A Media Richness Theory-Based Analysis of Students' Communication Experience in AI-Assisted Consultation - Mirawati, Ira; Rahmawan, Detta; Sharipudin, Mohamad-Noor Salehhuddin (Mediator: Jurnal Komunikasi, 2025)
Recent advances in artificial intelligence (AI) have expanded students' consultation options beyond traditional sources such as parents, peers, and counselors. This study examines the emerging practice of AI-assisted consultation among Indonesian university students, employing Media Richness Theory (MRT) as an analytical framework to evaluate perceived media richness. A quantitative survey was administered to 553 students who had previously utilized AI for consultation purposes. Results indicate that AI is generally perceived as a “rich” medium, with an overall score of 3.78. In terms of MRT dimensions, AI scored highly in ambiguity reduction (4.02), immediacy of feedback (4.16), cue multiplicity (3.84), and message personalization (3.91). However, comparisons with conventional consultation methods (3.43) and the perceived long-term impact of AI-based interactions (3.60) were rated at a moderate level. These findings suggest that while AI demonstrates notable potential in delivering rapid, tailored, and multifaceted responses, its effectiveness remains limited when assessed against traditional human counseling, particularly regarding sustained outcomes. Consequently, AI should be positioned as a complementary tool rather than a substitute for human counselors. Enhancing AI’s capacity to produce enduring psychological and developmental support will be essential to fully leverage its role in educational and psychosocial consultation contexts.