When AI Use Is Not a Choice: Qualitative Examination of Voluntary and Involuntary Engagement Among College Students

Background and Objective:

The rapid growth of generative AI technologies has transformed how college students engage with learning, daily activities, and career preparation. Students increasingly use AI for personalized learning, creative pursuits, and career development. However, prior research has relied largely on quantitative surveys, limiting understanding of the contextual and experiential dimensions of AI use. In particular, students’ motivations for using AI remain underexplored. This study examines: (1) how college students use AI across daily life, academic work, and career-related domains; (2) factors shaping voluntary and involuntary AI use; and (3) how these contexts influence continued engagement.

Methods:

A qualitative study using focus group interviews was conducted with 24 social science students at a public university in U.S. South. Following informed consent, data were collected through eight virtual semi-structured focus groups, each lasting approximately 60 minutes and facilitated by trained faculty interviewers. Audio-recorded data were transcribed by a professional transcription service. Data collection continued until thematic saturation was reached. Using thematic analysis (Creswell and Poth, 2016), two independent research teams conducted initial coding, followed by iterative comparison, cross-validation, and consensus-based refinement to develop the final themes and subthemes.

Results:

We identified three main domains of students’ AI use—daily life, academic work, and career preparation—and found a wide range of AI use practices across these domains. In each domain, students’ use of AI ranged from voluntary to involuntary. Peer modeling and faculty encouragement serving as a positive signal all promoted students’ voluntary AI use. Involuntary use, on the other hand, was driven by conditions such as, peer pressure that made refusing to use AI feel like falling behind; and workplace expectations that require employees to demonstrate effective AI use. For most participants, observing peers’ creative uses of AI influenced their voluntarily use, and the familiarity of AI’s functions developed through that process further promoted future AI use. In addition, faculty’s encouragement of AI use served as a key entry point for students to begin exploring AI. In contrast, many students identified inconsistent AI policies among faculty and within the university as a major factor that heightened anxiety about academic dishonesty, thereby discouraging engagement with AI.

Conclusions and Implications: In daily, academic, and professional domains, college students utilized AI as a co-pilot. While some students employed AI for its convenience, efficiency, low cost, and responsiveness, other students used it due to peer influence, instructor advocacy, and the pervasive presence of AI in digital tools. Thus, students need support in both accessing AI and developing the capacity to use it intentionally and appropriately across life domains. From an empirical social work perspective, students’ choices around AI use should be understood not simply as individual choices, but as behaviors shaped by social, institutional, and technological ordering. The findings also raise concerns about inequity related to students’ AI literacy, familiarity, and access to technology. Finally, the combination of institutional support, policy ambiguity, and pressure in students’ accounts implies the need for clearer ethical and educational direction around AI use in social work education.