How workers engaged with AI affected what they learned. Cyborgs, who were engaging intensively with AI, acquired new AI skills. Centaurs were upskilled by increasing their current domain expertise. Self-automators, who offloaded tasks more fully to AI, did not gain skills.
“Whether professionals lean into AI as collaborators, treat it as a selective tool, or offload their judgment to it altogether will shape not only the outcomes of today’s projects but also the very contours of expertise, authority, and competitive advantage within their organizations,” the researchers write.
Kellogg said this indicates that leaders should think about making sure employees are both learning new AI skills and strengthening existing skills, “and how they might structure work to make sure that happens, depending on what needs to be accomplished.”
This study builds on earlier research at BCG from Kellogg and colleagues. That paper, in which cyborgs and centaurs were introduced, found that the performance of workers who used AI was mixed, depending on the task at hand.
I tend to interact with generative AI like a centaur. I use it for pretty specific tasks, often in a sort of advisory role. As the researchers point out, though, an individual can act as a cyborg sometimes and a centaur other times. This paper made me think more about the way I’d used AI to help with that tricky sentence and what I’d learned from the process: Did I gain knowledge about using AI to help with my writing? Did I boost my writing expertise? In this case, was I self-automating by letting AI do the work for me? These are questions I’ll now keep in mind.
