What Students’ Use of AI Reveals about Academic Advising and Judgement

Generative artificial intelligence (AI) is now widely discussed in higher education in relation to learning, assessment design, and academic integrity. Much of this discussion, however, treats students' use of AI as a set of discrete academic practices, rather than as part of broader decision-making that spans learning and everyday life. This piece argues that students' academic and non-academic uses of AI increasingly shape one another, influencing how they approach uncertainty, manage emotional pressure, and make judgements when learning feels high-stakes. Informed by academic advising and personal tutoring conversations, it shows that students are not using AI solely to generate outputs, but to talk ideas through, test interpretations, and steady their thinking when confidence and academic identity are in play. These practices closely resemble the relational and cognitive work advisers already support and reveal how AI is now being used to sustain the emotional work of learning that underpins sound judgement. A simple practice-based framework is presented describing four overlapping modes of student AI use – instrumental, dialogic, metacognitive, and affective-regulatory – each aligned with established advising functions. The framework highlights how AI is increasingly woven into the reflective and decision-making processes that advisers already support. Rather than positioning AI as a threat to advising, academic integrity or professional judgement, the piece argues that advising conversations can help students recognise how AI shapes their thinking and develop the boundaries and judgement needed to use it well.