AI in college admissions: why real work now matters more than polished writing
- Anushka Goyal
- 6 days ago
- 7 min read
AI in college admissions is no longer a writing shortcut; it is a sorting signal. Students who use AI to think faster, research better, and build real projects can stand out. Students who use it to fabricate polish risk sounding generic, because admissions readers are now trained to look for authenticity and proof of work.
In a recent webinar at BetterMind Labs, Harvard alumnus and college admissions consultant John Gardezi framed AI as a force multiplier. That is the right lens. AI should strengthen a student’s judgment, not replace it. The strongest applications increasingly show contribution, initiative, and evidence of real execution, not just well-written claims.
About the Expert Featured in This Discussion
The insights in this article come from a recent webinar led by John Gardezi, a Harvard graduate (Class of 2009), former Harvard interviewer, and college admissions consultant with more than 15 years of experience. He earned a perfect SAT score, has advised students admitted to highly selective universities, and specializes in admissions strategy for STEM, business, and pre-med applicants.
Before launching his admissions practice, Gardezi worked as a high school teacher and management consultant at EY and Cognizant. Today, he focuses on helping students navigate the rapidly changing admissions environment, with particular expertise in the role of AI in college admissions, essays, and extracurricular development.
Check out John Gardezi and Edvanced Learning here.
Table of Contents
What is actually changing in college admissions?
Colleges are moving from evaluating only polished outputs to checking whether a student’s work is real, consistent, and verifiable. AI has made it easier to generate strong-sounding essays, so admissions offices are paying more attention to authenticity, grades, activities, and evidence that a student actually built something meaningful.
That shift is visible in the continued stability of Common App essay prompts for 2024-2025 and 2025-2026, which still reward personal reflection rather than formulaic polish. It is also visible in fraud policies and academic integrity guidance that remind students and counselors that transparency matters more when tools can imitate voice so easily.
According to John, the fundamental admissions question is changing. Historically, colleges focused on what a student accomplished. As AI makes it easier to produce polished applications, admissions officers are increasingly evaluating what a student contributed and what they are capable of creating in the future. As Gardezi explained,
"that's where the authentic initiative, the real impact, the vulnerability, the growth over time, that's the new question."
In other words, selective universities are looking beyond achievements and examining evidence of meaningful engagement, leadership, and long-term development.
How should students use AI in essays without losing authenticity?
The safest use of AI in essays is support, not authorship. Harvard’s guidance emphasizes responsible experimentation, privacy, and academic integrity, while Princeton requires disclosure when AI is used in academic work. That combination points to a clear rule: AI can help organize thought, but the student must supply the lived experience and final voice. (huit.harvard.edu)
A practical way to think about it is simple. Use AI in the green zone for brainstorming, outlining, and revision feedback. Treat large rewrites with caution, because they can flatten voice. Never let AI invent experiences, emotional depth, or accomplishments. Specificity, not polish, is what makes an essay believable. (huit.harvard.edu)
A strong essay process usually looks like this:
Student writes the raw story first.
AI helps test structure or clarity.
The student revises for honesty, detail, and tone.
A trusted mentor checks whether the final draft still sounds like the student.
That kind of workflow preserves authenticity while still making AI useful. (huit.harvard.edu)
Why are real projects becoming the strongest signal?
Because AI can help produce content quickly, colleges will trust demonstrated work more than claims. ACT’s 2026 issue brief found that 70% of students think AI gives some applicants an unfair advantage, and 69% believe those users have a significant edge. That perception alone pushes admissions toward proof of work, portfolios, and verified outcomes.
For students, this means the best strategy is to build something that can be seen, tested, and explained. GitHub repositories, personal websites, competition entries, research artifacts, and public-facing projects all help convert interest into evidence. A mentored, project-based structure is especially strong because it forces students to define a problem, build a solution, and explain tradeoffs like an engineer, not a content generator.
Gardezi emphasized that future admissions decisions will place greater weight on measurable outcomes rather than activity participation alone. Students will increasingly need to demonstrate what changed because of their work.
As he noted, "the impact that you're making will matter even more in the future."
This includes concrete evidence such as research outcomes, software applications, nonprofit initiatives, published work, competition results, or community contributions.
He further highlighted the importance of "community impact, you know, the people you've served, the funds you raised, the programs you've built, etc."
Those outcomes provide admissions readers with evidence that a student can translate ideas into action.
What human skills still matter when AI can draft almost anything?
Human skills matter more, not less, when AI becomes easier to use. Judgment, leadership, teamwork, empathy, and communication are the traits colleges still need to trust, because they predict whether a student can contribute in a community, solve ambiguous problems, and build with others over time.
