Academic Use of Generative AI in Higher Education— An Initial Study on Staff Usage and Perspectives from a UK University

<p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d10428e118">This research investigates faculty perceptions and adoption patterns of Generative Artificial Intelligence (GenAI) across four academic disciplines at a UK university. Drawing on survey data from 30 faculty members (Computing n=7, Engineering n=8, Digital Arts &amp; Animation n=11, Games n=4) collected between November 2025 and January 2026, we reveal profound disciplinary polarisation. Computing shows highest adoption (71.4% regular users), while Digital Arts demonstrates strongest resistance (54.5% never users). Despite recognizing GenAI's effectiveness (M=3.45/5), faculty express significant trust deficits (M=2.45/5) and ethical concerns (77.4%), which extend beyond academic integrity to encompass creativity erosion, professional displacement, and environmental impact. Using Wenger's (1998) communities of practice framework and Biesta's (2015) educational purposes triad, we theorise that disciplinary resistance reflects clashes between professional identity, pedagogical values, and economic realities. Our findings seem to challenge universal AI integration approaches, advocating instead for discipline-responsive policies that respect epistemic diversity while addressing legitimate ethical concerns. The results could contribute to emerging scholarship on AI in education by demonstrating how disciplinary cultures mediate technology adoption in ways that transcend simple techno-optimism/pessimism binaries. There are clear implications for assessment redesign, proportionate academic‑integrity practice, capability building, inclusion, and evaluation.