Herbert John, vice president, digital services, Techwave & Jonathan Rosen, vice president, engineering services, Techwave say that AI and automation are quietly transforming telecom network operations.
For those who have worked in the telecom operations centre operating through long shifts and unpredictable off hours know how much this is true. Networks do not announce their changes with noise. They evolve quietly. It begins with anomalies so subtle they barely register. Slight delays. A behaviour change. And over time, those signals become conversations—not just between people, but between scripts, systems, and intelligent algorithms.
That is the quiet revolution underway across telecom networks. Artificial intelligence and automation are no longer futuristic concepts reserved for innovation roadmaps. They are already here. Working silently in the background, transforming operations from reactive firefighting to proactive orchestration and self-restoration.
In the past, engineers spent hours manually interpreting logs, chasing issues, and inputting command-line prompts with the muscle memory of seasoned troubleshooters. Today, AI is increasingly taking over those tasks—detecting issues and often resolving them before anyone notices.
This shift reflects more than a technological upgrade. It is transforming how people work, think, and how networks are fundamentally designed.
AIOps: The new backbone of telecom operations
One live implementation offers a clear glimpse into what this change looks like in the real world. A telecom provider operating across multiple regions deployed AI-powered automation not with grand expectations but simply to reduce the operational load. What followed over the next six months surprised even the most seasoned engineers. Resolution times dropped by more than half. The volume of noisy, low-priority alerts decreased dramatically. Most importantly, operations teams finally had breathing room—the time and space to move from constant response to strategic thinking.
This is the essence of AIOps, or artificial intelligence for IT operations. These systems are not just rule-based monitors. They ingest massive volumes of telemetry, learn what normalcy looks like, and surface anomalies that matter. They flag issues in real time. In many cases, they resolve them automatically. In essence, they provide a second layer of awareness—one that never forgets, never tires, and always learns.
Building smarter networks with intent-based design
The transformation is also reshaping how telecom networks are built and maintained from the ground up.
Traditionally, network architecture was deeply manual. Every configuration had to be defined explicitly. Failover logic, route preferences, and access policies were each written line by line. This approach was exact but inflexible, relying on teams to anticipate every possible scenario.
Today, that model is giving way to intent-based networking. Rather than defining every technical step, engineers now set outcomes. They specify what they want—lower latency, higher availability, faster recovery—and let intelligent systems determine the best way to achieve it.
This shift enables major telecom providers to operate with greater agility. In one instance, during a fifth-generation network rollout, AI-based zero-touch provisioning allowed thousands of tower sites to go live in a fraction of the expected time. Configuration validation and error resolution happened in real time. What once took days at each site now requires only minutes.
Another example involves a network using machine learning to detect clusters of firmware anomalies that had previously gone unnoticed. The system correlated customer complaints, identified a pattern in device behavior, and issued a targeted update preventing what could have become a widespread issue.
These are not speculative use cases. They are happening today, in production environments, with millions of users depending on uninterrupted service. AI and automation are already managing smart city infrastructure, industrial internet of things systems, and high-traffic consumer broadband. They are not waiting for permission. They are already doing the work.
Engineers evolve: From manual work to strategic innovation
None of this progress would be possible without people willing to evolve alongside the technology.
The role of the telecom engineer is changing. It is no longer enough to be fluent in command-line tools and manual diagnostics. Today’s professionals are expected to design automation frameworks, understand data pipelines, and manage intelligent systems that think for themselves. That transition can be difficult—but it also presents an opportunity.
This shift has implications not just for operations, but for the business as a whole. While automation certainly brings cost efficiencies, its greater value lies in what it enables. When engineering talent is no longer consumed by repetitive tasks—resetting passwords, resolving routine outages, chasing configuration errors—they are free to think bigger.
They can design new services, experiment with architecture, rethink delivery models, and elevate the customer experience in ways that would have been impossible under older operational models.
Automation, in essence, brings back creativity
At the end of the day, most customers never ask how their connectivity works. They only care that it does—that their video call does not buffer while speaking to family, that their warehouse systems sync seamlessly across regions, that their smart devices respond instantly. Increasingly, those expectations are being met not through constant human vigilance but through systems that quietly carry the weight of complexity behind the scenes.
This is not tomorrow’s promise. It is today’s reality. And for telecom professionals, the question is no longer whether to adopt AI and automation. It is whether they are ready to embrace what comes next.