A Study of Factors Influencing the Adoption of Artificial Intelligence in Crisis Management

Abstract

This paper presents a study on the Factors Influencing the Adoption of Artificial Intelligence (AI) in Crisis Management. The research identifies 28 AI usage factors categorized into seven groups: Large-Scale Machine Learning, Deep Learning, Reinforcement Learning, Robotics, Computer Vision, Natural Language Processing, and Internet of Things. The study conducted a questionnaire survey among 281 employees at the UAE National Crisis and Emergency Management Authority, using purposive sampling to assess their opinions regarding the impact of these usage factors on the adoption of AI in crisis management. The collected data underwent descriptive analysis to determine the ranking of AI usage factors within each of the seven groups. In terms of group rankings, Robotic emerged as the top-ranking factor, followed by Reinforcement Learning. Large-Scale Machine Learning occupied the next position, succeeded by Natural Language Processing, Deep Learning, Internet of Things, and Computer Vision, which held the lowest rank. Furthermore, when examining the correlation between these usage factor groups, it was discovered that most of them exhibited strong positive correlations, with correlation coefficients ranging from 0.634 to 0.934. This indicates that changes in one variable are associated with predictable changes in another variable. While this information can be instrumental in understanding relationships and making predictions, it does not establish a causal relationship.