Implementing Conversational AI into ERP Software | Zendy

Siar Sarferaz | Zendy

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Implementing Conversational AI into ERP Software

Author(s) -

Siar Sarferaz

Publication year - 2025

Publication title -

ieee access

Language(s) - English

Resource type - Magazines

SCImago Journal Rank - 0.587

H-Index - 127

eISSN - 2169-3536

DOI - 10.1109/access.2025.3608477

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Enterprise Resource Planning (ERP) systems are pivotal in the digital transformation of organizations, offering an integrated platform to digitalize processes across various business functions, such as finance, supply chain, and human resources. Despite their expansive capabilities, these systems often present usability challenges due to their complexity and vastness. The integration of Conversational Artificial Intelligence (AI) presents a novel opportunity to enhance user interaction with ERP systems, streamlining processes and improving accessibility through natural language interfaces. Conversational AI refers to technology that enables machines to engage in human-like dialogue, understanding and responding to user queries in natural language. However, embedding Conversational AI into ERP systems is not without challenges due to the vast and intricate landscape of ERP systems, which are comprised of hundreds of thousands of business processes, involve hundreds of millions of lines of code and cater to diverse industry-specific requirements. This paper explores the critical research question: How to systematically develop Conversational AI in ERP systems? The paper conducts the business requirements and proposes a comprehensive solution framework. This framework is implemented and evaluated using real-world ERP use cases, demonstrating its potential to significantly enhance ERP user engagement and operational efficiency, while setting the stage for future innovations in enterprise software usability.

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