AI in Admissions: please don’t do it just because you can

New tools promise faster processing, better student-course matching and improved risk assessment.

The Uni Guide, for example, uses AI to help students identify universities and courses that fit their aspirations, while UniReady Global has developed AI capabilities to help providers assess whether applicants are likely to be genuine students. Others are going further, seeking to automate significant parts, or even all, of the admissions process.

The attraction is obvious.

AI processes information at a scale no human team can match. It can triage applications, identify missing documents, flag inconsistencies, detect potential fraud and highlight where an applicant’s background, ambitions and chosen programme may not align.

For institutions under growing pressure to recruit effectively while managing compliance and costs, AI offers genuine advantages.

But there is a crucial distinction between using AI to support admissions decisions and allowing Agentic AI to make them.

The danger begins when a risk flag automatically becomes a rejection, a course-fit score becomes a gatekeeper, or an automated recommendation is treated as more objective than the human judgement it was designed to inform.

Three risks deserve particular attention.

The first is institutional repetition.

Professor Marnie Hughes-Warrington has observed that the large language models underpinning AI are inherently historical. They learn from what has happened before.

That is precisely what makes them effective; but it also means they risk reproducing yesterday’s patterns rather than identifying tomorrow’s potential.

Universities rightly talk about preparing students for a changing world. Yet admissions systems trained on previous cohorts may repeatedly favour applicants who resemble those already admitted. Efficiency could come at the expense of opportunity, overlooking talented students whose potential sits outside historical norms.

The second challenge is bias.

Admissions systems trained on previous cohorts may repeatedly favour applicants who resemble those already admitted

AI systems inevitably inherit the strengths and weaknesses of the data on which they are trained. Existing cultural, linguistic and educational biases are not necessarily removed through automation; they can become embedded and amplified.

For institutions committed to widening participation and diversity, that should give pause. As Norbert Wiener’s “alignment problem” reminds us, AI systems do not always produce outcomes that reflect the values of those who build them.

The third challenge is ethical.

Nelson Mandela famously described education as ‘the most powerful weapon which you can use to change the world’. If that is true, decisions about who gains access to education cannot become purely technical exercises.

Admissions decisions shape lives. While AI may create an appearance of neutrality, it cannot exercise judgement, empathy or accountability. As Pope Leo XIV recently observed, entrusting algorithms with deciding who is worthy of opportunity risks handing over responsibility for defining the boundaries of human possibility.

None of this is an argument against AI. Quite the opposite.

Used well, AI can make admissions more efficient, more consistent and more effective. In developing AI applications for The Uni Guide and UniReady Global, four defining guardrails were adopted: transparency about where AI is used; clarity about how recommendations are reached; meaningful human oversight; and human accountability for both processes and outcomes.

Higher education needs to embrace AI but it should resist the temptation to confuse automation with wisdom.

The future of admissions is not AI-led but AI-supported: systems that recommend, explain and identify risk, while people make the decisions, accept responsibility for them and remain accountable for the consequences.

That is not just better admissions practice. It is how universities ensure technology continues to serve their mission, rather than redefine it.

About the author: Dr Lawrence Pratchett is the chief executive officer of UniReady Global, a cutting-edge technology platform that streamlines and strengthens the assessment of international student applications. Leveraging advanced document and financial verification alongside an AI-driven genuine-student interview, UniReady Global helps universities significantly reduce risk in their admissions processes.

Before founding UniReady Global, Pratchett held senior academic leadership roles at the University of Canberra, serving as professor of politics, pro vice-chancellor, and previously dean of the faculty of business, government and law.

Lawrence is chaining a panel on AI in Recruitment and Admissions at the forthcoming PIE Live Asia Pacific on the Gold Coast.