Enterprise resource planning (ERP) systems are indispensable tools for organizations, offering streamlining of various processes, enhanced planning strategies, personnel management, and resource optimization. Over time, these ERP solutions have evolved through the integration of diverse technologies, enhancing their capabilities. This iteration is currently resolving around the integration of artificial intelligence (AI), which has created a substantial knowledge gap among users, as well as lack of fundamental understanding on how to properly utilize these newer AI integrated ERP solutions. With this imminent evolution, this master’s thesis will address the question: What are the opportunities and challenges of integrating AI into ERP systems? This inquiry forms the core of this thesis, employing semi-structured interviews with experts in ERP and AI development. Followed by a thematic analysis to elucidate the various facets of this research field and its organizational implications. The research's findings underscore the potential of AI integration in ERP systems, promising improved predictive capabilities, process streamlining, and task efficiency. However, numerous challenges will rise, including the need for robust change management strategies, deeper understanding of AI technologies, and commitment in resource allocation and revised methodologies within enterprises. By delving into these opportunities and challenges, this thesis offers valuable insights for both practitioners and academics, enriching our understanding and knowledge of the upcoming integration of AI into ERP.