The Critical Role of User Traffic

When a major telecom provider went dark for the better part of a day a few years back, it wasn’t a dramatic cyberattack or a natural disaster that brought it down. It was a configuration change, one of the most routine operations in network management, that quietly snowballed into one of the most disruptive outages the country had seen in recent memory.

Millions of subscribers lost mobile and internet connectivity. Payment terminals went offline. Public services stuttered, and emergency systems felt the strain. For nearly 15 hours, the engineering teams trying to fix it were working with incomplete information, stitching together fragmented logs and partial traces, hunting for a root cause that was hiding in plain sight.

The issue was unfolding in the data plane, where real user traffic flows, while control-plane signals continued to indicate normal operation. Beneath the surface, routing loops and forwarding failures were actively degrading performance, yet the tools and metrics in place weren’t designed to detect them.

This disconnect between what the network reports and what customers actually experience is a gap operators often face, and one they can no longer afford to ignore. As AI takes on an increasingly central role in operating and optimizing next-generation networks, the user plane will become even more critical.

The Illusion of Visibility

Here’s the uncomfortable truth: control-plane monitoring tells you whether your network is technically “up” and running. It does not tell you, however, whether your customers are actually receiving the services they’re paying for. Sessions can be active, dashboards can look normal, and KPIs can all be green. All the while, your customers may experience buffering, dropped calls, failed transactions, and degraded app performance.

A recent GSMA survey, conducted in partnership with RADCOM, revealed that only 41% of operators have built an end-to-end architecture that integrates data across all departments. That means nearly six in ten operators are making critical, time-sensitive decisions without a complete picture of what’s happening at the user–plane level.  In a world where customers expect seamless connectivity and will switch providers without hesitation when they don’t get it, that’s not a monitoring gap. It’s a competitive liability.

Agentic AI Needs Real Data to Do Real Work

The industry is moving fast toward agentic AI. These systems don’t just flag anomalies but actively investigate, prioritize, and remediate them. The promise is enormous: faster resolution times, fewer human escalations, and proactive fixes even before customers notice a problem. However, agentic AI is only as smart as the data it’s working with. Feed it incomplete inputs, and it will confidently and at scale make incomplete decisions.

Consider the difference between the two scenarios. In the first, your AI agent sees “packet loss detected” and “cell utilization at 65%.” It has generic signals to work with and will respond accordingly, likely deprioritizing the issue because utilization isn’t critical. In the second, that same agent knows that the packet loss is specifically degrading video streaming traffic on a particular UPF path, affecting a measurable segment of subscribers at exactly 9 PM on a Tuesday. Now it has something actionable.

The difference between these two scenarios isn’t model quality or compute power. It’s user-plane data. Without granular, real-time visibility into what is actually happening at the data plane, agentic AI ends up optimizing for metrics that don’t map cleanly to customer experience. It can automate fixes for the wrong problems or miss the ones that are quietly eroding satisfaction and driving churn. The technology becomes a faster version of the old approach, not a fundamentally better one.

What Full Visibility Actually Looks Like

RADCOM ACE, RADCOM’s AI-native, end-to-end assurance platform correlates user-plane data, i.e., the real traffic flows, application behavior, session quality, and service interactions, all with control-plane signals, and in real time. RADCOM’s High Capacity User Analytics solution captures 100% of user-plane traffic, rather than sampling or approximating, delivering the full picture at bandwidths that keep pace with modern network demands.

With this foundation in place, RADCOM ACE can do what wasn’t possible before. These include:

• Measuring application-level quality of experience on a per-session basis
• Detecting SLA violations as they happen rather than after the fact
• Identifying exactly where in the network a failure is originating and how it’s propagating
• Offering agentic systems with grounded, accurate inputs so they can take the right action

This goes beyond faster troubleshooting. RADCOM enables operators to fundamentally transform how they understand and manage the customer experience. By correlating granular, real-world user experience data with network performance, operators can move beyond proxy metrics and optimize directly based on what customers feel in real time. This drives measurable improvements in service quality, assurance, and customer experience.

The Stakes Have Never Been Higher

Customer expectations for connectivity have been climbing for years, and the rise of AI-powered services is accelerating the shift. Today, subscribers no longer think in terms of network architecture; they think in terms of outcomes: whether a video call holds, a payment completes, or an application responds instantly. When experience degrades, it is immediately visible to the customer, even when traditional network dashboards fail to reflect it.

Deploying agentic AI without user-plane visibility is like equipping a highly skilled analyst with incomplete data. The capability exists, but its full potential remains out of reach. In fact, it risks producing confident but incorrect conclusions.

Operators who close this visibility gap will be best positioned to realize the promise of AI-native networks, enabling faster resolution, proactive service assurance, and truly differentiated customer experiences. Those who do not will continue to face familiar challenges, only with more advanced tools.

Ultimately, the user plane is where customer experience truly happens. It’s time to start treating it that way.

Visit https://radcom.com/high-capacity-user-analytics/ for more info on RADCOM’s High Capacity User Analytics or contact us for a demo at [email protected]