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This study investigates the effect of a specialized generative AI system—developed and tested as part of a Proof of Concept (PoC)—on the speed with which public officials in a central government agency draft written responses to citizen inquiries. Using a quasi-experimental design with difference-in-differences analysis and propensity score matching, 80 civil servants were divided into a treatment group participating in the proof of concept (adopting AI-based drafting) and a control group that maintained existing practices. The difference-in-differences results of this study indicate a significant reduction in document preparation time for the AI group, with an observed difference-indifferences estimate of 3.81 min and a regression-adjusted estimate of 4.05 min faster than the control group. Notably, new employees benefited the most, suggesting that generative AI can help close the skill gap by expediting their learning curve. These findings highlight that generative AI can improve task-level efficiency in document drafting. Broader organizational or effectiveness-related outcomes were not assessed in this study. Policy implications include the importance of tailored training and support for different experience levels, as well as considerations for standardization, quality control, and ethical safeguards. Overall, this study provides empirical evidence that generative AI can transform administrative workflows in government agencies, offering actionable insights for policymakers seeking to enhance productivity and service quality in the digital era.
Eungjoon Kim (Thu,) studied this question.