Integrating Artificial Intelligence (AI) into Enterprise Resource Planning (ERP) systems offers numerous benefits, including enhanced decision-making, automation of routine tasks and improved operational efficiency. Despite these advantages, the integration process remains filled with different challenges. However, previous research has only investigated these challenges vaguely. In this context, through a literature review, this paper examines the existing research on the obstacles faced when joining strengths of AI into ERP systems. These key identified challenges embrace various sections of an organization such as IT, Human Resources, financial management, manufacturing, auditing, Supply Chain management, and accounting. To the best of the authors’ knowledge, no previous research has comprehensively collected and analyzed the diverse challenges associated with AI integration within ERP systems. The results of this analysis revealed that data quality and security, high software costs, lack of skilled personnel and organizational resistance to change are the main bottlenecks found in the literature that impede the integration of AI within ERP systems. This highlights the critical need for future research to develop effective methodologies for overcoming AI-ERP integration. This study offers valuable insights for organizations considering AI implementation within their ERP systems, providing practical strategies for practitioners and scholars. The findings of this research will outline numerous solutions in different sectors such as software examples to be used for successful AI-ERP integration, providing a valuable resource and easy implementation for organizations seeking to harness the power of AI in their ERP systems.