Generative AI Use in Professional Graduate Thesis Writing: Adoption, Perceived Outcomes, and the Role of a Research-Specialized Agent

TL;DR

This study surveys MBA thesis students in Japan, revealing widespread AI use in research writing, perceived benefits, ongoing concerns, and the potential of specialized AI tools like GAMER PAT to improve research workflows.

Contribution

It provides empirical evidence on AI adoption in academic writing, highlighting the importance of research-specific AI tools and the shift towards verification and source management.

Findings

95.2% of students used AI in thesis writing

Students reported improved clarity, structure, and speed

Preferences favored research-specialized AI for inquiry and organization

Abstract

This paper reports a survey of generative AI use among 83 MBA thesis students in Japan (target population 230; 36.1% response rate), conducted after thesis examiner evaluation. AI use was nearly universal: 95.2% reported at least some use and 77.1% heavy use. Students engaged AI across the full research-writing workflow - literature review, drafting, and consultation when stuck - reporting benefits centered on clearer argument and structure (82.3%), better revision quality (73.4%), and faster writing (70.9%), with a mean perceived quality improvement of 6.27 out of 7. Concerns about output accuracy (75.9%) and citation handling persisted alongside these gains. Among respondents who rated GAMER PAT, a research-specialized agent, against other AI, preferences significantly favored it for inquiry deepening and structural organization (both p < 0.05, exact binomial). A preliminary qualitative analysis of follow-up interviews further reveals active epistemic vigilance strategies and differentiated tool use across thesis phases. The central implication is not adoption itself but a shift in the educational challenge toward verification, source governance, and AI tool design - with GAMER PAT offering preliminary evidence that research-specialized scaffolding matters.