AI-Powered Dynamic Billing Optimization: Personalized Plan Recommendations Through Generative Intelligence

This article examines the application of Generative AI (GenAI) to transform telecommunications billing systems from static models to dynamic, personalized solutions. The article explores how AI-human collaboration models analyze individual customer usage patterns to generate optimized billing recommendations in natural language, simulate usage scenarios, and deliver actionable insights. The article evaluates cloud-based AI services, data processing frameworks, and natural language generation technologies that enable these capabilities, while addressing implementation challenges related to privacy, bias, and system integration. Findings demonstrate significant improvements in customer retention, satisfaction, operational efficiency, and revenue management. The article concludes with an assessment of environmental and economic sustainability impacts, ethical considerations, research limitations, and practical recommendations for telecommunications providers implementing dynamic billing optimization solutions.

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Publication Details

Journal
International Journal of Computational and Experimental Science and Engineering
Published
2025-09-27
DOI
https://doi.org/10.22399/ijcesen.3964
Primary Topic
Business Process Modeling and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Powered Dynamic Billing Optimization: Personalized Plan Recommendations Through Generative Intelligence

Ashish Kumar
International Journal of Computational and Experimental Science and Engineering
Business Process Modeling and Analysis
article

AI-Powered Dynamic Billing Optimization: Personalized Plan Recommendations Through Generative Intelligence

Ashish Kumar
article en

Abstract

This article examines the application of Generative AI (GenAI) to transform telecommunications billing systems from static models to dynamic, personalized solutions. The article explores how AI-human collaboration models analyze individual customer usage patterns to generate optimized billing recommendations in natural language, simulate usage scenarios, and deliver actionable insights. The article evaluates cloud-based AI services, data processing frameworks, and natural language generation technologies that enable these capabilities, while addressing implementation challenges related to privacy, bias, and system integration. Findings demonstrate significant improvements in customer retention, satisfaction, operational efficiency, and revenue management. The article concludes with an assessment of environmental and economic sustainability impacts, ethical considerations, research limitations, and practical recommendations for telecommunications providers implementing dynamic billing optimization solutions.

International Journal of Computational and Experimental Science and EngineeringVol. 11(4)
Film Independent (US)
Openalex Percentile: Top 57%
Business Process Modeling and Analysis
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AI-Powered Dynamic Billing Optimization: Personalized Plan Recommendations Through Generative Intelligence — Ashish Kumar · International Journal of Computational and Experimental Science and Engineering (2025) | TGRS Research Map | TGRS