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

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 & 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.