Just a few years ago, higher education’s reaction to ChatGPT was pure panic.
Campuses rushed to ban tools. Faculty attempted to rewrite syllabi at breakneck speed. Students navigated a maze of inconsistent rules that varied from classroom to classroom and assignment to assignment. Institutions are now moving from reacting to AI toward determining how these technologies should be integrated into the core infrastructure that supports teaching, learning, and student success.
That moment has passed, and most institutions now accept that generative AI is here to stay—not just in the classroom, but across the learner journey, from advising, admissions, and student support.
But just as higher education begins to find its footing with generative AI, the ground has shifted again.
Agentic AI is the latest evolution in artificial intelligence. Simply put, it refers to systems that can plan, make decisions, use tools, and take action with a degree of autonomy to accomplish multi-step goals.
To visualize how this might work in higher education, an agentic AI system in advising could identify students at academic risk. It would then recommend appropriate interventions and coordinate outreach across advisors and support services.
Agentic systems don’t just respond to prompts. They act. In areas such as admissions, advising, and student assessment, this raises important questions about how AI can support human judgment without replacing it.
That shift raises bigger questions than plagiarism or acceptable use. It forces institutions to rethink where human judgment is essential, where automation genuinely adds value, and how governance keeps pace with systems that don’t just generate content, but also execute tasks.
The opportunity is enormous, and so is the responsibility. The institutions that thrive won’t be the ones that avoid agentic AI. They’ll be the ones who intentionally shape it.
Here’s where to start.
1. Revise policies with agentic AI in mind
Most AI policies were written for tools that respond to prompts. Agentic systems are different. They can initiate actions, make recommendations, and operate with limited supervision.
Policies should reflect this new shift towards agentic AI. Clarify where autonomy is appropriate, where human approval is required, and how decisions are documented. Governance shouldn’t slow innovation, but it must make accountability explicit.
An institution’s AI policy will likely become outdated within one year, so it’s best to plan to continue evolving and iterating your policy to stay aligned with ever-changing technology, at least annually.
2. Experiment, with humans in the loop
Agentic AI can unlock meaningful efficiency in curriculum planning, advising workflows, communications, and operational processes.
Pilot thoughtfully, start in lower-risk areas, and define guardrails. It’s critical that you keep humans responsible for oversight and final decisions to ensure the ethical and accurate usage of artificial intelligence. The goal isn’t full automation, but reducing the burden on administrative personnel through better coordination and faster insight; freeing people to focus on higher-value work such as mentoring students, strengthening programs, and making strategic decisions.
If used well, agents can handle the friction so people can handle the judgment.
3. Engage your vendors proactively
Many technology partners are already building agentic capabilities into their platforms. The question isn’t whether these features are coming, but whether they’ll reflect your institution’s priorities.
Talk to your vendors and ask them how agentic tools will function in your workflows. Offer input on how these systems should support your processes rather than override them.
It’s the Institutions that define the values and guardrails, while the vendors bring technical expertise. The strongest outcomes will come from collaboration, not passive adoption. Ultimately, institutions must define the governance, values, and guardrails that shape how these systems operate within their academic and administrative processes.
4. Stay current
Leaders don’t need to become technologists. But they do need working fluency. Some questions institutional leaders should ask:
- What can these systems do?
- Where are the risks?
- Where are peer institutions experimenting?
- How are regulatory conversations evolving?
Yesterday, the focus was generative AI. Today, it’s agentic AI. Tomorrow, it will be something else entirely.
The institutions that succeed will not simply adopt these technologies, but will build the leadership capacity and governance frameworks required to guide their responsible use.
Staying informed isn’t optional. Understanding where AI is headed is critical to knowing how best to leverage it while responsibly managing the associated risks. The difference won’t be the technology itself, but whether institutions build the capacity to adapt—leading with clarity, curiosity, and intention as each new wave of AI arrives.
