Obi, Chinedu Douglas (2026) UNIVERSITY STUDENTS’ PERCEPTIONS OF GENERATIVE AI’S ROLE IN HYBRID LEADERSHIP AND EMPLOYEE ENGAGEMENT. Masters thesis, York St John University.

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Abstract

Generative AI has spread rapidly through universities, and hybrid working has become established practice across UK organisations. The two developments are usually studied apart, and management scholarship has given little attention to where they meet. This dissertation examines that intersection through the perceptions of postgraduate and advanced undergraduate students at York St John University’s London Campus concerning the role of generative AI in hybrid leadership and employee engagement. Four research questions organise the inquiry: RQ1 examines the cohort’s familiarity and confidence with generative AI tools; RQ2 asks how they expect it to affect the practice of hybrid leadership; RQ3 examines how they weigh the efficiency it offers against the authentic connection it may cost; and RQ4 asks what governance recommendations follow. The study draws on the Technology Acceptance Model (Davis, 1989; Venkatesh and Davis, 2000) and Self-Determination Theory (Deci and Ryan, 2000; Ryan and Deci, 2017), adopting a pragmatic paradigm and a convergent parallel mixed-methods design. Forty-two respondents completed the survey, and all figures are reported as absolute counts alongside percentages in Chapter Four. Acceptance is high: respondents rated their confidence with generative AI platforms at a mean of 3.93 out of 5, 40 of the 42 had used ChatGPT, 23 Microsoft Copilot and 17 Google Gemini, and the sample expected generative AI to reduce the administrative burden of hybrid leadership. Alongside this sits a consistent reservation about what is lost when interaction is not face to face — relatedness in Self-Determination Theory terms. That reservation is not diffuse anxiety but a sustained task-boundary logic: respondents readily delegate administrative and analytical work to AI while reserving relational and judgemental work for human leaders. The dissertation reads this as an emerging psychological contract for the next generation of knowledge workers, in which generative AI serves as an administrative co-pilot without displacing the relational core of leadership. Three limitations qualify these conclusions: the single-institution sample is not representative of UK students, the cross-sectional design captures attitudes at one moment in a fast-moving field, and the quantitative sample (n = 42) is too small to support inference. Internal consistency was strong for the perceived-usefulness scale (α = 0.88) but fell below the conventional threshold for the two-item relational-risk scale (α = 0.54), whose items are reported separately. The study makes three contributions: an empirical account of this bifurcated attitude; a task-based boundary model applicable directly to organisational AI policy; and a testable proposition that time spent in hybrid working predicts a bounded and self-aware attitude towards AI better than chronological age.

Item Type:	Thesis (Masters)
Status:	Published
Subjects:	L Education > LF Individual institutions (Europe) > LF14-797 England
School/Department:	London Campus
URI:	https://ray.yorksj.ac.uk/id/eprint/15871

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