Relativism in Workplace Collaborations Involving Humans and AI

Artificial intelligence (AI) is rapidly transforming workplace dynamics, reshaping how employees collaborate and make decisions. While AI systems can enhance productivity and manage increasing workloads, they may also disrupt traditional human-to-human collaboration. Prior research underscores this paradox: AI can facilitate teamwork but may also lead to reduced engagement with human colleagues (Marimon et al., 2024). To better understand this tension, the present study introduces relativism—the process by which individuals evaluate AI assistance relative to human collaboration—as a critical but underexplored factor in shaping collaborative dynamics (Zhang, 2013). This study investigates how human-AI collaboration influences human-human collaboration, with a focus on the mediating role of engagement disposition—a construct reflecting how employees cognitively and affectively weigh AI involvement against human interaction. It further explores how this relationship is moderated by job complexity. In highly complex roles, AI assistance may appear more efficient than human collaboration, thereby reducing interpersonal engagement (Tortorella et al., 2024). Individual personality traits also influence AI preferences: extroverted employees tend to seek human interaction, whereas introverted individuals may favor AI-driven solutions, turning to AI for problem-solving over interpersonal exchange (Gass, 2023). Guided by Social Exchange Theory (SET), which posits that individuals evaluate interactions based on perceived costs and benefits (Cook et al., 2013), this research positions relativism as a central mechanism in the evolving nature of workplace collaboration. When AI is perceived as more beneficial or less effortful than human interaction, reliance on human colleagues may decline. Hypothesized relationships will be tested with organizational survey data. By highlighting relativism as a key driver of collaboration patterns, this research addresses a critical gap in the literature and offers practical insights for organizations aiming to balance technological advancement with human-centered work design.