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Product Management Challenges in AI-Driven Telecom Billing & Payment Ecosystems
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 89 |
| Year of Publication: 2026 |
| Authors: Balu Chavan |
10.5120/ijca2026926545
|
Balu Chavan . Product Management Challenges in AI-Driven Telecom Billing & Payment Ecosystems. International Journal of Computer Applications. 187, 89 ( Mar 2026), 10-15. DOI=10.5120/ijca2026926545
Abstract
This work describes the challenges far from trivial that product managers in telco are facing, striving for payment ecosystems powered by AI. As telecoms morph into fintech’s, AI and old fangled payment systems have their very own set of unique challenges – ranging from ensuring interoperability and winning user trust to crunching numbers in all but real-time. This paper is based on a mixed-method study that uses data from 458 operating cases of a Tier-1 telecom company. Python is used for preliminary filtering and statistical classification, while Tableau is utilized to visualise the complex multidimensional relationships between system latency and fraud detection accuracy. The tension between stability (linguistic and algorithmic) and dynamic, linguistic decision-making is the subject of investigation. Key findings include: The primary bottleneck is not model sophistication but the architectural constraints of current telecom cores, which were not designed to accommodate high-frequency, low-latency financial transactions. The paper ends with the suggestion that for product management to succeed in this space, feature-centric roadmaps should be replaced with platform-centric strategies that favour architectural modularity and explainable AI as a strategy to retain user trust.
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