Prompt & Circumstance: Navigating AI Literacy in Higher Education
Part 1: Mapping the Campus Baseline
AI is rapidly changing higher education – changing how students learn and how educators teach. The arrival of AI in the collegiate world is a permanent reality. Therefore, it’s vital for these institutions to ensure their students have the understanding and wisdom necessary to use these applications.
Caption: College students sitting in the library, doing homework with the assistance of AI-powered tools.
What the Data Tells Us
A 2025 study from Campbell Academic Technology Services found that 86% of college students and 61% of faculty use AI in academic contexts. Students turn to these tools when searching for information, drafting papers, and breaking down complex information. Meanwhile, faculty commonly use AI for curriculum design, automation of administrative tasks, and personalized learning.
Though AI use is increasingly prevalent in higher education, particularly among students, there are still concerns about bias, inaccuracy, and ethical implications. A 2025 Chegg study found that 53% of students who used generative AI in their studies were concerned about incorrect or inaccurate information. Students in this survey also reported concerns around data privacy and AI’s potential to impair critical thinking skills. Similarly, in a 2024 study by Ellucian, faculty believed that accuracy and ethical implications around AI use in higher education were the greatest concerns, with 49% reporting concerns about bias in AI models and 59% concerned about data security and privacy.
Both high usage rates and ongoing ethical concerns point to the importance of fostering AI literacy in higher education spaces, a need only further emphasized by existing competency data. Digital Education Council’s 2024 Global AI Student Survey found that over half (58%) of college students felt that they did not have sufficient AI knowledge and skills and nearly half (48%) did not feel prepared to actively participate in an AI-powered workplace post-graduation. Similarly, 40% of faculty reported only beginning their AI journey, with a mere 17% reporting an advanced or expert level of AI literacy.
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All of this data points to a need for clear, evidence-based AI literacy training in higher education spaces. This will ensure that students and faculty alike are equipped with the skills to utilize AI appropriately, examine outputs for bias and inaccuracy, protect their personal information, and strengthen their critical thinking. But what does this look like in practice? In Part 2, we’ll explore real-world examples to see how colleges and universities are successfully launching AI literacy programs on their campus and in their communities.
