions together.
Four Questions for Your Leadership Team
Rather than adding these ten issues to ten different committee agendas, I would bring the list to your cabinet or leadership team and ask:
Where are we investing in technology without being clear about the value we expect it to create?
Are we preparing students and employees for today's tools, or building the judgment and adaptability they'll need when those tools change?
Where are our structures—governance, data, security, procurement—helping responsible innovation, and where are they creating unnecessary friction?
Whose experience are we not hearing when we make technology decisions?
Perhaps the biggest message in the 2027 EDUCAUSE Top 10 is that perpetual change doesn't require us to chase every new technology faster. It requires institutions to become better at deciding what deserves our attention, investment, and trust. That feels like a technology strategy worth building.
