It’s the peak traffic hour on a busy weekday evening. A common occurrence for a typical telecommunication (telco) service provider. Millions of subscribers are streaming videos, playing games, and making calls. Suddenly, a network outage occurs in a key metropolitan area.
Level 3 (L3) operations team at the service provider would begin troubleshooting the incident. They would manually sift through logs across multiple domains (radio access network, core, transport) and race against time to restore services. Hours, sometimes days, could pass before the incident was fully resolved, leading to frustrated customers, lost revenue, and reputational damage. How different would the situation have been if artificial intelligence (AI) was involved?
An agentic AI-driven network would detect anomalies in real time, identifying the root cause and resolving the issue autonomously before customers even noticed a problem. Operations teams would be able to move from a reactive posture to a proactive one, focusing instead on strategic innovation and customer experience.
Building AI-driven autonomous intelligent networks
The telco industry is at a pivotal moment. With 5G fully deployed, and 5G advanced and 6G on the horizon, networks are more complex and data-intensive than ever. Manual approaches to network deployment and operations simply cannot keep up with the scale of current and future demand.
By embedding AI at every layer of the network, service providers can predict and resolve issues proactively, optimize spectrum usage in real time, deliver personalized, differentiated customer experiences, and reduce operational costs and improve time to market.
4 cutting-edge use cases
L3 customer support assistant for network operations
One of the biggest challenges faced by service provider network operations teams is resolving complex multi-domain issues. In collaboration with Future Connections, Red Hat has developed a multi-agentic, AI-powered assistant which acts as a virtual expert to guide engineers through advanced troubleshooting. The AI-powered assistant is built using Red Hat AI Inference Server and Red Hat OpenShift AI.
This assistant accelerates root cause analysis (RCA) and dramatically reduces mean time to resolution (MTTR), resulting in faster and smarter problem solving—and happier customers.
Intelligent autonomous radio assistant for spectrum efficiency
Spectrum is a scarce and expensive resource for service providers. Again in collaboration with Future Connections, Red Hat has developed an AI-powered radio assistant that helps maximize spectrum utilization by detecting coverage gaps in real time, reducing uplink and downlink (UL/DL) interference, and provides actionable AI-assisted optimization decisions.
By improving spectrum efficiency, service providers can enhance connectivity, deliver better service quality, and make the most of their infrastructure investments.
Agentic AI-powered customer experience analytics
In a competitive market, customer experience is everything. This use case demonstrates how open source data lakehouses and advanced analytics give service providers a competitive edge by collecting crowdsourced experience data and running natural language queries via the Red Hat AI Inference Server. This helps service providers gain real-time visibility into service performance and to benchmark quality against competitors at granular geographic levels.
By transforming raw data into actionable insights, service providers can proactively improve customer satisfaction and uncover new growth opportunities.
Autonomous intelligent network with event-driven automation
An autonomous intelligent network identifies issues and resolves them on its own. Telemetry log events can trigger large language model (LLM)-driven RCA using Event-Driven Ansible, part of the Red Hat Ansible Automation Platform. Automatic creation of remediation scripts is achieved with Red Hat Ansible Lightspeed generative AI (genAI) to achieve end-to-end, closed-loop autonomous remediation.
Built entirely by Red Hat’s Center of Excellence, this is the blueprint for future network operations, delivering lightning-fast resolution and proactive fault management.
The technology powering the transformation
Behind these use cases lies Red Hat’s comprehensive AI platform, designed to help service providers scale AI adoption with security and efficiency. Red Hat OpenShift AI is a complete machine learning operations (MLOps) and large language operations (LLMOps) platform for training and deploying AI at scale. It provides model-as-a-service (MaaS) to simplify access to production-ready AI models and Red Hat AI Inference Server for high-performance inferencing for carrier-grade workloads. Red Hat Enterprise Linux AI provides the tools for fine-tuning and deploying AI models at the edge.
These technologies give service providers the flexibility to innovate without vendor lock-in, while maintaining carrier-grade security and performance.
Beyond AI: The broader Red Hat portfolio ecosystem
Red Hat’s vision extends beyond autonomous intelligent networks. Our solutions integrate with hybrid cloud infrastructure for flexible, multicloud strategies, automation and management platforms for streamlined operations, and cloud-native application platforms for rapid service innovation.
This unified portfolio empowers service providers to modernize their entire technology stack, from the datacenter to the edge of the network, ensuring long-term agility and resilience.
Red Hat as the AI platform partner at India Mobile Congress 2025
Red Hat is proud to be the official AI platform partner at this year’s India Mobile Congress (IMC), empowering service providers to reimagine network operations with open, modular, and scalable AI-driven platforms. Our solutions are designed for fully autonomous, self-healing, and self-optimizing networks.
Visit Red Hat at the Yashobhoomi Event Center, New Delhi, Hall 1, Booth C5, between October 8-11, 2025, where we will showcase live, interactive demos of AI-driven network innovations. Here you can engage with Red Hat experts to discuss tailored strategies for your organization and gain insights into emerging trends and technologies shaping the industry.
关于作者
Atul is a Principal Chief Architect in the Global Field CTO Office (Telco) at Red Hat, where he collaborates with Telco CXOs to shape and execute strategic transformation roadmaps toward AI-native and Cloud-native architectures. He currently leads initiatives focused on advancing Level 4/5 Autonomous Intelligent Networks, driving the transition from manual to AI-driven Intelligent Operations by harnessing Red Hat’s Hybrid Cloud, AI, and Automation portfolio in synergy with Red Hat's global partner ecosystem.
Rob McManus is a Principal Product Marketing Manager at Red Hat. McManus is an adept member of complex matrix-style teams tasked to define and position telecommunication service provider and partner solutions with a focus on network transformation that includes 5G, vRAN and the evolution to cloud-native network functions (CNFs).
