Business Intelligence (BI) is established as an enabler of strategic operational efficiency, cost optimization, and customer engagement for Small and Medium-sized Enterprises (SMEs). This paper integrates emerging empirical and systematic review literature on BI adoption among U.S. SMEs, which is seen as converting raw data into useful information for business decision-making. The results suggest BI systems allow for the consolidation of multi-source data, have predictive analysis, and are used for real-time monitoring as part of SMEs to manage processes better, resource allocation, operating costs reduction, and effective inventory and supply chain management. Case studies involving an international online retailer and a major telecommunications company illustrate the real-world impact for BI: Predictive analytics and tailored interventions drove customer retention up, service quality improved, and actual returns on revenue growth. However, SMEs face barriers including lack of technical staff, high costs in the set-up process, data quality problems and organizational resistance and cyber threats. Effective adoption demands strong data governance, compatibility with the organizational strategy, capability building and staged implementation. In general, BI guides SMEs to adopt proactive instead of reactive management and will assist evidence-driven decisions in areas related to widening the organization`s competitive edge, improving operating performance, and financial results. The research highlights the relevance of BI in addressing technological and strategic challenges within a complex digital economy.