Purpose
The increasing integration of artificial intelligence (AI) into medical education has sparked both excitement and concern, especially in the domain of student assessment. While its potential for automation and personalization is widely discussed, limited research explores how medical educators perceive this shift. This study aimed to examine the expectations, apprehensions, and ethical reflections of medical educators regarding the use of AI in assessment.

Methods
This qualitative study involved 20 medical educators teaching in undergraduate medical programs across India. Participants were purposively sampled from both clinical and preclinical departments with at least five years of experience in assessment design or evaluation. Semi-structured online interviews were conducted between March and May 2025, lasting 45–60 minutes each. Sessions were audio-recorded, transcribed verbatim, and anonymized. Data were analyzed using reflexive thematic analysis within a constructivist paradigm. Trustworthiness was enhanced through iterative coding, peer debriefing, and reflective memoing.

Results
Three themes emerged from the analysis. First, a sense of uncertainty and lack of trust in artificial intelligence systems was linked to their perceived opacity and risk of bias. Second, educators expressed fears of professional displacement, where human judgment and mentorship might be devalued. Third, while participants recognized the benefits of artificial intelligence in formative feedback and efficiency, they emphasized the need for ethical oversight, human involvement, and contextual adaptation.

Conclusion
Educators view artificial intelligence in assessment as a double edged development. Their concerns reflect not resistance to technology but a call for thoughtful integration. Responsible implementation must involve transparent design, capacity building, and frameworks that respect the educator’s role in shaping student learning and professional identity.