Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
With the rapid development of artificial intelligence (AI) technologies, many organizations have adopted AI to collect data on worker behavior and provide feedback to workers based on such data (for simplicity, we call such tools as AI supervisors). In this study we explore how workers’ productivity is shaped by AI supervisors. We design and implement a large-scale randomized field experiment to quantify the economic impact of an AI supervisor on sales workers’ productivity and distinguish its effect on work effectiveness vs. work efficiency. Our results show that the AI supervisor positively influenced bottom-ranked sales workers’ productivity but had a negative impact on top-ranked workers’ productivity. We further seek to understand the mechanisms through which AI feedback influenced sales workers: Bottom-ranked workers’ productivity gain was driven by improvement in both selling effectiveness and customer engagement efficiency, whereas top-ranked workers’ productivity loss was largely driven by their reduction in customer engagement efficiency.
Recommended Citation
Liu, Haoyuan; Wen, Wen; Agarwal, Ashish; and Whinston, Andrew, "The Implications of Artificial Intelligence Feedback for Worker Productivity" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 4.
https://aisel.aisnet.org/hicss-57/da/emerging_markets/4
The Implications of Artificial Intelligence Feedback for Worker Productivity
Hilton Hawaiian Village, Honolulu, Hawaii
With the rapid development of artificial intelligence (AI) technologies, many organizations have adopted AI to collect data on worker behavior and provide feedback to workers based on such data (for simplicity, we call such tools as AI supervisors). In this study we explore how workers’ productivity is shaped by AI supervisors. We design and implement a large-scale randomized field experiment to quantify the economic impact of an AI supervisor on sales workers’ productivity and distinguish its effect on work effectiveness vs. work efficiency. Our results show that the AI supervisor positively influenced bottom-ranked sales workers’ productivity but had a negative impact on top-ranked workers’ productivity. We further seek to understand the mechanisms through which AI feedback influenced sales workers: Bottom-ranked workers’ productivity gain was driven by improvement in both selling effectiveness and customer engagement efficiency, whereas top-ranked workers’ productivity loss was largely driven by their reduction in customer engagement efficiency.
https://aisel.aisnet.org/hicss-57/da/emerging_markets/4