AI/ML-Driven Service Assurance: 2024 Breakthroughs Transforming Telecom Operations

This article explores the transformative impact of artificial intelligence and machine learning technologies on telecommunications service assurance. The industry is experiencing a paradigm shift from reactive to predictive and prescriptive approaches to network management, enabled by three key technological breakthroughs: generative AI, causal inference, and federated learning. Major telecommunications providers are implementing Large Language Models to automate incident resolution processes, reducing resolution times and improving remediation quality. Simultaneously, causal AI is advancing proactive service assurance by establishing cause-and-effect relationships between network events, enabling operators to prevent service disruptions before they occur. Federated learning implementations are solving multi-domain assurance challenges by enabling cross-operator insights while maintaining data sovereignty. Together, these technologies are not merely enhancing existing processes but fundamentally reimagining telecommunications service assurance. The convergence of these approaches promises to deliver self-diagnosing, self-optimizing networks that can anticipate and address potential issues before they impact customer experience, representing a revolutionary advancement in how service quality and reliability are managed in increasingly complex network environments.

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Publication Details

Journal
Journal of Computer Science and Technology Studies
Published
2025-05-09
DOI
https://doi.org/10.32996/jcsts.2025.7.4.1
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00
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article

AI/ML-Driven Service Assurance: 2024 Breakthroughs Transforming Telecom Operations

Venu Madhav Nadella
Journal of Computer Science and Technology Studies
Digital Transformation in Industry
article

AI/ML-Driven Service Assurance: 2024 Breakthroughs Transforming Telecom Operations

Venu Madhav Nadella
article en

Abstract

This article explores the transformative impact of artificial intelligence and machine learning technologies on telecommunications service assurance. The industry is experiencing a paradigm shift from reactive to predictive and prescriptive approaches to network management, enabled by three key technological breakthroughs: generative AI, causal inference, and federated learning. Major telecommunications providers are implementing Large Language Models to automate incident resolution processes, reducing resolution times and improving remediation quality. Simultaneously, causal AI is advancing proactive service assurance by establishing cause-and-effect relationships between network events, enabling operators to prevent service disruptions before they occur. Federated learning implementations are solving multi-domain assurance challenges by enabling cross-operator insights while maintaining data sovereignty. Together, these technologies are not merely enhancing existing processes but fundamentally reimagining telecommunications service assurance. The convergence of these approaches promises to deliver self-diagnosing, self-optimizing networks that can anticipate and address potential issues before they impact customer experience, representing a revolutionary advancement in how service quality and reliability are managed in increasingly complex network environments.

Journal of Computer Science and Technology StudiesVol. 7(4)
Cytel (United States) (US)
Openalex Percentile: Top 87%
Digital Transformation in Industry
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