European Journal of Computer Science and Information Technology (EJCSIT)

Breaking the EDI Bottleneck: Modern Mapping Through Generative AI

Abstract

Electronic Data Interchange (EDI) is an established technology in the integration of an enterprise but the conventional mapping procedures are limited by the high levels of manual work, limited reuse and long cycles of partner onboarding. This paper describes a generative artificial intelligence (GenAI)-based system to automate EDI mapping based on schema-sensitive prompt engineering, metadata-based design, and validation-based generation of transformations. Unlike other methods which are rule-based and thus static, the intended solution is dynamically generated to produce transformation logic and adapt to the variations in data of partners.A case study of production that entailed around 200,000 monthly EDI transactions has shown that up to 70% of the onboarding period and 60 percent of the mapping work was reduced. These findings imply that GenAI has the potential to convert EDI workflows to manual setups to an automated system of intelligent, scalable, and adaptive integration.

Keywords: ANSI X12, B2B Integration, Cloud integration, Data Mapping Automation, EDI, enterprise AI, generative AI

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This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License

 

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Email ID: editor.ejcsit@ea-journals.org
Impact Factor: 7.80
Print ISSN: 2054-0957
Online ISSN: 2054-0965
DOI: https://doi.org/10.37745/ejcsit.2013

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