Generative AI and the Temporary Upskilling of Knowledge Workers

“Upskilling” often refers to the process by which workers acquire and expand their skills, enabling them to perform different types of work as market demands change. This paper demonstrates that while generative artificial intelligence (GenAI) can act as an “exoskeleton,” enhancing workers’ capabilities while they attempt new skills, these gains are dependent on the continued use of the technology. When the “exoskeleton” is removed, little to no knowledge is retained independently, revealing that the newfound capabilities are temporary and reliant on the external support provided by GenAI. We run a randomized controlled trial on “reskilling” with GenAI by providing Boston Consulting Group (BCG) consultants with access and training in using ChatGPT to solve technical problems. We measure their performance on real data science tasks outside their skill sets, which cannot be independently solved by ChatGPT. Treated workers score 49, 20, and 18 percentage points higher than those in the control group on the three tasks and perform close to the level of real BCG data scientists on two of the three tasks. However, treated workers are no better at answering technical questions without the use of ChatGPT post-experiment, suggesting their demonstrated newfound technical capabilities do not imply knowledge acquisition.