The ACT brief also shows why grades still matter, even as AI complicates how people interpret them. Students rated grades as the most important admissions indicator, but they also worried AI could distort performance. That is why the strongest students are not trying to look perfect. They are trying to look capable, self-aware, and real.
For families choosing a major, the safest path is not to chase what AI can do fastest. It is to pursue fields where human reasoning stays central.
Case Study: How Structured AI Projects Create Demonstrable Impact
As AI makes it easier to produce polished applications, colleges are increasingly looking for evidence that a student can apply knowledge to solve real problems.
According to John Gardezi,
"the impact that you're making will matter even more in the future."
That impact is often best demonstrated through substantive projects rather than descriptions alone.
A strong example is Alexie Manuel, a BetterMind Labs student who combined his interests in artificial intelligence and biotechnology to develop ChiralAI, a project focused on one of the more challenging problems in modern chemical manufacturing.
Chiral molecules play an essential role in pharmaceuticals, biotechnology, and advanced materials, yet many are difficult and expensive to produce.
Alexie built an AI-powered system that identifies chiral molecules that biology can potentially produce and developed a Feasibility Filter to predict viable microbial production routes.
The project uses machine learning to explore biosynthetic pathways for hard-to-manufacture chiral compounds, helping researchers evaluate whether biological production may be feasible before investing in costly experimentation.
What makes this project compelling is not just the technical sophistication.
Alexie had to understand a complex scientific problem, analyze research, work with biological data, develop predictive models, and communicate the practical significance of his findings. The result was a tangible piece of work that demonstrated initiative, intellectual curiosity, and the ability to apply AI to a real-world challenge.
Projects like ChiralAI exemplify the type of evidence admissions offices increasingly value. Rather than simply stating an interest in STEM, students can point to research, code, models, and outcomes that demonstrate their capabilities.
This approach helped Alexie build a distinctive academic profile and ultimately gain admission to Cornell University.
This reflects the broader philosophy at BetterMind Labs. Students are not taught to use AI as a shortcut. They are guided through a structured process of identifying meaningful problems, conducting research, building solutions, and creating measurable outcomes. In an admissions environment increasingly focused on authenticity and demonstrated contribution, projects like ChiralAI provide exactly the kind of verifiable proof of work that colleges trust most.
FAQs
Is AI bad for college admissions?
No, but careless use is. AI helps when it supports thinking, research, and revision, yet it hurts when it replaces the student’s voice. Admissions readers care less about perfect polish and more about whether the work feels real, specific, and consistent.
Should students use AI for essays?
Yes, in limited ways. AI is useful for brainstorming, outlining, and feedback, but the student should write the core narrative and final draft. That keeps the essay authentic and avoids the flat, generic tone that admissions officers increasingly notice.
Why does mentorship matter so much?
Because AI can generate options, but mentors help students choose the right problem and shape the final story. Structured mentorship turns scattered effort into a coherent project, which is far more valuable than chasing random activities or copying online templates.
Do mentored projects matter more than certificates?
Usually yes. Certificates show exposure, but projects show judgment, persistence, and execution. A mentored project also gives a student something concrete to discuss in essays, interviews, and activity descriptions, which is exactly what selective admissions rewards.
Which AI tools are most useful for students?
The best tools depend on the task. Students can use AI for brainstorming, research summaries, tutoring support, and coding assistance, but they should always verify facts and keep ownership of the work. The goal is to become a better thinker, not a passive user.
What should parents look for in an AI program?
Look for structure, mentorship, and a final project that can be shown and explained. If a program only offers prompts or certificates, it will usually be weaker than one that teaches students how to build, document, and communicate real work.
Conclusion
Traditional metrics still matter, but they are no longer enough on their own. In an admissions process shaped by AI, the students who stand out will be the ones who can prove initiative, explain their thinking, and show tangible work that a reader can trust. That is why a structured, mentored, project-based model is becoming the clearest path forward.
The students who thrive in an AI-driven admissions environment will not be those who use AI to appear impressive.
They will be the students who use AI to create genuine impact, demonstrate initiative, and produce work that can be independently verified. As John Gardezi emphasized throughout the webinar, authentic growth, measurable outcomes, and real contribution are becoming the signals colleges trust most.
That is also why BetterMind Labs makes sense as the solution. It gives students a disciplined way to turn AI into output, not shortcuts, and to build the kind of portfolio colleges can evaluate with confidence.
Explore the BetterMind Labs AI program for High School Students and see how a real project-based pathway can strengthen both skills and admissions outcomes.
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