Assessing AI-Enabled Fraud Detection and Business Intelligence Dashboards for Trust and ROI in U.S. E-Commerce: A Data-Driven Study

As the U.S. e-commerce sector grows, mixing AI and BI tools is essential for corporate success and customer satisfaction. This study examines the impact of AI and BI technologies on customer loyalty and marketing ROI. A cross-sectional poll of 400 US e-commerce specialists from various sectors and vocations was conducted. Quantitative data were collected via questionnaire and analysed using descriptive statistics, chi-square tests, Spearman correlations, and Kruskal-Wallis H tests. Over 47.5% of organisations employ AI for fraud detection, and over 58.5% utilise BI dashboards, all with good thoughts about using them to detect fraud, gain actionable customer data, and strengthen customer connections. AI fraud detection affects platform security perception (p = 0.04151), while BI tools help businesses use dashboards more (p = 0.005). Companies may value AI/BI systems differently based on their advancement and capacities, rather than their marketing results or trust. Due to the field's sophistication, data sensitivity, and fierce competition, these findings benefit U.S. managers, policymakers, and researchers. The research combines AI, BI, trust, and performance in e-commerce to understand their link. The research presents a data-based approach for assessing the effects of AI and BI on security and marketing in U.S. digital commerce, supporting the national goal of safe and reliable AI adoption.