Not All AI Is Built for Higher Ed: 3 Questions to Cut Through the Hype

Higher ed leaders are being flooded with AI promises: from “digital teammates” that work around the clock to automation tools that claim to solve every operational challenge. 

The reality? Not all AI is built for the complexity of supporting real students with real needs.

With so many AI-powered tools emerging, it can be difficult to separate what’s practical and effective from what’s performative or unlikely to improve student outcomes. The key is knowing what to look for before you commit. 

Here are three essential questions to ask to separate real impact from marketing spin.

1. Is it built on your institution’s data—or someone else’s?

Generic AI models often rely on broad, national data sets. That might work for general analysis, but it misses the unique factors influencing your student population.

At Civitas Learning, we build predictive models using only your institution’s data, so recommendations are relevant, timely, and trusted. That means your advisors aren’t just getting insights, they’re getting insights that matter for your students.

Why This Matters Now: Budget pressures and enrollment uncertainty mean higher ed leaders can’t afford to act on generic patterns that don’t reflect their actual student population. Decisions driven by non-local data can lead to wasted resources and missed opportunities, especially when every intervention needs to count.

2. Does it support your team—or try to replace them?

Some AI tools operate with minimal human oversight, making decisions without the necessary context. That can lead to missteps and erode trust among staff.

We take a “human-in-the-loop” approach: AI augments your team’s expertise, never replacing it. By combining predictive insights with your team’s judgment, you can ensure interventions are both data-informed and student-centered.

Why This Matters Now: The urgency to “do more with less” is real, but automating student support without context risks undermining trust with both students and staff. Institutions need tools that extend human capacity, not sideline it, so that relationships and judgment remain at the heart of student success.

3. Can it connect insight to action—in one place?

Most AI tools live in separate dashboards or CRMs, forcing your staff to toggle between systems to act on insights. That slows down response time and creates room for missed opportunities.

Our AI is embedded directly into advising workflows. This way, teams can move from data to action, without ever leaving the tools they use every day.

Why This Matters Now: With leaner teams and tighter timelines, every extra click, login, or data transfer delays action. When students are at risk, speed matters. Embedding AI where work already happens ensures insights lead to timely, coordinated action—while the opportunity to make a difference is still in front of you.

The Bottom Line

AI should build on your team’s expertise—not take it out of the equation. By asking these three questions, higher ed leaders can better distinguish between tools that sound impressive and those that deliver real, measurable impact for students.

Connect with Civitas Learning to explore how we can help your institution cut through the AI hype.