Generative AI and sustainable policy implementation: Expanding UTAUT2 to examine sustainable policy alignment and ambiguity impact on street-level bureaucrats’ discretion

This study investigates the adoption of Generative Artificial Intelligence (GenAI) by street-level bureaucrats (SLBs) and examines its impact on their discretion in implementing sustainable policies in Iraq and Oman. By extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to include sustainable policy alignment and policy ambiguity as moderating factors, the research explores how these policy elements influence the relationship between GenAI adoption and SLBs’ discretionary actions. Data was collected from 489 SLBs and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings demonstrate that performance expectancy, effort expectancy, hedonic motivation, and habit significantly drive the continuous intention to use GenAI. In contrast, social influence and facilitating conditions do not have a significant effect. Furthermore, the continuous intention to use GenAI positively influences SLBs’ discretion in policy implementation, with sustainable policy alignment strengthening this relationship and diminishing policy ambiguity. A multi-group analysis reveals notable differences between Iraq and Oman. In Oman, all UTAUT2 variables are significant, reflecting a supportive and stable governance environment. In contrast, in Iraq, individual perceptions dominate, likely due to higher policy ambiguity and weaker institutional support. These results underscore the importance of emphasizing GenAI’s practical benefits and ease of use and advocate for developing clear, supportive policies that empower SLBs. This study extends the theoretical foundations of UTAUT2 in the public sector, offering practical insights for policymakers and organizations seeking to leverage GenAI for enhanced sustainability outcomes.