Generative AI: reconfiguring supervision and doctoral research

Checked 30 Sept 2026. Open license (CC-BY, CC-BY-SA, CC0, public domain): full text indexed and used in synthesis.

The uptake of generative artificial intelligence (GenAI) tools has implications for doctoral research and academic publication practices within both construction management and the wider academic context. Unless these implications are understood, GenAI tools have the potential to disrupt traditional relationships between doctoral researchers and their academic supervisors. Rather than exploring the technical competence and reach of GenAI tools, this study explores the nature of these challenges. GenAI is explored from both supervisor and doctoral perspectives for how its integration into doctoral research processes might shift relationships and affect practice. Informed by structuration theory, the research uses mixed methods to map shifts in agency and structure resulting from the adoption of GenAI tools. Findings highlight that the often-unacknowledged use of GenAI in doctoral research can confer undue agency on the technology that disrupts traditional relationships in an unacknowledged way. The rapid but often unacknowledged uptake of GenAI within doctoral research comes with a lack of consideration of the emotional support ascribed by students to the technology. It is concluded that GenAI tools should be openly incorporated into research and practice in a transparent, integrated approach. Practice relevance This research has relevance to the academic community both within the built environment disciplines and more general pedagogical implications. The identification of concerns over the reach and rapidity of GenAI adoption exposes potential changes to relationships and practices. Academics will be able to understand the shifts in relationships between stakeholders and the possible ramifications. The research exposes an unacknowledged proliferation of GenAI use in doctoral research and its underlying role in providing surrogate emotional support to doctoral students. By giving voice to stakeholders, this research exposes the lack of ethical frameworks around the use of GenAI and the need to consider its open and supported use, and its impact on developing the technical understandings and communication of doctoral researchers. The research uncovers some of the debates, concerns and possibilities that GenAI can bring to doctoral research practice, so that they can be intentionally addressed.

• Across two independent studies of doctoral supervision, hidden GenAI use emerges as the central relational problem: Boyd & Harding 2025 find students "(often covertly) using GenAI tools to support their emotional and discipline specific development," while Lai et al. 2025 trace "conflicting expectations regarding supervisory responsibilities among students, supervisors and peers"—and both conclude that supervision must become transparent and collaborative rather than prohibitive. Trace →
• The emotional reliance on GenAI that Boyd & Harding 2025 document in doctoral supervision—"the emotional support ascribed by students to the technology"—is independently flagged by Zhu et al. 2026 as an unmet design challenge, since "deployment in emotionally sensitive contexts" is among the agent capabilities "not fully captured by existing principles." Trace →

• Supervision and doctoral educationanchor