Faculty Burnout at the Intersection of Artificial Intelligence Adoption and Academic Integrity Measures: A Thematic Analysis in Higher Education

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Abstract
The rapid integration of Artificial Intelligence (AI) in higher education has changed teaching and assessment practices and has introduced new risks for faculty well-being. This study, conducted in 10 public and private universities in Dhaka, Bangladesh, examines faculty burnout associated with AI adoption and academic integrity enforcement. Semi-structured interviews were conducted with 37 full-time faculty members, each with more than 5 years of teaching experience. Reflexive thematic analysis identified 5 domains of burnout: workload intensification through invisible labor, technostress driven by rapid technological change, an investigative burden that moves the faculty role from pedagogy toward surveillance, ethical strain within a policy vacuum, and disruption of professional identity. Participants described AI integration as a structural intensifier of academic labor rather than a labor-saving tool. In the absence of clear governance, faculty members absorbed the cognitive, emotional, and administrative costs of institutional transitions. The findings support the need for written institutional AI policies, formal recognition of assessment redesign labor, fair and reliable misconduct procedures, and sustained professional development so that integrity enforcement does not rest on individual instructors alone. The results carry implications for university governance, national regulatory bodies, and occupational health in academic workplaces.

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