Student Psychological Support in the AI-Driven University: Digital Well-Being, Risk Prevention, and Human-Centred Care

Abstract

The digitalization of society and the rapid development of artificial intelligence are transforming students’ academic, social, and psychological experiences. Digital platforms, online learning environments, social media, AI assistants, learning analytics, and mental health chatbots create new opportunities for psychological support, early identification of distress, personalized guidance, and wider access to help. At the same time, they may intensify loneliness, digital fatigue, social comparison, academic pressure, privacy concerns, overreliance on automated advice, and unequal access to professional care. The objective of this article is to analyse the need for psychological support for students in the context of societal digitalization and AI development and to propose a human-centred model of AI-supported psychological care in higher education. The article applies a qualitative review methodology based on literature synthesis, document analysis, and conceptual modelling. The selection of sources prioritized academic relevance, methodological clarity, recency, citation value, and direct connection with the research topic. The analysis integrates research on student mental health, digital mental health interventions, AI-supported psychological support, chatbot-based care, academic stress, digital well-being, and ethical governance of AI in higher education. The article demonstrates that psychological support for students is becoming a strategic function of universities rather than an auxiliary student service. Statistical evidence shows high levels of depression, anxiety, suicidal ideation, loneliness, and help-seeking among college students. AI can support psychological care through early screening, triage, psychoeducation, self-help tools, personalized recommendations, crisis signposting, and continuous low-threshold support. However, AI-based tools cannot replace professional counselling because they raise risks related to accuracy, emotional safety, privacy, bias, crisis response, and dependence on automated interaction. Universities need integrated psychological support systems that combine professional counselling, peer support, digital mental health services, AI-assisted screening, ethical data governance, academic staff training, and crisis escalation protocols. AI should be used as a supervised support layer, not as a substitute for human psychological care. Future studies should empirically examine student trust in AI-supported mental health tools, compare the effectiveness of hybrid support models, analyse risks for vulnerable student groups, and evaluate long-term psychological outcomes of AI-assisted university care systems.