When it comes to AI use in the classroom, there is a not-so-clear line between “enough” and “too much”. According to the DInsmore and Fryer [1], the most important part of the learning process is also the part that using AI tends to skip over, the struggle phase. There is an argument to be made that this is evidence AI does not belong in the classroom end-of story, and I do not disagree. As a student, my end goal is not just to get a degree but also to use the information I’ve learned in my endeavors. A degree is something you can put on your resume as proof you did the work and know things that others don’t. AI clearly muddies this process. Once a student has obtained their degree, they can get hired at a job based on those credentials. They are not “preparing” anymore, so the use of AI in the workplace is a much more open discussion. traditionally, whoever gets things done the fastest is the “better” worker but they are both doing the job at equal levels of success. in this case, AI is actively cutting down on wasted time and inefficiencies, it is not sacrificing any level of quality since it is not the one determining the quality.

Works Cited

[1] Dinsmore, Dan L., and Luke K. Fryer. “What Does Current genAI Actually Mean for Student Learning?” Learning and Individual Differences, vol. 125, 2026, article 102834,