Navigating Disruption: A Transformative Learning Theory Examination of Faculty Perceptions of Generative Artificial Intelligence in Academic Practices

Generative artificial intelligence (GenAI) tools such as ChatGPT have rapidly entered higher education, challenging longstanding norms around authorship, assessment, and disciplinary expertise. While early GenAI scholarship has largely emphasized student outcomes, adoption trends, and academic integrity, comparatively little empirical work has examined how faculty and staff make sense of this disruption over time. Guided by Transformative Learning Theory (TLT) as an interpretive lens for faculty discourse, this qualitative study examines how educators interpret GenAI as a “disorienting dilemma” and how patterns in faculty discourse differ across two cross-sectional cohorts during the first year of widespread adoption. We analyzed open-ended survey responses to the question, “How do you think AI tools like ChatGPT will impact the future of your discipline?” collected at a large U.S. R1 Hispanic-serving public research university. Two cohorts were examined: an early-adoption dataset gathered in 2023 (n = 104) and a follow-up dataset collected in 2024 (n = 313). Using Braun and Clarke’s reflexive thematic analysis procedures, we identified persistent themes and qualitative differences in how participants described GenAI-related concerns and opportunities. No educator-navigation theme differed significantly in proportional prevalence between cohorts. Accordingly, interpretations of cross-cohort differences rest on variations in thematic framing, tone, and illustrative detail rather than on statistically demonstrated temporal change. The 2023 responses more often foregrounded academic-integrity concerns and defensive assessment redesign, whereas the 2024 responses included more concrete descriptions of pedagogical experimentation and potential uses of GenAI to support faculty productivity and professional practice. Across both years, persistent anxieties regarding student dependency, erosion of foundational skills, and the potential dehumanization and homogenization of academic discourse remained salient. These results highlight faculty as active agents engaged in reflection and adaptation and show how aggregate patterns of faculty sensemaking are compatible with early processes described by Transformative Learning Theory. TLT is used here as an interpretive lens for cohort-level faculty discourse, not as evidence that individual instructors underwent internal perspective transformation. This underscores the need for institutionally supported, human-centered approaches to GenAI integration, including policy clarity, sustained faculty development, and communities of practice that enable ethical, reflective experimentation.