The evolution of trust research in human-AI teams

The integration of AI into organisational work processes has fundamentally altered traditional conceptions of teamwork. As AI systems evolve from passive tools to active teammates, a critical research domain has emerged to examine how trust operates within human-AI collaborative configurations. Contemporary research has identified several factors that are fundamental to the formation and maintenance of trust in human-AI teams. Social dynamics within teams are particularly influential in determining trust. Studies have shown that trust can spread through team networks based on interpersonal influence (Duan et al., 2025; Erengin et al., 2025). When human teammates who are held in high regard endorse AI capabilities, other members demonstrate increased trust; conversely, scepticism propagates similarly. These findings indicate that human resource management practices significantly influence the success of AI integration.

Task design and role clarity are additional critical factors. Evidence suggests that humans exhibit differential trust based on task characteristics, demonstrating higher confidence in the technical capabilities of AI while remaining sceptical of the social dimension of tasks (Duan et al., 2024; Schmutz et al., 2024; Jain et al., 2022). Therefore, organisations must thoughtfully allocate responsibilities, aligning AI capabilities with tasks where the system’s strengths align with human expectations and requirements. Contemporary frameworks emphasise that trust operates simultaneously at the individual, team, and organisational levels and is influenced by psychological, technological, and environmental factors (Ulfert et al., 2023; Janhunen et al., 2024). This multilevel conceptualisation challenges siloed approaches that address trust exclusively through technological modifications or individual training interventions. Effective trust management requires integrating insights from diverse disciplines, including organisational psychology, computer science, and organisational behaviour. However, such integration remains challenging in both research and practice contexts, with scholars often operating within disciplinary boundaries that limit a comprehensive understanding. Similarly, organisations attempting to integrate AI teams struggle to coordinate across functional areas such as technology deployment, human resource management, and operational execution, each of which contributes essential elements to trust formation.

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This article is part of the project “People and Algorithms in Organisations: Competences to Work in the Digital Environment” (DIGIT_People and algorithms), funded by the NAWA – Narodowa Agencja Wymiany Akademickiej (Polish National Agency for Academic Exchange).

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