From Hours to Minutes: The Impact of Generative AI on Work Turnaround Time and Productivity

The rapid adoption of Generative AI in workplaces has sparked discussions on its impact on efficiency, particularly in reducing task turnaround times. Previous studies highlight Gen AI's potential to streamline workflows by automating manual, repetitive tasks. However, there is limited empirical evidence on how much time is actually saved across different types of tasks and whether these efficiency gains continue over time. This study aims to quantify Gen AI-driven reductions in task turnaround times and examine the long-term trend of efficiency improvements. Using secondary datasets comprising ten workplace task categories, a comparative analysis of ‘without Gen AI aid’ task durations and ‘with Gen AI aid’ task durations was conducted. The analysis was performed using Excel-based tables and charts, and a linear regression model to forecast future AI-driven efficiency gains. The findings confirm that Generative AI significantly reduces task times, with an average efficiency gain of 80% to 90% across various functions. However, the impact is task-dependent, with more significant reductions in routine, standalone tasks and diminishing returns observed in complex, multi-step projects over time. These insights suggest that while Gen AI continues to enhance productivity, its future improvements may shift from time savings to quality enhancement and cognitive support. The study highlights the need for further research on Gen AI’s broader role in workplace efficiency beyond just speed improvements.