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Implementing Conversational AI in ERP Systems: A Technical Framework for Real-Time Financial Operations

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  • Bhagavathi Sathya Satish Kadiyala

Abstract

This article presents a comprehensive technical framework for implementing conversational AI interfaces within Enterprise Resource Planning (ERP) systems, focusing on real-time financial operations. The article examines how Natural Language Processing (NLP) technologies can transform traditional ERP interfaces into intuitive, conversation-driven systems that enhance user accessibility and operational efficiency. The article details the technical architecture, core capabilities, implementation methodologies, and business impact of integrating NLP-enhanced interfaces in enterprise environments. Through analysis of multiple enterprise implementations, the article demonstrates how conversational AI significantly improves user adoption, reduces training requirements, and enhances operational efficiency across financial processes. The article addresses critical aspects including security considerations, performance optimization, and scalability requirements while providing insights into the practical challenges and solutions for enterprise-scale deployments. The article reveals that NLP-enhanced ERP systems not only streamline financial operations but also democratize access to complex financial data, enabling more informed decision-making across organizational hierarchies while maintaining robust security and compliance standards.

Suggested Citation

  • Bhagavathi Sathya Satish Kadiyala, 2025. "Implementing Conversational AI in ERP Systems: A Technical Framework for Real-Time Financial Operations," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(1), pages 3583-3593, February.
    • Handle: RePEc:jbh:ijsrcs:v11:y2025:i1:id:1037
    DOI: 10.32628/CSEIT251112383
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112383
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