Customer experience is having a ‘moment’ with it sinking to unprecedented lows across all businesses and industries. In telecom, only 35% of customers report satisfaction with their current provider’s customer service and half of customers say they are prepared to pay a premium for exceptional customer experience. This reveals a substantial gap in the market which is expected to change with the introduction of agentic AI, resolving 80% of common customer services issues by 2029.
The question, however, is: can agentic AI (AAI) truly live up to its promise? Is it just another hype cycle, or will consumers finally be able to converse with telecom robots? And how can telecom operators reap real value from this disruptive technology?
The benefits of agentic AI are numerous. Agentic AI combines multiple AI models that understand and interpret data and react to predefined tasks. The agent does not just suggest an outcome but rather decides the best way to achieve the intended result. AI agents collect data from various sources and independently act in real-time with minimal human supervision. Furthermore, AI agents can communicate with each other and drive a multi-task workflow successfully. This means that telecom networks have the potential to truly metamorphosize into autonomous systems, managing complex tasks, understanding priorities and proactively making modifications.
Some examples include telecom customer care operations that can assign a team of AI agents to handle customer complaints in real-time, which validate and successfully resolve any issues. Or network operation centers that can allocate a team of AI agents to assess the impact of service incidents, prioritize them, investigate the root cause analysis and suggest remediation.
It is no surprise, then, that agentic AI is gaining traction, with 48% of tech leaders already implementing it within their organizations. Fueled by the need to streamline network operations and reduce reliance on manual processes, the telecom sector is poised to see a 62% increase in AI investment by 2029, reaching $22 billion.
AAIs Customer Experience Data and Insight Foundation Layer
Agentic AI models enable a huge leap forward for mankind. However, for telecoms to reap the real benefits of agentic AI, data needs to become the foundation stone. The bedrock of telecom agentic AI needs a deep understanding of the customer experience, driven by real-time data across the network, from end-to-end. This means that complete subscriber-level information, built around real-time, correlated trusted data, is required to drive customer care, predict customer behavior, and ensure thorough root-cause analysis.
This level of granular information will enable agentic AI to analyze customer feedback, understand why they are most likely to churn, and ensure loyalty. It may even offer hyper-personalized services, adjust service configurations, and quality of experience to accommodate each customer. However, only with a customer experience insight (CEI) foundation layer, built on trusted data, will agentic AI transform the network into a customer-centric system. And in turn, this will enhance the customers’ satisfaction levels.
These deep data insights will then be able to power agentic AI’s reasoning and automation capabilities, predict when a customer will be happy, optimize processes and resolve complex network issues.
RADCOM’s ACE platform and embedded solutions incorporate best-in-class, future-ready user and service analytics. From a data and insight foundation layer to advanced prediction models, RADCOM leverages agentic AI automation layers to enhance the operators’ network and subscriber experience.
RADCOM’s customer experience insight (CEI) foundation layer is designed to monitor tens of millions of connected devices, high-speed voice and data services, and changing conditions across all areas. Incorporating years of experience in the telecom domain, RADCOM collects data from numerous sources spread across the network, often in silos, offering a complete understanding from the RAN to the core. The solution leverages accelerated computing technology to uniquely offer ultra-high capacity processing at low total cost of ownership, while providing real-time, per-user and service analytics. These include insights into user trends, location intelligence, usage patterns, service interactions, and more, with a 360-degree view of the customer experience.
Data, Insights and Automation
RADCOM is collaborating with leading business process management vendors to leverage agentic AI for expanding beyond the traditional service assurance domain. With user and service insights available in real-time, customers can now intelligently automate core business processes in customer care, service management and network optimization.
The agentic AI powered customer complaint handling process, for example, offers validation, verifies whether a complaint is tied to a real network issue, correlates with similar complaints, and suggests a resolution. Furthermore, RADCOM’s AI agents prioritize the worst “offenders”, enabling the engineering team to troubleshoot and resolve the most serious issues quickly before they escalate. This improves first-call resolution rates, reduces ticket-handling time, and lowers the volume of tickets.
AI’s Conditional Value
Agentic AI may be taking off at super-fast speeds, but as Deepika Giri, head of research, Big Data & AI, at IDC Asia/Pacific, said, “The underlying data ecosystem must evolve to support agent-based architectures by enabling dynamic data pipelines that facilitate the seamless flow of multimodal data across systems.” Solutions like RADCOM offer telecom operators just this – facilitating seamless flow of multimodal data across systems. Real-time subscriber-level analytics with complete network visibility and agentic AI’s intent-prediction ensures a powerful combination. As the IEEE noted, “For telecoms to reap the real benefit of it, (they) need a comprehensive understanding of the customer experience combined with real-time data”.
