Name: Lauren Moran

School of Psychology- Ph.D Dissertation Defense Meeting

Date: Tuesday, July 14, 2026

Time: 1:00pm - 3:00pm ET

Location: Virtual (https://teams.microsoft.com/meet/245659493630560?p=9Zl2hnoRCWt96hdVYW) 

Advisor:

Dr. Christopher Wiese (Georgia Tech)

Committee Members:

Dr. Bruce Walker - (Georgia Tech)

Dr. Mengyao Li - (Georgia Tech)

Dr. Scott Moffat - (Georgia Tech)

Dr. Cort Rudolph - (Wayne State University)

Title: Generative AI and Worker Functioning: A Multilevel Examination of the Roles of Approach and Avoidance Crafting  

Abstract: Organizations and individuals are increasingly adopting large language model chatbots (e.g., ChatGPT) for a variety of purposes (Chatterji et al., 2025; OpenAI, 2026; Tully et al., 2025). Thus far, LLM chatbots have been employed by workers to perform many common tasks, such as drafting emails, brainstorming ideas, and automating routine tasks (Brachman et al., 2025). Despite the prevalence and promise of these technologies, we do not know whether their use predicts important individual outcomes such as well-being and organizational citizenship behaviors. Additionally, questions remain as to when and why these relationships between LLM chatbot usage and critical worker outcomes may be present. Drawing from the literature on job crafting, the Job Demands-Resources model, and Conservation of Resources theory, I take a person-centric approach to examining these relationships within-persons. I empirically test the proposed model using a daily diary study of workers from multiple industries. I find that, on a daily basis, LLM use is significantly and positively associated with both approach and avoidance crafting, and that in turn, approach crafting is associated with thriving and interpersonally-focused OCBs. However, these relationships were not present when effects were lagged across days in a supplementary RI-CLPM. These findings will benefit individuals as they seek to navigate decisions surrounding their own chatbot usage at work, as well as organizations that seek to understand whether and how chatbot usage may impact their workforce. Future research can explore whether these relationships are present within-day, with repeated measurements over the course of the day. Future work can also consider how these results differ in populations with less autonomy over their use of AI.