Sarcouncil Journal of Engineering and Computer Sciences

Abstract: The integration of artificial intelligence into Enterprise Resource Planning systems has created a significant knowledge gap between technical capabilities and practical business applications. This article presents an educational framework designed to bridge this divide through industry-specific analogies and visual learning techniques. The framework addresses the challenges faced by business professionals in understanding and implementing AI technologies by translating complex technical concepts into familiar business scenarios. Through contextual learning approaches and progressive complexity models, the article enables organizations to effectively train their workforce in AI implementation. The results demonstrate improved knowledge retention, enhanced operational efficiency, and increased adoption rates across various industry sectors. By incorporating visual learning architectures and customized implementation strategies, organizations can successfully overcome the technical-business divide, leading to more effective AI integration in ERP environments and improved business outcomes across manufacturing, distribution, and food & beverage sectors.