Democratizing AI in Erp Systems: A Business-Centric Educational Framework

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-11
DOI
https://doi.org/10.5281/zenodo.15862373
Primary Topic
Chromosomal and Genetic Variations
Type
article
Field-Weighted Citation Impact
0.00
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article

Democratizing AI in Erp Systems: A Business-Centric Educational Framework

Zenodo (CERN European Organization for Nuclear Research)
Chromosomal and Genetic Variations
article

Democratizing AI in Erp Systems: A Business-Centric Educational Framework

article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Film Independent (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 67%
Chromosomal and Genetic Variations
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Democratizing AI in Erp Systems: A Business-Centric Educational Framework · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS