Enterprise Resource Planning (ERP) systems have long served as the transactional backbone of modern organizations, integrating core business functions such as finance, operations, supply chain, and human resources into unified digital platforms. However, while ERP systems excel at data standardization and process automation, they have historically fallen short in supporting complex, adaptive, and forward-looking decision-making. In parallel, Decision Intelligence (DI) has emerged as an interdisciplinary paradigm that combines data analytics, artificial intelligence, decision theory, and domain knowledge to systematically improve organizational decisions. This study examines the conceptual and practical integration of Decision Intelligence within ERP ecosystems, positioning DI as a critical evolution beyond traditional business intelligence and reporting layers. Through a structured analytical synthesis of existing literature, system architectures, and organizational use cases, the paper develops a comprehensive framework that explains how DI augments ERP systems by embedding predictive, prescriptive, and cognitive decision capabilities directly into enterprise workflows. The findings demonstrate that DI-enabled ERP systems enhance decision quality, organizational agility, and strategic alignment, while also introducing new challenges related to data governance, model transparency, and human-AI collaboration. The paper concludes by outlining future research directions and managerial implications for enterprises seeking to transition from transaction-centric ERP systems to intelligence-driven decision platforms.