The New College Experience–How Generative AI Is Changing What It Means to Be a College Student

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Written By Stanford University

April 16, 2026 | By Edward T.

Growing up, college was always pictured to be an incredibly-intense academic environment–multi-chapter readings every night, essays to submit every few weeks, and exams that you were left to find a way to study for. Yet, as generative AI becomes ever more common, I can’t help but feel that my college experience is looking a lot different than it was always imagined to be. 

If you asked me three or four years back what Artificial Intelligence was, I’d probably give you a pretty shallow idea that it’s something that makes computers work faster and process data–and in a blink of an eye, it’s now everywhere: from AI-generated videos on social media, to generative AI models like ChatGPT telling me which pair of running shoes I should go buy. It feels like the latest, coolest buzzword that seemingly every company, advertisement, and news article is striving to incorporate in what feels like the “AI takeover” for a world that prioritizes efficiency and speed. And by no surprise, it's come onto college campuses too–something that became impossible to ignore when my college officially formalized an AI-use policy for courses this year, acknowledging what many of us already knew: AI is no longer on the margins of higher education, but firmly embedded into what learning now looks like.

A campus divided

The policy was an important moment–rising numbers of students are relying on Generative AI models, and for a college experience that’s supposed to challenge us with a level of rigor, it’s an easy way to dodge that for the sake of getting work done fast. Yet the introduction of such a policy also revealed how unevenly AI is received across my campus. Among my professors, I’ve seen a divide into two major sides: some are definitively strict, seeing any use of AI-generated content as a violation of academic integrity and a lack of independent contribution of thought to our work, while others encourage experimentation and affirm that it’s a legitimate tool for getting feedback or ideas. After all, they say, in the real world, you’re free to use generative AI whenever, and it doesn’t make sense to restrict its use only in the classroom. This also comes at a time when governments and schools are beginning to consider what an overreliance of tech in youth looks like, from phone bans in schools to national laws against the use of social media apps. 

It’s an interesting time to be navigating changes in the digital education landscape–something that I grew up hearing was going to be the “next generation” of learning, and encouraged as part of nationwide efforts to modernize classrooms with tablets and laptops, online learning platforms, and an abundance of EdTech startups making their way into classrooms. In some sense, I feel that the use of AI in education is simply a continuation of the use of technology in the classroom–but yet, it also feels decidedly different. 

The cost of efficiency

Before these generative models, there was a lot more of an emphasis on the “production process” of work–outlining, drafting, revising, getting feedback, and polishing. Especially at a liberal arts college, I see a real decline in this sort of work happening amongst my peers–it’s now all about efficiency, If you could get feedback on your essay without having to coordinate times with your professor, or if you could get started on a project right away instead of having to spend hours thinking of a good idea, wouldn’t you use these platforms too? 

That efficiency then affords students time for other things–more time to study for exams, more time to spend with friends, but also more time to “take advantage” of clubs, research, or internships. 

This efficiency, though, can also blur into dependency–by focusing more on an output, it changes what it means to prepare for class. It’s about having the “right” answer, the one that will come up on the exam, or net the points you want from an assignment. And for professors, this conundrum has forced them to reconsider their courses. It no longer makes sense to assign lengthy assignments or readings if a student can ask generative AI to produce answers or summarize chapters–and things that were once staples of a college courseload, like take-home essays, are now viewed with suspicion. In one of my classes, an essay that was historically assigned as a take-home paper was converted into an in-class essay with a one-hour time limit this year, citing the fact many students will simply have a generative model write out an essay for them. I can’t help but feel that replacing a take-home essay with a timed in-class one is very different as a student, but it highlights how AI is reshaping assessment and what is considered “quality work” at the university level.

Finding the line

I, too, have been challenged to navigate the line between the utility of generative AI at school and the quality of my own work–and I’ve found that I need to set definite limits on when and where I’ll use generative AI. For getting a new mnemonic to remember a new topic, or re-explaining a concept that I’m missing details around, I’ll definitely consider turning to generative AI, but I draw a personal line at using it for class assignments, especially those like writing assignments, or doing homework (where that “production process” is vital to my own learning process). 

I can’t say it feels like a switch was flipped with the introduction of (or new regulation of) generative AI in the classroom, but I do find it fascinating to live through a time when universities are balancing a line between innovation, efficiency, and skill-building. There’s no doubt that AI is here to stay, but how it will shape education, and the intellectual growth that a college experience is meant to foster, is something I don’t think we’ll be able to parse out fully for the coming few years.

About the author

Edward (he/him) is a second-year at Harvard with an interest in the systems that youth interact with, and how it affects their physical and mental health. He's particularly interested in the roles of policy and tech in making change, both socially and in public health. Outside of school and GoodforMEdia, you’ll find Edward going on walks around campus, trying his hand at a new dish, or window shopping at antique stores.

 

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