پژوهشنامه پردازش و مدیریت اطلاعات

پژوهشنامه پردازش و مدیریت اطلاعات

Artificial Intelligence and Machine Learning in Telecommunications Revolutionizing Customer Experience and Enhancing Service Delivery

نوع مقاله : مقاله پژوهشی

نویسندگان
Yaser Issam Hamodi Aljanabi 1
Mohammed Fadhil Mahdi 2
Omorova Aizhan Nurlanovna 3
Saif Kamil Shnain 4
Intesar Abbas 5
1 Al-Turath University, Baghdad 10013, Iraq,
2 Al-Mansour University College, Baghdad 10067, Iraq
3 Osh State University, Osh City 723500, Kyrgyzstan
4 Al-Rafidain University College Baghdad 10064, Iraq
5 Madenat Alelem University College, Baghdad 10006, Iraq
10.22034/jipm.2025.728199
چکیده
ABSTRACT
Background: The telecommunications industry is at the crossroad of change seemingly precipitated by the use of Artificial Intelligence (AI) and Machine Learning (ML). These technologies have yielded new features like network automation, prescriptive analytics, and contextual-consumer engagement, solving traditional dilemmas in service delivery and operationalization.
Objective: The current article seeks to understand how AI and ML has positively affected customer experience and service provision in the telecommunication industry. The research objectives focus on how to increase KPIs to service latencies, network reliability, and customer retention while at the same time establishing the problems associated with big data large-scale implementation.
Methods: Samples were gathered using systematic reviews of the current literature, meta-analysis of case studies, and assessment of industry datasets. This concerned artificial intelligence enabled operations such as dynamic resource management, real-time customer emotions analysis and real-time fault detection. Regression analysis and time series models were used in order for measuring performance indices.
Results: AI and ML integration led to multifaceted advancements: a decrease of average service latency by 55%, reduction of network downtime by 70%, and an increase of maintenance predictions accuracy by 35%. The customer retention rate which had improved to 25% was also credited to better personalization of the services as well as having proper service management. AI-equipped resource allocation also raised efficiency in bandwidth utilization by 60%.
Conclusion: AI and ML are positively disrupting telecommunications as they deliver remarkable enhancements in the caliber of services and client satisfaction. With all the challenges in data governance and interoperability, it is clear that their adoption promises a great chance in enhancing the current standards within the telecommunications field and creating the basis for the development of a more sophisticated environment.
کلیدواژه‌ها
KEYWORDS: Artificial Intelligence (AI)
Machine Learning (ML)
Telecommunications
Customer Experience (CX)
Service Delivery
Network Optimization
Predictive Analytics
Resource Allocation
Bandwidth Utilization
Predictive Maintenance

عنوان مقاله English

Artificial Intelligence and Machine Learning in Telecommunications Revolutionizing Customer Experience and Enhancing Service Delivery

نویسندگان English

Yaser Issam Hamodi Aljanabi 1
Mohammed Fadhil Mahdi 2
Omorova Aizhan Nurlanovna 3
Saif Kamil Shnain 4
Intesar Abbas 5
1 Al-Turath University, Baghdad 10013, Iraq,
2 Al-Mansour University College, Baghdad 10067, Iraq
3 Osh State University, Osh City 723500, Kyrgyzstan
4 Al-Rafidain University College Baghdad 10064, Iraq
5 Madenat Alelem University College, Baghdad 10006, Iraq
چکیده English

ABSTRACT
Background: The telecommunications industry is at the crossroad of change seemingly precipitated by the use of Artificial Intelligence (AI) and Machine Learning (ML). These technologies have yielded new features like network automation, prescriptive analytics, and contextual-consumer engagement, solving traditional dilemmas in service delivery and operationalization.
Objective: The current article seeks to understand how AI and ML has positively affected customer experience and service provision in the telecommunication industry. The research objectives focus on how to increase KPIs to service latencies, network reliability, and customer retention while at the same time establishing the problems associated with big data large-scale implementation.
Methods: Samples were gathered using systematic reviews of the current literature, meta-analysis of case studies, and assessment of industry datasets. This concerned artificial intelligence enabled operations such as dynamic resource management, real-time customer emotions analysis and real-time fault detection. Regression analysis and time series models were used in order for measuring performance indices.
Results: AI and ML integration led to multifaceted advancements: a decrease of average service latency by 55%, reduction of network downtime by 70%, and an increase of maintenance predictions accuracy by 35%. The customer retention rate which had improved to 25% was also credited to better personalization of the services as well as having proper service management. AI-equipped resource allocation also raised efficiency in bandwidth utilization by 60%.
Conclusion: AI and ML are positively disrupting telecommunications as they deliver remarkable enhancements in the caliber of services and client satisfaction. With all the challenges in data governance and interoperability, it is clear that their adoption promises a great chance in enhancing the current standards within the telecommunications field and creating the basis for the development of a more sophisticated environment.

کلیدواژه‌ها English

KEYWORDS: Artificial Intelligence (AI)
Machine Learning (ML)
Telecommunications
Customer Experience (CX)
Service Delivery
Network Optimization
Predictive Analytics
Resource Allocation
Bandwidth Utilization
Predictive Maintenance

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  • تاریخ دریافت 15 مرداد 1404