Poster #106 - AI Attitudes Among Emergency Managers: A Two-Year Trend Analysis

• In Event: Saturday Poster Luncheon

Abstract

AI technologies are used increasingly, and in new ways in the public and private sectors. How managers perceive these technologies directly shapes their adoption, and it is particularly critical that public managers adopt AI in a responsible manner, reflecting their obligations to the public. Individual attitudes toward AI are critical antecedents for effective organizational implementation (Misra et al., 2024). However, longitudinal studies tracking AI attitudes in local government remain scarce.

This study addresses this gap by examining whether US emergency managers’ (EMs) general attitudes toward AI (GAAI) changed over two years following ChatGPT's release, and which demographic, behavioral, or jurisdictional factors are associated with this change. Additionally, we also investigated the relationships between EMs’ AI attitudes and their views around the use of AI for managerial information processing and decision-making. We surveyed 72 US-based county level EMs in 2023 and 137 EMs in 2025, comparing results to representative US adult samples (N=302 in 2023; N=502 in 2025). Studying EMs allows us to control for a particular work context while studying an important public sector role with consequences for lives and property.

We find EMs’ overall optimism toward AI increased (higher positive attitudes and lower negative attitudes), while the Prolific sample showed no significant changes (except for those in the Banking, Finance, Insurance industry, who grew more negative). Although EMs remained less optimistic than Prolific samples overall, this gap narrowed over time due to the notable increase in EMs’ positive attitudes toward AI. Changes were consistent across repeat respondents (n=13) and state aggregates (n=20 states), with the proportion of AI optimists increasing notably.

While AI engagement (frequency and duration of AI use) correlates with attitudes in 2025, it did not fully explain EMs’ attitudinal shift. At the jurisdictional level, physical factors (rural/urban location, risk indices) disappeared as predictors, while ideological factors (2024 presidential voting) emerged. Interestingly, bootstrapped EM samples matched with Prolific samples by demographics and recent crisis management experience showed similar attitudinal changes as EMs, suggesting demographics and recent crisis experience drive the optimism shift. In 2025, EMs with higher AI optimism reported: (a) greater information overload and organizational integration challenges; (b) stronger support for AI augmentation with fewer concerns; yet (c) remained cognizant of specific requirements for workplace AI adoption. This suggests general AI optimism translates into more favorable views of AI in managerial decision-making, though practical adoption remains conditional on meeting operational standards.

We observed a meaningful shift toward AI optimism among emergency managers, attributable to demographic factors and recent crisis management experience rather than profession alone. These findings contribute to understanding how AI attitudes evolve in the public sector and highlight the importance of tracking these attitudes. Organizations can use such insights to anticipate workforce needs, prioritize upskilling initiatives, and develop responsible AI adoption policies aligned with technological change.

Reference mentioned: Misra et al. (2024). "Toward a Person-Environment Fit Framework for Artificial Intelligence Implementation in the Public Sector." Government Information Quarterly. doi:10.1016/j.giq.2024.101962.

Authors

• Tuan Pham, Virginia Polytechnic Institute & State University
  Presenting Author

• Shalini Misra, Virginia Polytechnic Institute & State University
  Non-Presenting Co-Author

• Benjamin Katz, Virginia Polytechnic Institute & State University
  Non-Presenting Co-Author

• Norhan Abdelgawad, Virginia Polytechnic Institute & State University
  Non-Presenting Co-Author

• Patrick Roberts, Virginia Polytechnic Institute & State University
  Non-Presenting Co-Author

• Muhammad Awfa Islam, Virginia Polytechnic Institute & State University
  Non-Presenting Co-Author