How Enea is Transforming Network Traffic Management with AI

At Mobile World Congress 2026, discussions around AI in telecom focused less on potential and more on practical impact. In a conversation between Enea’s Santiago Bouzas and Omdia’s Roberto Kompany, the emphasis was clear: how AI is being applied today to solve real challenges in mobile networks and deliver measurable value for operators.

At Enea, this shift is already reflected in how we are evolving our traffic management solutions. AI is not being treated as an add-on, but as a core capability that helps mobile network operators (MNOs) maintain visibility in increasingly encrypted networks, improve efficiency, and unlock new revenue opportunities.

One of the most pressing challenges discussed is the rapid growth of encrypted traffic. Technologies such as Encrypted Client Hello (ECH), DNS over HTTPS (DoH), DNS over TLS (DoT), and DNS over QUIC (DoQ) are making traditional deep packet inspection (DPI) far less effective than before. This creates a serious issue for operators, as accurate traffic classification is fundamental to service assurance, policy control, and monetization.

To address this, Enea is introducing AI into its traffic classification engine. By augmenting traditional heuristic-based methods with AI, it becomes possible to identify traffic patterns without inspecting packet headers or payloads. This allows operators to retain visibility even when traffic is fully encrypted, something that is becoming increasingly critical.

This approach has already been validated in live environments. In a recent deployment with a tier-one operator, Enea’s AI-driven classification was able to identify more than 70 applications despite the presence of blinding encryption- demonstrating that this is not just a future capability, but something delivering results today.

Moving Beyond Analytics to Traffic Intelligence

Another key area of innovation is the shift from traditional network analytics to deeper traffic intelligence. Instead of focusing only on network performance metrics, Enea’s new platform enables operators to analyze behavior within the network, opening up new ways to act on that data.

This has immediate applications in areas such as fraud detection. By identifying anomalous subscriber behavior, Enea helps operators detect and prevent charging bypass fraud in real time, mitigating revenue leakage that can reach 2–3% in some cases. These capabilities are also extending into adjacent domains, such as drone detection, through behavioral analysis, reflecting the growing convergence between telecom networks and broader security and regulatory requirements.

Improving Efficiency While Reducing Hardware Dependency

Alongside these new capabilities, efficiency remains a critical focus. As hardware costs continue to fluctuate, operators are under pressure to optimize how they scale their infrastructure. Enea is addressing this by significantly improving the performance and scalability of its software.

The latest software releases are designed to deliver the same level of performance while using up to 60% fewer hardware resources. This has a direct impact on both cost and sustainability, enabling operators to handle increasing traffic volumes more efficiently while reducing their overall infrastructure footprint. In a market where data demand continues to grow, this kind of efficiency is essential.

Enabling New Monetization Opportunities

One of the most interesting shifts highlighted in the discussion is how AI is moving beyond operational efficiency and into revenue generation. Traditionally, AI in telecom has been used to optimize networks and reduce costs, but it is now becoming a key enabler of new business models.

By understanding traffic in real time, without needing to decrypt it, operators can start to offer more dynamic and personalized services. For example, they can provide temporary bandwidth boosts, enhanced connectivity for specific use cases, or low-latency services for applications like gaming. These types of offerings allow operators to better align network performance with user needs while creating new revenue streams.

This reflects a broader industry trend, where traffic understanding is no longer just about managing the network, but about actively shaping the services that run on top of it.

AI as a Strategic Differentiator

What emerges clearly from the conversation is that AI is becoming a strategic differentiator for telecom operators. It is no longer just a tool for improving efficiency, but a way to fundamentally rethink how networks create value.

At Enea, we are embedding AI across our traffic management portfolio to help operators:

• Maintain visibility in encrypted environments.
• Detect fraud and emerging threats.
• Unlock new monetization opportunities.

Conclusion

AI is already reshaping traffic management in real-world deployments. At Enea, we are applying it to address some of the most critical challenges facing mobile network operators today, from encryption and cost pressures to the need for new revenue streams.

The direction is clear: AI is not just enhancing traffic management, it is redefining what is possible.