9 Best Practices for Admissions in the Era of AI

At Pioneer Academics, we review thousands of applications each year, which is closer in scale to a small liberal arts college than to a summer program. Because our applicants are younger, we often see early signals of trends that later ripple through higher education. Few shifts have been as rapid or consequential as the rise of generative AI.

Tools like ChatGPT are now mainstream. Students use them for everything from grammar fixes to drafting essays, while admissions officers wrestle with how to protect fairness and authenticity. This creates both risk and opportunity.

As Matthew Jaskol, Founder of Pioneer Academics, explains: “Generative AI certainly presents new challenges for admissions, but it also opens up an important opportunity. For a long time, students from well-resourced schools have benefited from structured application support, while others have had little guidance. AI, if used responsibly, can help level a playing field that has never really been equitable.” (M. Jaskol, personal communication, August 2025).

The question, then, is not whether AI belongs in admissions. It already does. The real challenge is how institutions can adapt practices to ensure integrity while also embracing innovation. Drawing on Pioneer’s experience and models from universities worldwide, we outline nine best practices for admissions in the AI era.

1. Set Clear Rules

The first step is clarity. Applicants need to know where the lines are. Without guidance, some will assume all AI use is prohibited while others will assume anything goes. That ambiguity is dangerous for both fairness and enforcement.

Cornell University has taken a simple but strict approach: AI may be used to brainstorm ideas, but drafting and revising must be the student’s own. Caltech allows for light editing and grammar assistance but requires disclosure if applicants used AI tools. Pioneer Academics also sets explicit boundaries: ideation support may be acceptable, but essays and final submissions must be composed independently, with applicants informed that proctored checks may be used if questions arise.

Clarity also signals values. By distinguishing between acceptable support and unacceptable substitution, admissions offices model the responsible use of technology that students will need in college and beyond.

2. Don’t Rely on Detectors Alone

Detection software has become the default response to AI essays. Yet it can be unreliable and often unfair. Studies show that detectors frequently flag non-native speakers at far higher rates, with Stanford research finding up to 61% of TOEFL essays misclassified as AI-generated. False positives create enormous risks in high-stakes admissions decisions.

Vanderbilt University addressed this head-on by instructing staff not to use Turnitin’s AI detector in admissions at all. Instead, they compare drafts, check stylistic consistency, and cross-reference with other application materials. Pioneer Academics also uses detectors such as GPTZero, but only as a secondary lens. Authenticity is judged holistically through interviews, coursework, recommendations, and proctored writing.

What’s clear is that detectors may help flag issues, but they must never stand alone. Layered evidence can help to eliminate false positives.

3. Request Verification

Even with rules in place, institutions need safeguards. Brown University provides a useful model: it permits limited AI proofreading but reserves the right to request a graded paper or follow-up writing sample if doubts arise. This protects integrity without assuming bad faith.

Other schools lean on honor pledges. MIT and Yale ask applicants to certify that their work is their own. While easy to put in place, the effectiveness of pledges is untested. Research on academic honor codes suggests they work best when paired with consistent reinforcement. A pledge may set the tone, but verification options provide teeth when questions arise.

The principle is balance: trust students, but keep a mechanism in reserve.

4. Recalibrate Essays

Personal essays have long been the heart of college applications. But they are uniquely vulnerable to both AI and human coaching. Duke University recently reduced the weight of essays in its review process, recognizing that they no longer reliably reflect student authenticity.

Other systems are redesigning the format. UCAS in the UK will replace the traditional personal statement in 2026 with three structured short-answer sections, making it harder for AI to generate generic narratives. Some U.S. universities now require “anchored” writing samples; that is, graded class papers that provide a baseline of authentic work under normal school conditions.

The upshot is that essays still matter, but they cannot carry the same weight. Anchoring them in real classroom work or shortening their format makes them more trustworthy.

5. Prioritize Process Over Product

Polished outputs are easy to fake. Authentic intellectual journeys are not. That is why process-oriented evaluations are gaining ground.

At Pioneer, one-on-one faculty mentorship allows reviewers to observe how students develop research questions, grapple with challenges, and refine their thinking. The value lies not in the final paper but in the steps along the way. Similarly, Minerva University encourages applicants to submit project-based portfolios that reflect effort over a sustained time period.

Evaluating portfolios, research logs, or multi-stage assignments provides richer evidence of originality than a single polished essay. It also rewards persistence and creativity, qualities harder to replicate with AI.

6. Adopt Real-Time Assessments

Real-time communication is far harder to fake. That’s why many institutions are adding synchronous or proctored components.

Sciences Po has reintroduced timed entrance exams. Bowdoin offers optional live interviews with officers or alumni. Toronto’s Rotman Commerce and Waterloo Engineering use Kira Talent, which delivers timed video and written prompts. Researchers are even piloting AI interview bots.

Pioneer embeds this into its core process. Every applicant completes a 30-minute interview: 20 minutes of oral questioning followed by a 10-minute proctored writing task with screen-sharing and cameras on. This ensures reviewers see authentic thinking in real time. The program is now piloting shared-screen oral questioning, so interviewers can observe reasoning step by step.

Taken together, these models demonstrate that real-time formats, whether oral, written, or hybrid, offer some of the strongest safeguards against AI misuse.

7. Add Checkpoints Later in the Funnel

Not every university can interview tens of thousands of applicants. But real-time checks can be added selectively.

For example, they might be reserved for finalists, borderline cases, or applications that raise red flags. Essays flagged by detectors may trigger closer review, while inconsistencies across materials prompt follow-up questioning.

The key is communication. Applicants should perceive these steps as routine parts of the process, not as accusations of dishonesty. If framed carefully, selective checkpoints can raise confidence in authenticity without overwhelming staff.

8. Center Equity

Access to AI is uneven, but it can help. Students in well-resourced schools already benefit from trained counselors, essay coaches, and premium software. For others, AI may be their only source of feedback. Used responsibly, it can reduce long-standing inequities.

Programs like Education Above All’s Digi-Wise provide AI literacy tools that work even offline in low-resource settings. For applicants in rural or underfunded schools, such tools may offer the first structured guidance on how to plan or refine their writing.

Policies must reflect this nuance. Blanket bans risk cutting off students who stand to gain the most. Instead, admissions offices should define AI’s role as support, not substitution, ensuring it levels rather than widens the playing field.

9. Define AI as Advising, Not Authoring

Perhaps the clearest line is this: AI can guide and advise, but it shouldn’t be used to write.

Admissions offices might permit students to use AI for the kinds of structured guidance and feedback that counselors or advising services already provide, such as brainstorming ideas, suggesting outlines, or flagging unclear grammar. But the essays themselves must remain the applicant’s own voice.

This approach recognizes reality: students will experiment with AI. By framing it as a tool for advising, not authoring, institutions both support equity and protect authenticity.

From Threat to Catalyst

Generative AI presents both challenges and opportunities for college admissions. It undermines long-trusted signals like essays, but it also offers tools that could democratize access to guidance and feedback.

The path forward is not about banning or embracing AI wholesale. It’s about building admissions systems that remain transparent, inclusive, and future-proof, modelling ethical technology use for the very students they seek to serve.