Page 88 - SAMENA Trends - June-July 2025

ARTICLE SAMENA TRENDS

In summary, 5G-A is not just “better / faster Key AI Applications Deployed in in Tele- powers AI-driven chatbots and virtual
5G” – it’s a smarter, more responsive net- coms: assistants.
work layer, designed to handle the complex • Network Optimization with AI - Generative AI (GenAI) is now enabling
needs of both human and machine users in - AI helps with intelligent traffic intent prediction, personalized service
real time. management, dynamic spectrum suggestions, and real-time ticket reso-
allocation, energy optimization, and lution.
Understanding AI in Telcos predictive maintenance in radio access • Customer Experience Enhancement with
AI in the telecom industry refers to a broad and transport layers. AI
set of technologies – machine learning - Reinforcement learning is used to - Development new services or business
(ML), deep learning, & generative AI – that self-optimize network performance models (such as New Calling, Real
are applied to automate, optimize, and per- based on real-time data. Time Translation, SLA-based services
sonalize various aspects of network and • Customer Service Enhancement with AI at the app level etc.)
business operations. - Natural language processing (NLP) -
Top 3 AI Applications in Telcos

Source: Futurism Technologies
The growing maturity of AI means telecom algorithms are increasingly responsible • Network Slicing Automation: AI deter-
operators are not just using AI as a tool, but for managing the complexity of modern mines when and how to create, scale,
are beginning to architect their networks networks, where thousands of parameters or remove network slices based on re-
and services around AI. This shift is most (user behavior, location, service type, ser- al-time demand, QoS needs, and user
powerful when paired with a 5G-A net- vice experiences etc.) change in millisec- profiles – especially in enterprise and in-
works, capable of hosting and supporting onds . dustrial settings.
real-time, distributed AI functions. How AI Boost 5G-A
• RAN Optimization: AI models improve 5G-A Enables Real Time AI
The Relationship Between 5G-A and AI beamforming, scheduling, and interfer- While AI empowers the network, 5G-A also
The relationship between 5G-A and AI is not ence management in massive MIMO empowers AI-based services and applica-
simply complementary – it’s deeply inter- networks, dynamically adapting to traffic tions. Its high throughput, low latency, and
dependent . These technologies reinforce loads and user mobility patterns. edge computing capabilities allow real-time
each other’s value, forming a feedback loop • Self-Healing Networks: Predictive main- interaction and decision making .
where intelligent infrastructure enables ad- tenance tools use AI to detect anomalies How 5G-A Supports AI
vanced services, and AI empowers the net- before outages occur, reducing down- • Edge AI Inference: 5G-A’s distributed
work to evolve in real-time. Together, they time and improving service quality. architecture allows AI models to be de-
form the intelligent engine of future tele- • Energy Efficiency: AI enables base sta- ployed at the network edge – closer to
com innovation. tions to enter low-power modes during the user or device – reducing latency for
low usage periods or reroute traffic to applications like video analytics, industri-
AI Makes the 5G-A Networks More Potent optimize energy use – critical for sus- al robotics, or autonomous vehicles .
Unlike previous network generations, 5G-A tainability and cost control in dense 5G-A • Support for Massive AI Workloads:
is designed with AI built into its core. AI deployments. AI-driven applications, such as computer

88 JUNE-JULY 2025