Decoding the AI Value Chain for Telcos

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There are many forces shaping the future of telecom networks, driven on one side by emerging necessities and on the other by the rapid advancement of AI—specifically, the new dawn of Agentic AIs.

One of the most pressing needs is the acceleration of network software deployment, as telecom functions have shifted from tightly integrated hardware-software solutions to cloud-native software packages. This transition demands more advanced CI/CD/CT pipelines to handle the complexity and stringent reliability requirements of modern networks. At the same time, operators must find ways to reduce operational costs as network architectures grow increasingly complex with the introduction of 5G, 6G, and microservices-based functions. Beyond operational efficiency, the industry is also focused on building new capabilities that enable fresh revenue streams, such as Network as a Service (NaaS) and Network Slicing.

Agentic AI, driven by the synergy between GenAI and AI-based automation, is rapidly becoming a critical enabler of this transformation. Unlike traditional automation methods, Agentic AI can independently make decisions, proactively execute tasks, and dynamically adapt to changing conditions. In telecom, this translates into accelerated development of truly self-optimizing networks, seamless AI-driven deployment processes, and intelligent, proactive service assurance—ushering in a new era of autonomous operations, enhanced efficiency, and expanded revenue opportunities.

Streamlining CI/CD/CT Pipelines with Agentic AI

Continuous Integration, Continuous Deployment, and Continuous Testing are foundational practices in modern software development, enabling rapid delivery of high-quality software. However, the full adoption of this practice into the Telco world has faced many challenges associated with the complex picture of dependency management, security validation and sophisticated testing. With the emergence of the Agentic AI though these challenges can be eventually overcome bringing transformative benefits.

Automated Discovery and Validation

Agentic AI agents can autonomously monitor repositories and vendor releases to detect new software packages, ensuring that the latest updates are identified promptly. Upon discovery, these agents validate code changes and configuration files, assessing compatibility and compliance with existing systems. This proactive approach minimizes the risk of integration issues and accelerates the deployment process.

Intelligent Test Scope Definition

Determining the appropriate scope of testing for new software updates is crucial. Agentic AI analyzes the nature and extent of changes to define the necessary testing scope, optimizing resource utilization and ensuring comprehensive validation. This intelligence-driven testing strategy enhances the reliability of deployments.

Autonomous Security Testing

Security is paramount in telecommunications. Agentic AI agents can conduct autonomous penetration testing, identifying vulnerabilities and applying necessary fixes without human intervention. This continuous security assessment fortifies the network against emerging threats.

Canary Deployments and Anomaly Detection

To mitigate risks associated with full-scale deployments, AI agents can leverage canary deployments or FOAs to monitor performance and anomalies in real-time. If no issues are identified, the update can be safely rolled out network-wide, ensuring stability, reliability and fulfilling the speed of deployment needed to keep up-to-date with ever accelerating software deployment cycles.

The integration of Agentic AI into CI/CD/CT eventually provides a reliable solution as networks become more complex with the introduction of technologies like 5G and beyond.

Autonomous Troubleshooting and Issue Resolution

As telecommunications networks grow in complexity, traditional troubleshooting methods become increasingly inadequate. Agentic AI offers a paradigm shift by enabling autonomous detection and resolution of network issues, thereby enhancing operational efficiency and customer satisfaction.

Proactive Issue Detection

Agentic AI agents continuously analyze and correlate multiple data streams—such as Packet Capture (PCAP) files, system logs, and tracing data—to detect anomalies in call flows and overall system performance. Beyond detection, these agents also conduct root cause analysis and proactively recommend remediation steps, allowing potential issues to be resolved before they escalate and minimizing service disruptions.

Replicating Engineering Ways of Working

By documenting existing troubleshooting processes, Agentic AI can replicate the decision-making workflows of human engineers. Each task, from diagnosing packet loss to identifying misconfigurations, can be assigned to specialized AI agents, ensuring consistent and efficient issue resolution. This capability allows for the scaling of expert knowledge across the network.

Autonomous Remediation

Even though we’ve heard a lot of hype around autonomous remediation for years and many attempts have been made to achieve the goal, Agentic AI makes a true paradigm shift with its capability to self-evaluate the approach and self-validate and correct actions in case of an encountered error. This capability makes the Agentic AI much better fit to the stringent requirements of reliability and resilience of modern telco network.

The deployment of Agentic AI in troubleshooting transforms reactive maintenance into proactive management, ensuring networks operate optimally with minimal human oversight. This shift is crucial for maintaining service quality in increasingly complex network environments.

Accelerating Network APIs and Network Slicing with Agentic AI

The advent of 5G and the impending rollout of 6G networks have ushered in opportunities for telecom operators to offer customized services through Network APIs and Network Slicing. Agentic AI plays a pivotal role in accelerating the development and management of these capabilities.

Rapid Development and Deployment of Network APIs

Agentic AI automates the creation, testing, and documentation of Network APIs, enabling telecom operators to expose network functionalities to third-party developers swiftly. This automation fosters innovation and allows for the rapid deployment of new services, thereby enhancing competitiveness.

Dynamic Network Slice Management

Network slicing allows operators to create virtual networks tailored to specific service requirements. Agentic AI can dynamically create and manage these slices in response to changing application demands, such as supporting low-latency services for augmented reality or high-bandwidth requirements for video streaming. This adaptability ensures optimal resource allocation and quality of service.

Enhancing Customer Experience

By leveraging Agentic AI, operators can offer personalized services through APIs and network slices, catering to the unique needs of individual customers or applications. This customization enhances user satisfaction and opens new revenue streams.

The integration of Agentic AI into Network API development and Network Slicing not only accelerates service delivery but also enables telecom operators to offer differentiated services, thereby driving growth and innovation in the industry.

Conclusion

For years, operators and software vendors have been discussing autonomous networks, making incremental efforts but consistently falling short of their ambitious vision. However, with the recent unprecedented advancements in AI—particularly the convergence of GenAI and AI-based automation into what we now call Agentic AI—it finally feels as though the winds have shifted in the right direction. At Reailize, we’re genuinely excited about the progress we’ve witnessed over the past year. In what ways do you envision Agentic AI shaping the telecom industry's future?