When a service issue strikes, customers aren’t thinking about network layers or fault domains — they just want their connection back. A call that won’t go through, a frozen video chat, or a buffering stream instantly turns convenience into frustration. In that moment, it doesn’t matter where the fault lies, it feels personal. A few bad experiences quickly spiral into public complaints, brand damage, and lasting loss of loyalty.
EE and BT discovered this the hard way in July 2025 when a network outage affected thousands of their customers over a lengthy two-day period, with major news and tech outlets picking up the story. Many of their customers were unable to make or receive calls, with some customers prevented from accessing the operator’s helplines or emergency services.
Turning Bad CX into an Opportunity
Operators anticipate some network issues — but when outages disrupt the customer experience, the actual cost goes far beyond technical downtime. Satisfaction drops, loyalty wavers and retention suffers. According to McKinsey, 73% of telecom executives cite customer experience as their top driver of differentiation, while 38% link customer churn directly to network performance issues. For an industry that promises seamless connectivity, it’s striking how often customers feel dissatisfied with their experiences.
Significant changes however are on the horizon. Findings from recent independent research, by RADCOM together with LightReading survey, , revealed a strong industry momentum towards integrating AI-powered solutions within the next six to twelve months. According to the survey, up to 78% of respondents intend to connect customer care and subscriber platforms, as well as trouble ticketing systems, with AI-driven assurance capabilities.
This shift marks a move beyond initial experimentation with AI. Telecom operators are increasingly embedding AI into the core of their business operations, progressing into more collaborative and integrated approaches. As this transition unfolds, the impact on customer experience is expected to be substantial, fundamentally enhancing how issues and anomalies are addressed and solved – and fueling a growing reliance on intelligent automation among operators.
AI Agents To Ease the Burden
The adoption of AI agents is set to further transform the quality of service that customers receive. Unlike traditional systems, AI agents are dynamic — they learn, reason, and evolve, driving a true shift in how problems are identified and repaired. Working alongside customer care teams, these intelligent agents can address issues in real time, reducing average handling times and easing the heavy troubleshooting workload on engineers. In the near future, customers may even have their own personal AI agents capable of managing all their service needs autonomously.
The vision is exciting. AI agents promise faster resolutions, while allowing customer care teams to focus on higher-value tasks such as personalization and proactive engagement. In practice, however, the path to success has proven more complex than anticipated with research showing 65% of AI initiatives have not yet delivered their expected value.
AI Agents Need End-to-End Data
Enhancing the customer experience, whether through human support or AI agents, begins with a complete end-to-end view of the network, from the RAN to the core. Yet, despite the critical importance of this capability, only 24% of telecom operators report having complete, end-to-end insight into their networks. Without it, AI systems and customer service teams are operating only with partial insight, making problem resolution slower and less effective.
Comprehensive network visibility is the foundation for effective problem resolution, whether handled by human experts or AI agents. Informed strategic decisions hinge on a deep understanding of the customer experience. This requires access to real-time data across the entire network. By systematically capturing every input—from Open RAN systems, traditional trace sources, or distributed networks encompassing numerous remote cell sites, a holistic perspective must be achieved. Data collected and analyzed across every segment can then support intelligent decisions that prevent degradations and anticipate customer needs. AI then takes this a step further, predicting and preventing future issues before they impact the customer experience.
RADCOM’s Agentic AI Layer: The End-to-End Experience
RADCOM’s Agentic AI solution, delivers a comprehensive understanding of the network by leveraging insights into user trends, location intelligence, usage patterns, service interactions and more. By continuously monitoring tens of millions of connected devices, high-speed voice and data services end-to-end, it ensures attention is given to both network performance and customer-centric issues. With hundreds of performance and quality metrics spanning all technologies, RADCOM highlights exactly where improvements are needed. This helps maintain optimal network performance and deliver a superior customer experience.
RADCOM’s Agent Accelerates Ticket Resolution
One of RADCOM’s AI Agents accelerates ticket resolution, including complaint resolution both during and after the call. The agent processes tickets assigned to the network, including the background workflows that interface with the service ticket platform, and analyzes the complaint in raw textual form. It then validates the tickets by correlating with RAN and core network faults and the relevant KPIs. Prioritizing the worst defect, engineers can resolve the most serious issues fast before they escalate.
RADCOM Predicts the Next Complaint
An additional RADCOM AI Agent helps pre-empt issues that could lead to grievances. It applies predictive analytics and enables pre-emptive service optimization along with specific data and subscribers’ KPIs. The agent then generates a model that can be applied to the entire subscriber base, driving proactive mitigation of potential issues that may arise.
Reaping Real Value from Agentic AI As agentic AI continues to mature, its impact on customer experience will only grow. Unlocking its true potential, however, demands a fundamental shift in how operators view the network and where and how they gather data. The potential benefits of autonomous agents to deliver personalized, proactive, and highly efficient customer experiences are numerous. Nevertheless, realizing its promise requires a holistic network perspective and actionable insights that enable intelligent, data-driven decisions at every level.
Contact us today for more information on RADCOM’s Agentic AI solutions.
