Trust determines whether AI strengthens a team's creativity or fuels conflict within it.

The highest-performing groups treat AI output as something to verify, not something to copy.

AI helps most when it combines real-time participation with feedback and reflection.

Co-authored by Rónan Fulton, Alana McCarthy, and Michael Hogan.

Generative artificial intelligence (GenAI) is rapidly becoming part of collaborative learning. As GenAI tools become increasingly capable, discussion often centres on the technology itself: whether it will improve learning or undermine it. Yet this framing overlooks a more fundamental issue. Consider a surgical team. Access to sophisticated instruments does not determine whether an operation is successful. The outcome depends on how well the team communicates, coordinates, and trusts one another while using those tools. AI-supported collaborative learning is no different: Like a scalpel, AI proves its worth only in skilled, trusting hands.

Three recent empirical studies, involving more than 480 learners across higher education, suggest that the effectiveness of AI depends less on what the technology can do than on how people work with it. Together, they point towards an important conclusion: Designing AI for collaborative learning is not simply a technical challenge, but also a psychological one.

Interpersonal trust shapes the value of AI-supported collaboration

Luo and colleagues (2025) surveyed 308 university students working in 66 collaborative groups to investigate how trust, collective efficacy, and task conflict influenced team creativity when generative AI was introduced. Rather than treating collaboration as a single outcome, the study examined the social conditions that determine whether AI benefits group work. Trust was measured through students' perceptions of whether group members could openly discuss difficulties, approach tasks professionally, and rely on one another to fulfill their responsibilities. Task conflict reflected........

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