Generative AI Can Boost Productivity, but Experienced Workers May Be Left Behind: Study

A recent study from researchers at Stanford University and Massachusetts Institute of Technology has shown that generative AI systems have the potential to significantly boost productivity in the workforce. However, the research also suggests that experienced workers could potentially be left behind as a result of the adoption of these systems.

The study surveyed over 5,000 customer support agents from an unnamed Fortune 500 company and found that those using a generative AI conversation assistant experienced a 14% increase in productivity compared to those who did not use the tool. However, the research suggested that less-experienced and lower-skilled workers saw a disproportionately larger gain in productivity compared to their more skilled counterparts.

The researchers found that the AI assistant provided significant benefits to the company’s least experienced and skilled workers, allowing them to complete work 35% faster with the AI’s assistance. Furthermore, those with just two months of experience were able to perform as efficiently as workers with six months of tenure who did not use the AI. Highly skilled workers initially gained less from using the AI as its recommendations were essentially tips and tricks they had already learned on the job.

The study marks the first of its kind to look at the impact of generative AI on a living workforce, with previous studies focusing on AI’s ability to pass major law and medical licensing exams. The researchers argue that generative AI working alongside humans can have a significant positive impact on the productivity and retention of individual workers, though it also raises questions about how workers should be compensated for the data they provide to AI systems.

The researchers suggest that the real losers of AI assistants in the corporate world are more senior managers rather than new or underperforming employees. The study found that the top-performing workers at the company typically reached solutions twice as quickly as average workers before AI was introduced. However, those disparities start to shrink once the AI assistant gets involved, in part because the AI model itself is trained on a dataset of successful customer service interactions. The top-performing workers might not have seen much meaningful benefit after using the AI, but their expertise funneled through an AI may help other workers catch up to their level. That, in turn, can improve the company’s overall productivity.

The researchers suggest that future organizations may pay high-performing employees even higher wages, as their successful performance could be used by AI to increase the productivity of the entire company. However, the study also notes that high-skill workers see smaller direct benefits in terms of improving their own productivity, despite playing an important role in model development.

Overall, the study’s findings suggest that generative AI systems can have a positive impact on productivity in the workforce. However, they also highlight the potential for experienced workers to be left behind as AI tools are adopted, and raise important questions about how these workers should be compensated for the data they provide to AI systems.