A paradox perspective on early AI adoption: understanding temporal and relational tensions

Purpose – Artificial intelligence (AI) has the potential to be a disruptive technology instigating paradigm shifts and significantly impacting both operational and strategic processes while presenting organizations with contradictory demands. This paper aims to explore tensions in the early stages of AI adoption in manufacturing firms. Design/methodology/approach – Drawing on paradox theory and 23 focus groups with 112 white-collar employees, we identify 9 themes categorized into 2 overarching dimensions: (1) temporal tensions between current capabilities and anticipated futures and (2) relational tensions between human and machines. Findings – Temporal tensions unfold along emergent trajectories where progress is uncertain, nonlinear and continuously negotiated. Relational tensions are marked by ethical reflexivity, as employees navigate shifting expectations around trust, control and human identity. Our findings show how these tensions reinforce one another and contribute to organizational hesitation and strategic drift. Research limitations/implications – The study focuses on large multinational manufacturing firms, limiting the generalizability of findings to other industries or small and medium-sized enterprises. Additionally, the study captures only the early stages of AI implementation, necessitating further longitudinal research to examine long-term organizational adaptations. Future research should explore cross-industry comparisons and investigate how different leadership styles influence AI-driven transformations. Practical implications – This research provides actionable insights for managers navigating AI integration. Addressing tensions proactively – through strategic workforce upskilling, clear AI governance frameworks and fostering human-AI collaboration – can mitigate resistance and maximize AI’s benefits. Organizations should embrace paradoxical thinking, leveraging AI to enhance productivity while supporting employees in transitioning to evolving roles. Social implications – The study highlights the societal impact of AI adoption in the workplace, particularly concerning job displacement fears and the evolving human-machine relationship. Managing AI transformation responsibly requires ethical considerations, workforce empowerment and inclusive policies to ensure that AI-driven innovations benefit employees and organizations alike. Originality/value – By conceptualizing AI adoption as a process shaped by interwoven temporal and relational paradoxes, the study offers new insights into the emotional, ethical and structural dimensions of integrating AI into established organizational settings.