Multi-Level Barriers to Generative AI Adoption Across Disciplines and Professional Roles in Higher Education
Organizations: Warwick Manufacturing Group, The University of Warwick, Coventry CV4 7AL, UK · Department of Politics and International Studies, The University of Warwick, Coventry CV4 7AL, UK · Department of Psychology, The University of Warwick, Coventry CV4 7AL, UK · Birmingham Business School, The University of Birmingham, Birmingham B15 2TT, UK
Abstract
Generative Artificial Intelligence (GenAI) is rapidly reshaping higher education, yet barriers to its adoption across different disciplines and institutional roles remain underexplored. Existing literature frequently attributes adoption barriers to individual-level factors such as perceived usefulness and ease of use. This study instead investigates whether such barriers are structurally produced. Drawing on a multi-method survey analysis of 272 academic and professional services (PSs) staff at a Russell Group university, we examine how disciplinary contexts and institutional roles shape perceived barriers. By integrating multinomial logistic regression (MLR), structural equation modelling (SEM), and semantic clustering of open-ended responses, we move beyond descriptive accounts to provide a multi-level explanation of GenAI adoption. Our findings reveal clear, systematic differences: non-STEM academics primarily report ethical and cultural barriers related to academic integrity, whereas STEM and PSs staff disproportionately emphasize institutional, governance, and infrastructure constraints. We conclude that GenAI adoption barriers are deeply embedded in organizational ecosystems and epistemic norms, suggesting that universities must move beyond generalized training to develop role-specific governance and support frameworks.
Figures & tables
| Question | Options | Note | |
| Independent variables | In which department or unit do you work at the University? | Combo box (dropdown selection plus one line text box) | STEM or non-STEM |
| Which of the following best describes your current role? | Academic; Professional Services | Job Role | |
| Dependent variables | What are the main barriers to using GenAI in your teaching/work? | Lack of institutional guidance or policies (Ins); Concerns about academic integrity and student misuse (E); Limited personal knowledge or training on AI tools (Ind); Lack of time to explore and implement AI solutions (Ind); Ethical concerns about bias, privacy, or surveillance (E); Uncertainty about AI’s effectiveness in improving learning outcomes (Ind); Technical difficulties or lack of institutional support (Ins); Concerns about AI replacing human elements in teaching (E); Resistance from colleagues or institutional culture (C); Lack of funding or access to appropriate AI tools (Ins); Preference for traditional teaching methods (C) | Select three most important. |
| Mediator | How would you describe your current level of GenAI literacy? | Likert scale 1–5, no understanding to expert | Literacy |
| What is your overall view of GenAI in education? | Likert scale 1–5, very negative to very positive | Attitude | |
| I am concerned that GenAI will become a threat to my job in the next 5 years. | Likert scale 1–5, strongly disagree to strongly agree | Job Threat |
| Model | 2 Log Likelihood | LR 2 | df | p |
| Intercept-only | 41.569 | |||
| Final | 33.056 | 8.512 | 3 | 0.037 |
| Outcome Category | B | OR = Exp(B) | p | Notes |
| Ethical | 0.545 | 0.58 | 0.181 | Not significant |
| Individual | 0.857 | 0.424 | 0.035 | non-STEM lower odds than STEM |
| Institutional | 0.952 | 0.386 | 0.024 | non-STEM lower odds than STEM |
| Model | 2 Log Likelihood | LR 2 | df | p |
| Intercept-only | 63.516 | |||
| Final | 33.959 | 29.558 | 3 | <0.001 |
| Outcome Category | B | OR = Exp(B) | p | Notes |
| Ethical | 0.196 | 0.822 | 0.522 | Not significant |
| Individual | 0.502 | 1.653 | 0.101 | Not significant |
| Institutional | 0.788 | 2.198 | 0.016 | PS staff higher odds than academics |
| ID | Size | Description | Representative Phrases |
| B1 | 21 | Opposed to GenAI integration | ‘I will not be integrating GenAI into my teaching’, ‘I do not intend to integrate GenAI’, ‘I am strongly against the integration of GenAI’, ‘No, I don’t plan to integrate AI into my teaching’, ‘I have no desire to embed genAI and support a ban’ |
| B2 | 20 | Copilot-only policy frustration | ‘Copilot is the only authorised tool’, ‘Copilot is inferior to ChatGPT/Claude’, ‘No approval for competitor products’, ‘Shifting guidance on data uploads’, ‘Poor quality and hallucinations’ |
| B3 | 15 | Erodes learning and integrity | ‘Undermines critical thinking and writing’, ‘Students bypass skills for instant gratification’, ‘Makes cheating hard to detect; devalues degrees’, ‘Produces superficially competent but inaccurate work’, ‘Shortcuts before learning underlying skills’ |
| B4 | 14 | Eroding critical thinking | ‘Students becoming too reliant on GenAI’, ‘GenAI obliterating students’ critical thinking skills’, ‘Students skip work trusting AI’, ‘Over-reliance on prompting instead of thinking’, ‘GenAI spreading misinformation as fact’ |
| B5 | 13 | Factual accuracy and reliability | ‘AI isn’t always correct!’, ‘When AI gets it wrong.’, ‘factual accuracy in finance’, ‘still checking the work’, ‘misinterpreted core message’ |
| B6 | 11 | Accuracy and trust concerns | ‘Some staff are mistrustful of it.’, ‘Not being accurate, so always have to check over what the output is.’, ‘It is not personal, and content may end up all sounding the same.’, ‘I don’t trust it to be either ethical or good enough quality.’, ‘Whether the information delivered is factual.’ |
Generative AI in Education
Generative AI in education uses language and multimodal models to support teaching, learning, feedback, assessment, and educational design.
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