<![CDATA[The rapid advancement of artificial intelligence (AI) and data-driven technologies has intensified the need for organizations to integrate heterogeneous systems and redesign their data strategies to support real-time decision-making and financial efficiency. This study investigates how system integration accelerates AI and data strategy transformation and simplifies financial operations in the Energy and Utilities sector in the United States. Using a quantitative research design, data were collected from 250 professionals in 2024 through a structured questionnaire measured on a five-point Likert scale. The data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS 3) to examine the relationships among system integration, data architecture and integration, AI and business intelligence capability, real-time decision-making, and financial operational performance. The results reveal that system integration significantly enhances data integration and AI-enabled analytical capability, which in turn improves real-time decision-making. Real-time decision-making emerges as the strongest predictor of improved financial operational performance, particularly in budgeting and forecasting processes. Furthermore, the findings demonstrate that the impact of system integration on financial performance is largely mediated by data integration, AI and BI capability, and decision-making capability. This study contributes to the digital transformation literature by providing empirical evidence from a multi-cloud context and offers practical insights for Energy and Utilities organizations seeking to leverage AI and data strategies to achieve agile, data-driven financial management.]]>
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