How Will AI Actually Show Up in Higher Ed in 2026?
by Claire L. Brady, EdD
AI didn’t arrive in higher education in 2025 — but it stopped being theoretical.
In 2025, campuses moved past “Should we talk about AI?” and into a more honest phase: We’re already using it. Students are already using it. Now what?
As we head into 2026, the question is no longer whether AI will shape higher education — it’s how intentionally we lead it.
Here’s what I’m projecting for the year ahead, based on what I’m seeing across institutions, leadership teams, and student-facing work.
1. The AI Bubble Won’t Burst in Higher Ed — But the Hype Will
Higher education is not experiencing an AI bubble; it’s experiencing an expectation correction.
By 2026:
Pilot fatigue will be real
Shiny tools without purpose will quietly disappear
Leaders will be far less impressed by demos and far more focused on outcomes
AI won’t vanish — but it will move from excitement to infrastructure. The institutions that thrive will be the ones that stop asking “What can this tool do?” and start asking “What problem are we solving?”
2. AI Will Become Invisible — Embedded, Not Announced
In 2026, the most impactful AI on campus won’t have a logo.
AI will increasingly live inside:
LMS platforms
CRMs and advising systems
Enrollment, financial aid, and student success workflows
Accessibility and accommodation tools
Students and staff won’t “go use AI” — they’ll simply experience faster, more responsive systems.
This shift will matter because it forces leaders to take responsibility. You can’t outsource ethics or strategy to a vendor when AI is woven into daily operations.
3. Critical Thinking Will Become a Leadership Priority (Again)
One of the most uncomfortable truths of AI adoption is this: efficiency can erode judgment if leaders aren’t careful.
By 2026, more institutions will:
Revisit learning outcomes tied to critical thinking
Rethink assessment models that reward speed over depth
Name AI discernment as a core leadership competency
The goal won’t be to ban AI — it will be to ensure students (and staff) can question, evaluate, and contextualize what AI produces.
4. AI Will Shift from “Academic Integrity Issue” to “Institutional Integrity Issue”
In 2025, AI conversations lived primarily in faculty senate rooms.
In 2026, they move decisively into:
Cabinet meetings
Risk management conversations
Accreditation, compliance, and legal strategy
Questions will change from “Is this cheating?” to:
Who is accountable when AI makes a mistake?
What happens when AI decisions disadvantage certain students?
How transparent are our systems — really?
This is where governance, not guidance documents, will matter most.
5. Student Affairs Will Emerge as a Strategic AI Leader
Here’s a quiet shift I expect in 2026: student affairs will stop being downstream of AI decisions.
Why?
AI touches advising, mental health, accessibility, belonging, career readiness, and engagement
These are human-centered domains — and AI works best when paired with context and care
Institutions that empower student affairs leaders to shape AI strategy (not just implement it) will see better outcomes and fewer unintended consequences.
6. Accessibility Will Become AI’s Strongest — and Most Scrutinized — Use Case
AI’s promise for accessibility is real:
Faster accommodations
Better transcription and translation
Personalized supports
But by 2026, accessibility leaders will push harder on:
Accuracy
Bias
Over-reliance on automated solutions
The question won’t be “Can AI help?”
It will be “Who is harmed if it fails?”
That tension will drive smarter, more ethical adoption.
7. AI Literacy Will Shift from Optional to Expected
By 2026, “AI literacy” won’t mean knowing how to prompt a chatbot.
It will mean:
Understanding limitations and hallucinations
Knowing when not to use AI
Recognizing ethical and privacy risks
Applying AI thoughtfully within one’s role
For leaders, this will be less about personal productivity and more about organizational fluency.
8. The Institutions That Win Won’t Be the Fastest — They’ll Be the Steadiest
The campuses that struggle most with AI in 2026 won’t be the ones that moved slowly.
They’ll be the ones that:
Chased tools without strategy
Delegated leadership to vendors
Treated AI as a tech problem instead of a cultural one
The institutions that succeed will be the ones that:
Invest in people, not just platforms
Build shared language across roles
Lead with clarity, humility, and intention
The Bottom Line
AI in higher education is no longer about prediction — it’s about practice.
2026 will reward leaders who are willing to:
Stay curious without being reactive
Move forward without pretending certainty
Keep humans — not hype — at the center of every decision
If 2025 was the year AI showed up on campus, 2026 is the year leadership shows up for AI.
