The evolution of digital transformation has increased the volume, velocity, and variety of data generated by organizations. This trend has prompted companies to adopt Business Intelligence (BI) as an approach to integrating, processing, analyzing, and presenting data as information relevant to decision-making. This study aims to analyze the implementation of Business Intelligence in supporting business decision-making using the Systematic Literature Review (SLR) method. The review process involved identifying, selecting, and synthesizing relevant prior research on Business Intelligence, data-driven decision-making, decision quality, and organizational performance. The review procedure adhered to PRISMA principles, focusing on publications from the 2020–2026 period sourced from relevant scientific databases and academic repositories. The findings indicate that Business Intelligence contributes to enhancing the quality, speed, and accuracy of decision-making through data integration, interactive visualization, and descriptive, predictive, and prescriptive analytics. However, successful BI implementation depends not only on technology but also on data quality, human resource capabilities, management support, data governance, a data-driven culture, and system integration. Recent developments also reveal a shift in BI from systems focused on historical reporting toward systems integrated with Artificial Intelligence (AI), data science, and Decision Intelligence. The study concludes that BI is best viewed as an organizational capability that strengthens decision-making processes and indirectly contributes to improved performance and corporate competitive advantage.