Human Dimensions of AI Research Capacity: A Case Study of Collaboration Styles and Leadership Readiness in Academic Teams

Abstract

We investigate how academic position, research experience, and collaboration style shape leadership pathways in AI research teams. Using a faculty survey (n = 39), we test associations among Position × Experience, Position × Preferred Role, and Preferred Role × Collaboration Style via $\chi^{2}$ with standardized residual heatmaps and Cramér’s V, and we summarize readiness via two indices (LRI, CBP). Results show consistently low leadership readiness and a dominant preference for “balanced” collaboration across roles, with pockets of over-/under-representation that inform targeted mentorship and coordinator opportunities. Unlike our companion paper on skills networks and policy alignment, this study focuses exclusively on human-factor dynamics. We translate findings into actionable interventions-structured leadership rotations, mentored coordinator roles for mid-career staff, and collaboration hygienedesigned to strengthen sustainable, high-functioning AI research ecosystems.

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