Resistance to AI Isn't Futile. It's Healthy.

"Resistance is futile."

Star Trek fans know this line as the chilling declaration of the Borg, an alien race bent on forcing others to assimilate into their cybernetic collective.

Those of us working in higher education technology may also recognize it as the feeling of inevitability that seems to accompany the rise of artificial intelligence (AI) capabilities. AI is all around us and isn't going anywhere, so we'd better get on board and assimilate.

Resistance is futile.

In his book The Coming Wave: AI, Power, and Our Future, Microsoft AI CEO Mustafa Suleyman expresses almost exactly that sentiment: "From where we stand today, it appears that containing this [AI] wave—that is controlling, curbing, or even stopping it—is not possible."

The inevitability of AI proliferation across higher education is certainly hard to argue against. It's already everywhere across our campuses: in our classrooms and meeting rooms, and in our systems and devices.

But ubiquity, if we're not careful, can be confused with utility. And that confusion risks unchecked and unstrategic adoption of technologies where they aren't needed or, worse, where they could do more harm than good.

It also risks dismissing legitimate concerns as foolish tilting at windmills. At precisely the moment when open dialogue is needed about what all these new AI capabilities mean, and when such dialogue is still possible, a failure to listen to and understand even the most skeptical among us will leave some of our most important questions unanswered and voices unheard.

So, I would offer a friendly counterpoint to the Borg's bold declaration: Resistance to AI isn't futile. It's healthy.

Resistance is often a sign that we're not yet convinced and that there's more work to be done. It's a reminder that there's still a beating heart inside each of us, that there are core values and principles at stake, and that assimilation must be in service to, not at the expense of, those values and principles.

This is a prevailing theme in the EDUCAUSE 2027 Top 10 report, where, for the first time, AI has ascended to the number one spot on our community's ranking of the most important technology issues impacting higher education. But ascendance doesn't signal consensus. Indeed, many of our institutions are still in the messy spaces of determining what AI means for them and whether and where adoption makes sense.

There's no question that AI has the potential to be, and for many of us already is, a useful tool for accomplishing and improving at least some aspects of our work. In EDUCAUSE's recent survey of higher education IT, institutional research, human resources, and business professionals, a full 94 percent of respondents said they've used AI for their work within the past six months.^Footnote1 Among those respondents, 73 percent reported using it either daily or weekly.

But "everyone's using it" doesn't tell the whole story. Most of us still feel a mix of optimism and caution about using these tools. A majority of respondents to that same survey also expressed concern about AI in areas like "increased misinformation" and "use of data without consent." Among our students as well, feelings about using AI in coursework are lukewarm, and risks such as plagiarism, cheating, and diminished learning may outweigh the benefits these tools can provide.^Footnote2

Of course, some concerns about AI run even deeper. Some fear that AI will erode our social fabric and remake the world in ways that feel devoid of human meaning and connection, or even render humans obsolete altogether. As tech pioneer Jaron Lanier put it:

"The danger isn't that a new alien entity will speak through our technology and take over and destroy us. To me the danger is that we'll use our [AI] technology to become mutually unintelligible or to become insane if you like, in a way that we aren't acting with enough understanding and self-interest to survive."^Footnote3

The argument for AI assimilation leaves important questions unresolved. Resistance may not be futile after all.

In higher education, certainly, AI still needs to demonstrate its value and earn its place as a resource that supports and builds on the core values and mission of our institutions. In our Top 10 panelist interviews and survey, we found that institutions are deliberately aligning AI adoption with their larger strategic priorities and goals.^Footnote4 For example, many are providing staff, faculty, and students with clear guidance on when, how, and why they should (or shouldn't) use AI in their work and learning.

In other words, some of our institutions are already starting to do the hard and necessary work of both assimilating and resisting where they know they can and should.

In our classrooms, adoption for adoption's sake isn't good enough. AI, like any other technology intended to support student learning and success, needs to align with learning goals and, ideally, help create new possibilities for education.

These are the same ideals we expressed decades ago in one of the very first EDUCAUSE Top 10 reports, when "e-learning environments" were new and offered technology teams the opportunity to support "new pedagogical approaches" and create "new forms of learning communities."^Footnote5 We saw the same thinking more recently in discussions about the adoption of emerging technologies like XR that have "the potential to be a game changer for pedagogy" but "must be deployed thoughtfully."^Footnote6

These same ideals can guide decisions about the adoption of AI as well, not as an inevitability, value be damned, but as a tool to be adopted with purpose and for the clear benefit of the institutional mission. The speed, scale, and breathtaking implications of AI adoption may be unprecedented, but the heart of higher education still beats stronger.

How can healthy resistance show up at our institutions, then? Perhaps in ways both big and small, and certainly with people and in places where we still have the power of choice:

• In conversations with solution and industry partners, demanding a compelling case for how new AI features enrich and move the user experience forward and enable the institution to accomplish its goals.
• In shoring up our institutions' data governance structures, ensuring our new AI tools align with sound data practices and support data user literacy and decision-making.
• In strengthening our institutions' cybersecurity posture, raising awareness of the risks of these tools to the institution, its data, and its people.
• In conversations among our leaders and staff across the campus, openly and honestly discussing and documenting what's working with AI, where it may be subtracting from rather than adding to our capacity and effectiveness, and where the real, helpful strategic opportunities actually lie.

Resistance to AI isn't futile. It's healthy. And, importantly, it's still possible to be more discerning in our engagement with these tools and to meet the Borg on our terms.

Notes

1. Jenay Robert, The Impact of AI on Work in Higher Education (EDUCAUSE, January 2026). Jump back to footnote 1 in the text.↩
2. Kristen Gay and Nicole Muscanell, 2026 EDUCAUSE Students and Technology Report: Steady Through Change (EDUCAUSE, March 2026). Jump back to footnote 2 in the text.↩
3. Jaron Lanier, "Tech Guru Jaron Lanier: 'The Danger Isn't That AI Destroys Us. It's That It Drives Us Insane," The Guardian, March 23, 2023. Jump back to footnote 3 in the text.↩
4. Mark McCormack and the 2026–2027 EDUCAUSE Top 10 Panel, 2027 EDUCAUSE Top 10: The Age of Perpetual Change (EDUCAUSE, October 2026). Jump back to footnote 4 in the text.↩
5. Paul B. Gandel and the EDUCAUSE 2000 Current Issues Committee, "Top 10 IT Challenges of 2000," EDUCAUSE Quarterly 23 no. 2 (June 2000), 12–13. Jump back to footnote 5 in the text.↩
6. Jeffrey Pomerantz, XR for Teaching and Learning: Year 2 of the EDUCAUSE/HP Campus of the Future Project (EDUCAUSE, October 2019). Jump back to footnote 6 in the text.↩

Mark McCormack is Interim Vice President, Research, Insights, and Analytics, at EDUCAUSE.