Students Are Using AI to Guide College Decisions. What Is It Telling Them?

Why It Matters

AI’s perceived authority is reshaping college selection, potentially altering enrollment patterns and widening equity gaps. Misleading AI outputs can cause students to miss better fits or make costly application mistakes.

Key Takeaways

• 46% of surveyed students used AI for college research in fall 2025.
• One‑third discovered new schools; one‑fifth removed schools after AI advice.
• Consultants report AI answers often lack nuance, leading to misinformation.
• Colleges are scrambling to ensure accurate data appears in AI tools.
• Equity concerns grow as under‑served students rely on single AI source.

Pulse Analysis

The surge in AI‑assisted college searches reflects a broader shift in how Gen Z gathers information. A recent EAB survey of more than 5,000 high‑schoolers shows AI usage jumping from 26% in spring to 46% by fall 2025, indicating rapid adoption. Students appreciate the speed of chatbot summaries and AI‑generated rankings, but the technology’s opacity often masks errors—misstated enrollment figures, nonexistent sports teams, or oversimplified diversity metrics. This blend of convenience and uncertainty is prompting families to treat AI as a first‑pass filter, while still seeking human validation for nuanced fit criteria.

Consultants highlight that effective AI queries demand sophisticated prompt engineering, a skill most families lack. Without precise context—such as specifying “water‑based recreation” versus “proximity to a lake”—AI can return vague or inaccurate results. The stakes are especially high for affordability and cultural fit, where a single erroneous data point can sway a student’s decision. Moreover, reliance on a solitary AI source amplifies inequities; students from under‑resourced schools may lack access to counselors who can verify or correct AI‑generated misinformation, potentially narrowing their college options.

Higher‑education institutions are responding by auditing how their data feeds into public AI models and by bolstering authentic, narrative‑driven content. Initiatives like Barnard’s daily‑life blogs aim to provide searchable, human‑curated stories that AI can surface, counterbalancing generic algorithmic summaries. As AI becomes entrenched in the admissions ecosystem, colleges that proactively ensure accurate, nuanced information in these tools will likely attract a more informed applicant pool, while those that ignore the trend risk misrepresentation and lost enrollment opportunities.