University admissions are changing. As application volumes increase and institutions attract students from a wider range of countries and backgrounds, admissions teams are looking for ways to evaluate applicants efficiently without turning the process into a purely automated exercise.

Artificial intelligence is becoming part of that conversation.

AI-powered interviews, assessments, application screening, and workflow automation can help universities manage large applicant pools and gather additional insights beyond traditional application materials. But the future of admissions is unlikely to be about replacing admissions professionals with AI.

Instead, the opportunity lies in combining AI-powered assessment with structured human decision-making.

The most effective admissions processes will use technology to handle repetitive work while giving admissions teams more time to focus on context, potential, and the individual applicant.

Moving Beyond Grades and Applications

Academic records remain an important part of university admissions. However, grades and application forms do not always provide a complete picture of an applicant.

Depending on the programme, universities may also want to understand communication skills, motivation, problem-solving, critical thinking, interests, and how an applicant approaches real-world situations.

This is where structured assessments and interviews can add another layer of information.

An AI-powered interview can give applicants an opportunity to respond to questions about their academic interests, experiences, goals, or programme-specific scenarios. Similarly, skills or cognitive assessments can provide additional information that may not be visible from an application form.

The goal isn’t to replace existing admissions criteria. It is to create a broader evidence base for decision-making.

AI Interviews Can Make Interviews More Scalable

One of the biggest challenges for universities is scale.

When hundreds or thousands of applicants are applying to a programme, conducting individual first-round interviews can require significant staff time. Scheduling across different countries and time zones can make the process even more complicated.

One-way video interviews can address some of these challenges by allowing applicants to complete structured interviews asynchronously.

Instead of coordinating a meeting between an applicant and an admissions officer, universities can provide a set of questions that candidates answer when it is convenient for them.

Dynamic AI interviews offer another approach. Rather than simply presenting a fixed list of questions, an AI interviewer can conduct a more interactive conversation, with follow-up questions based on the applicant’s responses.

For admissions teams, this can create opportunities to gather more structured information without requiring an admissions officer to conduct every initial interview.

Assessments Can Add Another Layer of Insight

Interviews are only one part of the picture.

Depending on the programme and admissions criteria, universities may also use assessments to understand an applicant’s skills, knowledge, reasoning, or other relevant capabilities.

For example, an institution might use assessments to evaluate areas such as:

• Critical thinking
• Problem-solving
• Communication
• Logical reasoning
• Programme-specific knowledge
• Situational judgment
• Other skills relevant to the course

The important principle is relevance.

An assessment should be connected to what the university is actually trying to understand about an applicant. Adding more tests simply because technology makes them easy to administer can create unnecessary friction for applicants.

A good admissions workflow asks a simple question at every stage: What additional information does this step provide?

AI Should Support, Not Replace, Admissions Teams

The biggest opportunity for AI in admissions may not be making decisions. It may be helping admissions teams make better use of their time.

Consider a traditional process.

An admissions team receives applications, manually reviews information, sends interview invitations, schedules interviews, conducts conversations, takes notes, compares applicants, and prepares information for decision-makers.

AI can assist with some of these repetitive activities.

It can help organise applicant information, support structured interviews, summarise responses, assist with assessments, and surface relevant information for review.

The admissions professional can then spend more time on the parts of the process that require context and human judgment.

For example, an applicant may have an unusual academic background but demonstrate strong motivation and relevant experience during an interview. Another applicant may have excellent grades but provide limited evidence of interest in the programme.

These nuances require interpretation.

AI can help organise evidence. It should not remove the people responsible for understanding that evidence.

Human Context Still Matters

University admissions are about more than identifying applicants who perform well on a particular assessment.

Admissions teams may need to consider academic preparation, personal circumstances, programme fit, extracurricular experience, motivation, institutional requirements, and many other factors.

There can also be legitimate reasons why an applicant’s profile does not follow a conventional path.

This is why human review remains important.

An AI-generated score or interview analysis should be treated as one source of information within the broader admissions process. Admissions professionals should be able to review relevant evidence, understand how it fits into the overall application, and identify cases where additional context is needed.

The future of admissions is therefore not AI versus humans.

It is AI plus human judgment.

Responsible AI Will Become Increasingly Important

As universities introduce AI into admissions, responsible implementation needs to be part of the conversation from the beginning.

Applicants should understand when AI is being used and what role it plays in the process. Institutions should clearly communicate what candidates are expected to complete and how their information will be used.

Universities should also consider accessibility and candidate experience.

Not every applicant will have the same device, internet connection, environment, or familiarity with digital interviews. Admissions processes should be designed to minimise unnecessary barriers and provide appropriate support when technical or accessibility issues arise.

Most importantly, universities should regularly review how AI-assisted processes are performing.

Are applicants completing the process successfully?

Are the assessments measuring relevant skills?

Are admissions teams getting useful information?

Are there unexpected differences in applicant progression that require investigation?

Responsible AI requires ongoing review rather than a one-time implementation.

Creating a More Connected Admissions Workflow

The future of university admissions will likely involve more connected digital workflows rather than isolated technology tools.

An applicant might move through a process such as:

Application → AI-assisted screening → Skills assessment → AI interview → Admissions review → Final decision

Each stage should have a clear purpose.

Application screening can help organise large volumes of information. Assessments can provide additional evidence about relevant capabilities. AI interviews can help universities gather structured responses at scale. Human reviewers can then consider the complete picture before making decisions.

This approach can make the admissions process more efficient while preserving the role of admissions professionals.

It can also create a more consistent experience for applicants by establishing clear criteria and structured evaluation stages.

The Candidate Experience Cannot Be Forgotten

Technology should make admissions easier, not simply make it easier for universities to process more applications.

Applicants are also evaluating the institution throughout the admissions process.

A long, confusing, or repetitive assessment experience can negatively affect how students perceive a university. Conversely, a clear and well-designed digital process can make the institution feel accessible and organised.

Universities should therefore consider the applicant experience when designing AI-powered workflows.

Keep instructions clear. Explain what is expected. Avoid unnecessary assessments. Make interviews accessible across devices where possible. Provide appropriate support.

The best technology is often the technology that candidates barely notice because it makes the process simpler.

The Future Is a Partnership Between Technology and People

AI has the potential to change how universities approach admissions, particularly as application volumes grow and institutions become increasingly global.

AI interviews can make structured conversations more scalable. Assessments can provide additional evidence about applicant capabilities. Automation can reduce administrative workloads and help admissions teams manage complex workflows.

But technology alone will not create better admissions.

The future will depend on how universities combine these capabilities with human expertise.

Admissions professionals understand institutional priorities, programme requirements, applicant context, and the broader educational environment. AI can help them process information and structure evidence more efficiently, but human judgment remains essential to understanding the individual behind the application.

The future of university admissions is therefore not about choosing between AI and people.

It is about designing a smarter partnership between the two.

When AI handles repetitive processes and helps organise meaningful applicant information, admissions teams can spend more time doing what technology cannot easily replicate: understanding context, asking better questions, and making thoughtful decisions about the students they welcome into their institutions.

Interviewer.AI is a purpose-built technology platform designed to help recruiters. We also partner with universities to support admissions and coaching, enabling them to use technology to better assess potential, skills, and readiness. Our mission is to make hiring more equitable, explainable, and efficient by enabling teams to screen candidates early and shortlist those who best meet role-specific criteria.

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

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.