225. SURVEY ON TECHNICAL, BUSINESS AND REGULATORY ASPECTS OF ARTIFICIAL INTELLIGENCE IN TELECOM NETWORKS AND SERVICES

Dimitar Tanevski; Toni Janevski; Venceslav Kafedziski

doi:10.51466/JEEIT2492225108t

Dimitar Tanevski Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University in Skopje, 18 Rugjer Bošković Str., 1000 Skopje, Republic of Macedonia
Toni Janevski Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University in Skopje, 18 Rugjer Bošković Str., 1000 Skopje, Republic of Macedonia
Venceslav Kafedziski Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University in Skopje, 18 Rugjer Bošković Str., 1000 Skopje, Republic of Macedonia

DOI: https://doi.org/10.51466/JEEIT2492225108t

Keywords: Artificial Intelligence (AI), AI governance, AI regulation, AI standardization, business aspects of AI

Abstract

The advancement of AI/ML models, along with the complexity of new-generation networks, including IMT-2020, has made AI functionality indispensable in telecom architecture and business strategies. Standardization bodies such as ETSI and ITU-T have established the foundation for architectural frameworks, with ITU-T Y.3172 and ETSI’s ENI models, leading to various recommendations and supplementary documents covering internal communication, quality of service, fault and recovery, and security frameworks and procedures. Globally, regulatory efforts surrounding AI in telecom, such as the EU's Artificial Intelligence (AI) Act and initiatives from the U.S. and China, emphasize risk categorization, fines for non-compliance, and ethical principles to ensure responsible deployment. Industry collaborations, exemplified by Nokia and NVIDIA's partnership for tech efficiency, and the deployment of AI-driven chatbots by telecom giants like AT&T, Deutsche Telekom, and Vodafone, highlight tangible benefits such as reduced costs, improved performance, and enhanced customer experience. These advancements not only drive down CAPEX and OPEX but also fuel revenue growth and bolster customer satisfaction, underscoring the transformative impact of AI in telecommunications