University admissions have long relied on a mix of grades, test scores, recommendation letters, and personal essays to decide which students receive offers. In recent years, however, a new tool has been reshaping the way admissions teams evaluate applicants: AI-powered video interviews. 

By combining convenience, scalability, and deeper insight into candidates’ communication skills and fit, AI video interviews are helping universities make better, fairer, and faster decisions — when used responsibly.

What are AI video interviews?

AI video interviews let applicants record answers to pre-set questions on video, or participate in live video interviews where AI helps structure and analyze the interaction. The AI can transcribe speech, analyze tone and clarity, flag relevant keywords related to program-specific competencies, and provide structured summaries to human reviewers. Some systems also evaluate nonverbal cues like facial expressions and eye contact, although this capability raises important ethical and accuracy concerns.

Why universities are adopting them

Admissions teams are under pressure: application numbers are rising, resources are limited, and programs need to discover fit beyond the transcript. AI video interviews offer several practical benefits:

Scalability. Interviewing thousands of applicants in person is impossible for most programs. Video interviews let teams screen more candidates without massively increasing staffing costs.

Standardization. Every applicant receives the same prompts and time limits, which reduces variability between interviewers and helps create a fairer baseline for comparison.

Richer evidence of fit. Essays and test scores show what applicants can produce in writing; interviews reveal how they communicate ideas, think on their feet, and show motivation and interpersonal skills.

Faster turnaround. Automated transcription and summarization accelerate the review process. Admissions officers can quickly scan highlights and focus in-depth reading on promising candidates.

Improved outreach and access. For international applicants or students from low-resource areas, video interviews reduce travel and scheduling barriers. Candidates can record on their own time with low-cost hardware — a smartphone or laptop with a webcam.

How AI adds value beyond a simple recorded interview

At face value, a recorded video could be reviewed manually. AI layer multiplies the usefulness of each recording:

Automatic summarization. Admissions officers don’t have to watch every video end-to-end. The AI produces concise summaries, timestamps of strong moments, and suggested rubric scores for quick triage.

Keyword and competency detection. AI models can detect whether an applicant mentions program-specific themes (e.g., “community health” for public health applicants or “sustainability” in environmental engineering), helping surface good thematic matches.

Bias reduction via consistent rubrics. While AI itself can carry bias risks, when designed carefully it enforces consistent evaluation criteria across applicants — reducing variability introduced by different human interviewers’ moods or expectations.

Interview prep analytics. Some platforms offer applicants practice runs, giving them a chance to improve how they present themselves — especially helpful for first-generation college applicants who may lack interview coaching.

Use cases across programs

Different programs use AI video interviews in different ways: selective colleges might use them to assess fit and communication; professional programs (business, engineering, public health) often target domain knowledge and problem-solving; graduate programs evaluate research motivation and presentation skills. Some schools use AI interviews only for shortlisted candidates; others include them as an optional supplement.

Ethical and fairness considerations

AI in admissions is useful but not a panacea. Universities must address serious ethical questions to ensure interviews improve equity rather than entrench unfairness.

Transparency. Applicants should know when AI analyzes their responses, what features are examined, and how the AI’s output informs decisions.

Fairness testing. Because AI models can pick up cultural or dialectal differences, systems must be evaluated across diverse samples to ensure they do not disadvantage certain groups.

Human oversight. AI should augment, not replace, human judgment. Admissions committees should review AI outputs and have the final say, especially in borderline or high-stakes cases.

Data privacy and consent. Video interviews hold sensitive biometric and personal data. Institutions must store, process, and delete recordings in line with privacy laws and applicants’ consent.

Best practices for universities

To harness AI video interviews responsibly, universities should follow several best practices:

Pilot and validate. Run pilots, compare AI-assisted decisions with traditional methods, and publish validation results internally to build trust.

Use rubrics. Define clear competencies and map AI signals to those competencies rather than letting the model generate opaque scores.

Ensure transparency. Provide applicants with clear disclosures and options to opt out or submit alternatives.

Train reviewers. Teach admissions officers how to interpret AI summaries and common model failure modes to prevent misreading outputs.

Protect data. Limit access to raw videos and implement strict retention and deletion policies.

Benefits for applicants

When done right, AI video interviews can help applicants too. They offer flexible scheduling, a uniform interview experience, and the possibility of automated feedback during practice runs. For international applicants, they save travel costs and logistical headaches. When universities publish clear evaluation criteria, applicants can prepare more effectively and present a fuller picture beyond grades and essays.

Looking ahead

AI video interviews are evolving. We’ll likely see improvements in transcription accuracy, better multilingual capabilities, and more robust fairness testing. Universities that prioritize responsible deployment — with transparency, human oversight, and strong data protections — will unlock value: a faster, fairer, and richer admissions process that recognizes qualities not captured in paper applications.

Conclusion

AI video interviews aren’t a magic bullet, but they’re a powerful tool when combined with thoughtful policy and human judgment. They expand access, increase efficiency, and reveal aspects of candidate fit that traditional measures may miss. With careful implementation that centers fairness, privacy, and transparency, AI video interviews can help admissions teams make better decisions — and help applicants tell their stories more completely.

Interviewer.AI is a technology platform purposely built to support Recruiters and HR teams in finding top talent for their companies. We also work with universities to help them with admissions and coaching, helping them use technology to solve for talent and training. Our mission is to make hiring equitable, explainable, and efficient. to screen in advance and shortlist the candidates that meet the criteria set. 

Schedule a demo today to learn more about how AI interviews can help your hiring.

Gabrielle Martinsson is a Content Writer at Interviewer.AI. She’s a tech geek and loves optimizing business processes with the aid of tech tools. She also loves travelling and listening to music in her leisure.