AI insights with actionable automation accelerate the journey to autonomous networks

AI insights with actionable automation accelerate the journey to autonomous networks Enabling better network AI insights Delivering actionable automation From DarkNOC to agentic AI: The evolution of actionable automation Bringing it all together Conclusion Hatville: miniature city where edge computing comes to life About the authors Saad Ahmed Francisco P Hernandez More like this IT automation with agentic AI: Introducing the MCP server for Red Hat Ansible Automation Platform Fast and simple AI deployment on Intel Xeon with Red Hat OpenShift Technically Speaking | Build a production-ready AI toolbox Technically Speaking | Platform engineering for AI agents Keep exploring Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share The telecommunications industry is accelerating its digital transformation, driven by the increasing complexity of modern networks and the demand for faster, more reliable services rollout. To meet these demands, operators are turning to autonomous intelligent networks, designed to ingest massive amounts of data and autonomously execute actions at high speed. The journey to autonomous intelligent networks is not a technology project—it is a mandatory operational shift to protect margins and accelerate time-to-service. This has led to concepts such as a DarkNOC , a network operations center that can operate without direct human intervention, using technology to enhance network reliability, improve performance, and increase cost-efficiency. There are two fundamental tenets for building autonomous networks: Better network AI insights and actionable automation. For any AIOps solution to be effective, it must be built on a foundation of highquality, AI-driven insights. These insights are derived from capabilities like: Data aggregation and analysis Anomaly detection and prediction Intelligent alerts and root cause analysis Leveraging AI for cross-domain event monitoring Red Hat accelerates AIOps strategies by providing a robust, integrated set of technologies. Our portfolio, including hybrid cloud infrastructure , cloud-native development , AI , IT automation and management , and edge computing , is represented by technologies such as Red Hat OpenShift, Red Hat AI, Red Hat Enterprise Linux (RHEL), Red Hat Ansible Automation Platform, Red Hat Runtimes, and centralized messaging systems like Red Hat OpenShift Streams for Apache Kafka. Combined, these products offer the essential container-as-a-service (CaaS) and AI platforms that AIOps solutions require. Gaining insights is only half the battle. You also need the ability to act on them quickly and reliably. You need actionable automation.