Virtual teams, i.e., geographically, temporally, or organisationally dispersed teams that collaborate toward a common goal and communicate and coordinate via information and communication technology (ICT) (Hertel et al., 2005), are increasingly prevalent. However, such teams face persistent challenges, such as information deficits and reduced social cues (Handke et al, 2021). Handke et al.’s (2022) review suggests that team process feedback (i.e., information about how the team collaborates, specifically their action, transition, and interpersonal behaviours; Geister et al., 2006; Marks et al., 2001) can help address these challenges. However, given the dispersed nature of virtual teams, observing team collaboration and providing timely and relevant feedback remains difficult for human supervisors.

Artificial Intelligence (AI) presents a promising alternative, as it can accurately, rapidly, and objectively assess and provide feedback on team processes by analysing team communications in ICT-mediated environments (Kotlyar & Krasman, 2021). Yet, the effectiveness of AI feedback may be constrained by lower acceptance relative to human-delivered feedback. Although prior research suggests that trust in AI can reduce this disparity (Kotlyar & Krasman, 2025), it remains unclear whether AI- versus human-generated differentially influences team processes and performance in virtual teams, and under what conditions these effects emerge. This is concerning, given that virtual teamwork is bound to become even more common in the future.

Our study aims to address this gap by experimentally manipulating the source of process feedback (disclosed as AI or human) given mid-task to virtual teams consisting of students collaborating on a creative design task, assessing the effect on feedback acceptance and subsequent team processes and team performance, and examining whether pre-task trust in AI moderates these relationships. Data will be collected from approximately 50 teams and team performance will be evaluated by external raters using predefined criteria.

This study has practical implications for organisations that are increasingly relying on virtual teams. It will inform decisions about whether AI feedback can be used as an alternative to human feedback, and guide strategies to help ensure its effectiveness and address potential barriers. Insights from the study can also help managers identify potential uses for AI in their organisations. Given the scalability and efficiency of AI, knowing when and how it can be used to provide feedback instead of having to rely on human supervisors to do so, has the potential for cost savings and performance improvements.