AI-Powered IVR Assistant With Intelligent Escalation Logic

DOI

10.2991/978-94-6239-693-7_92How to use a DOI?

Keywords

AI-IVR; intelligent escalation; speech recognition; Multilingual NLP; Customer Service automation

Abstract

With the rapid creation of artificial intelligence in the sphere of conversational technologies, the management of the interaction with the customers has been changed by the organization in question, specifically, the adopted use of the automated call-handling system. I will present an interactive voice response (IVR) assistant, which is an AI-based assistant capable of understanding natural speech and able to communicate in a multitude of languages and make sensible decisions about when to activate an assistant and when to call an assistant in the call center. It is a system that will be implementing state-of-the-art speech recognition, multilingual natural language processing, and intent-classification models to understand user queries in real time correctly. There is also an escalation engine that focuses on the sentiment indicators, intent confidence, and common misunderstandings to determine whether a customer requires connecting with a live AI agent or not in order to improve the quality of services provided and reduce the friction process within the customer support framework. Python Flask was used to develop the backend and it included translation modules, NLP pipelines, speech-to-text and text-to-speech modules, and a selection of a carefully chosen dataset to train intent models. The frontend is built on Next.js and Supabase authentication to work with and monitor the environment and provides a user-friendly interface to do so. The results of the experiment were to show a high rate of intent detection and multilingual comprehension and reduce unnecessary handoffs to human agents. The system is expected to ease the load on the working end, shorten the response time, and enhance the overall experience of the caller by automating the routine contacts and intelligently managing the escalations. The findings confirm the greater possibilities of AI-based IVR systems in the modern customer service environment.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Telukuntla Hemanth Kumar
AU  - Valleru Charan Tej
AU  - S. Rajashree
AU  - R. Santhanakrishnan
AU  - Jemshia Miriam
AU  - R. Srinivasan
PY  - 2026
DA  - 2026/06/16
TI  - AI-Powered IVR Assistant With Intelligent Escalation Logic
BT  - Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)
PB  - Atlantis Press
SP  - 956
EP  - 965
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-693-7_92
DO  - 10.2991/978-94-6239-693-7_92
ID  - Kumar2026
ER  -