While AI cannot fully replicate the rich nature of human interaction, our findings suggest that LLMs could fulfil part of the social role traditionally performed by human teammates. In other words, it might help to motivate staff, as well as making them more effective and efficient. None of this removes the need for business leaders to take care when integrating technologies such as AI. My previous research shows that it is incredibly difficult to identify the limits of generative AI, and therefore to know when to use it, not least because that ‘jagged frontier’ is constantly moving. However, this study challenges the prevailing view that even when AI outperforms humans on a particular task, overall team performance will decline as trust and coordination are eroded. Our results show that generative AI is not simply another automated tool, like a calculator or a spreadsheet. It provides real-time feedback, enhances performance, breaks down silos of professional expertise, and influences how users feel. This dynamic interaction means that generative AI acts less like a search engine or text generator and more like a ‘cybernetic teammate’. It can occupy roles we normally associate with human colleagues. And that could force organisations to rethink both their team structures and their entire approach to collaborative work.
3 . Human input remains key. Many of the workers in our experiment included large quantities of AI-generated content (often in excess of 75 per cent) in their final proposals. This does not necessarily mean that they adopted its suggestions without critically evaluating it. They may have conducted several iterations of prompts – validating the responses using their own expertise and external sources – before incorporating the results into their proposals. There were also workers who did not incorporate any of AI-generated content into their submissions. Instead, they used AI to brainstorm and to refine and validate their own ideas. Those who relied more heavily on AI produced more similar solutions than those who did not. However, these proposals were still more varied than the results we produced when we asked ChatGPT-4 to solve the same
problem iteratively without any human input. This shows that human input remains vital to the process, as humans meaningfully shape and contextualise the suggestions they receive, rather than adopting them wholesale. 4 . Gen AI fulfils social needs. A common concern about new technology is its potential to destabilise workplace routines and reduce human interaction, making work less satisfying. But on the contrary, we found that professionals who used generative AI reported significantly higher levels of positive emotions such as excitement, energy, and enthusiasm. At the same time, they experienced lower levels of anxiety and frustration. These benefits were even more pronounced for professionals working in teams than they were for those who used generative AI individually.
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