How College Admissions Are Changing: Tests, Data, and AI

After the Covid-19 disruptions prompted a broad move to test-optional admissions, elite and public universities are now reassessing how they choose students, and some institutions have decided to reinstate standardized testing or to tighten application rules. The federal government has increased scrutiny of campus admissions practices, requesting detailed applicant-level data and opening investigations into whether race or other factors were improperly considered, actions that have led universities to review their procedures and public statements more closely.

At the same time, admission offices under staffing and budget pressure have begun to deploy artificial intelligence tools to screen essays, extract grades from transcripts and speed routine tasks; proponents argue that AI can provide consistent, fast analysis, while critics caution that opaque algorithms may perpetuate bias and obscure human judgment. Examples of this shift include pilot programs at several research universities and medical schools that have used AI to narrow large applicant pools before human review, which has prompted calls for clear policies and oversight.

Consequently, applicants face a more complex landscape: if tests are required again, students who can prepare and show strong scores may gain an edge, yet holistic evidence such as rigorous coursework, recommendations and extracurricular projects remains important; moreover, schools that use AI will likely expect organized, verifiable application materials so that automated tools and human readers can assess authenticity. Prospective students should therefore read each institution’s published policies, keep records of original work, and consult counsellors so they can adapt to evolving practices without losing sight of their own academic goals.