A new study led by researchers from the University of Cambridge suggests that artificial intelligence (AI) can serve as an effective creative partner when clear guidance is provided on how humans and AI should develop ideas together. The research, published in Information Systems Research, explores the potential for collaboration between humans and generative AI (GenAI) in creative tasks.
The team found that simply introducing AI into a creative process does not automatically lead to better ideas. Co-author Dr Yeun Joon Kim from Cambridge Judge Business School said, “Adding AI doesn’t automatically lead to better ideas. For human-AI pairs to work together and improve ideas over time, organisations must provide targeted support – such as guidance on how to build on and adapt ideas – to help employees and AI learn how to create more effectively.”
The study redefines ‘augmented learning’ as a shared process where both humans and AI adjust their roles across various stages, such as generating ideas, providing feedback, and refining concepts. According to the researchers, GenAI systems are no longer just tools for information access but act as collaborators capable of actively shaping outcomes.
One example highlighted in the study is Netflix’s approach to scriptwriting. Instead of treating it as a single task, Netflix divides it into stages like idea generation and evaluation. Human writers create initial drafts while AI analyzes character arcs, pacing, and audience trends to help refine stories.
Dr Luna Luan from the University of Queensland explained the motivation behind the research: “We wanted to figure out how people can learn to work with GenAI in a more intentional way, so that human–GenAI co-creation leads to stronger joint results rather than just more content.”
The research involved three linked studies with 160–200 participants each. The first found that creativity did not naturally increase over time for human-AI teams working on social or environmental problems. The second identified different collaboration types—humans proposing ideas, asking AI for suggestions, or jointly refining ideas—and found that only joint refinement improved creativity. However, this approach was rarely adopted spontaneously by participants.
“We were surprised that human-AI pairs did not naturally improve through repeated collaboration,” said Joon. “Despite AI’s generative power, creativity did not increase over time. We found that improvement occurred only when we introduced a deliberate intervention.” He added: “Specifically, instructing participants to engage in idea co-development – focusing on exchanging feedback and refining existing ideas rather than endlessly generating new ideas – was the key.”
The authors suggest GenAI tools should prompt users for feedback exchange and iterative refinement instead of solely producing new content quickly. They emphasize that organizations need structured approaches—such as templates or workflows—to encourage effective collaboration between humans and AI.
They also recommend breaking tasks into stages where humans and AI play distinct roles; for instance, using AI for generating options while humans evaluate or refine them. The researchers caution against assuming technology alone will boost workplace creativity without appropriate training or understanding.
The study was co-authored by Luna Luan (University of Queensland), Yeun Joon Kim (Cambridge Judge Business School), and Jing Zhou (Rice University).
Reference:
Yingyue Luna Luan, Yeun Joon Kim, Jing Zhou. ‘Augmented Learning for Joint Creativity in Human-GenAI Co-Creation.’ Information Systems Research (2025). DOI: 10.1287/isre.2024.0984