AI Search Visibility Has Become an Enrollment Design Problem
Why this matters to Wen: if AI cannot find and summarise an institution's difference clearly, the student may never meet that difference at all.
of prospective students are already using AI platforms to research colleges.
EAB's framing matters because it moves AI search out of speculation and into a live recruitment visibility issue.
The Story
EAB's search-visibility audit piece is useful because it treats AI discovery as an operating problem instead of a trend report. If 46% of prospective students are already using AI platforms in their college research, then visibility is no longer only about classic ranking. It is about whether your institution can be found, represented accurately, and distinguished quickly inside summarised answers.
That raises the bar on content structure. Pages need complete, credible, specific information that can survive being quoted or compressed. If key proof points are thin, vague, or buried, an AI system may rely on third-party chatter instead. At that point the institution is no longer controlling its own first explanation.
For Wen, this is a strong reason to think beyond asset production. The higher-value move is helping shape content that can be surfaced accurately and trusted quickly. That is where editorial judgment, information hierarchy, and recruitment strategy now overlap.
Studio Wensday Angle
Build a quick rubric for one program page: can an AI tool find the page, summarise it clearly, and distinguish it from competitors without distortion?