Adoption of Artificial Intelligence Technologies in Enhancing Dubai Electricity and Water Authority (DEWA) Operational Performance - Alsharji, Abdelrahman Saeed Khamis Saeed; Noh, Hamidun Mohd (Tropical Scientific Journal, 2025)
Objective: This study investigates the impact of Artificial Intelligence (AI) integration on the operational efficiency of the Dubai Electricity and Water Authority (DEWA), focusing on five specific AI technologies: AI Procurement in a Box Toolkit, GT Intelligent Controller, One Way Data System, Robotic Process Automation (RPA), and the Spot Robot. Research Method: A quantitative research design was employed, using a structured questionnaire survey distributed to 253 DEWA employees who have experience using AI technologies. The data were analyzed through multiple linear regression to assess the statistical significance of each AI tool’s effect on organizational performance. Findings: The analysis led to the development of a conceptual framework demonstrating that four out of the five AI technologies examined had statistically significant effects on DEWA’s operational performance. Among these, the GT Intelligent Controller emerged as the most influential predictor, followed by the AI Procurement in a Box Toolkit and Robotic Process Automation (RPA). In contrast, the One Way Data System exhibited a significant but negative relationship with performance, suggesting challenges related to system integration or compatibility. The Spot Robot did not show a statistically significant impact, indicating that its effectiveness may be limited at present or still in an early phase of implementation. Originality: This study provides empirical evidence on the differential impact of individual AI technologies in a major utility organization. It contributes to the literature by offering a focused, tool-specific analysis of AI adoption and delivers practical insights for strategic, data-driven implementation of AI in the utilities sector