<p>Artificial Intelligence (AI), along with other innovative technologies, is a game changer with the power to completely transform ERP systems, revolutionizing how organizations manage operations, make decisions, and plan strategically. The rapid and forceful infiltration of AI into organizational systems has led to a surge in research on AI-powered ERP systems. However, there is still a need for more comprehensive and systematic studies to fully understand this phenomenon. This paper is a systematic literature review that synthesizes findings from academic and grey literature, exploring the application of all three categories of AI technologies: generative, analytics, and automation in business organizations. The review outlines the evolution of research, spotlights current trends, and identifies gaps and future research directions for the AI-driven ERP landscape. The review synthesizes 183 academic publications and 35 industry documents. Bibliometric analysis revealed an 11.3% annual growth rate in AI–ERP publications, with automation-related topics dominating (41%). Sentiment analysis shows that 93% of studies emphasize positive impacts, while ethical and governance concerns remain marginal (&lt; 2%). This mixed-method analysis highlights automation, predictive analytics, and generative AI as dominant themes, and identifies trust, governance, and long-term strategic impacts as underexplored areas. The results imply that AI is transforming traditional ERP systems by adding autonomy, adaptability, and predictive capabilities into their standard process-integration model. This has significant ramifications for the contemporary understanding of enterprise IT and information systems. Furthermore, they provide managers with a thorough understanding of how AI can be effectively integrated into ERP systems to enhance organizational processes, support more informed and data-driven decision-making, and improve operational performance.</p>