AI to curtail revenue leakage in 5G roaming connections

AI to curtail revenue leakage in 5G roaming connections Ryan is a senior editor at TechForge Media with over a decade of experience covering the latest technology and interviewing leading industry figures. He can often be sighted at tech conferences with a strong coffee in one hand and a laptop in the other. If it's geeky, he’s probably into it. Find him on Twitter (@Gadget_Ry) or Mastodon (@gadgetry@techhub.social)


According to Juniper Research, AI solutions will curtail “revenue leakage” in 5G roaming connections.

The research suggests that average revenue leakage per 5G roaming connection will decrease from $1.72 to $1.20. This significant reduction is attributed to the strategic implementation of AI-based segmentation by telecom operators, marking a pivotal advancement in monetising data-centric users.

Revenue leakage pertains to the value of services provided but not adequately monetised, a challenge that the telecoms industry has grappled with. Juniper Research’s latest findings indicate that AI-based segmentation solutions play a crucial role in addressing this issue by enhancing the allocation of resources and introducing new pricing models, particularly in the realm of 5G standalone networks.

The key driver behind this reduction is the ability of AI-based segmentation to discern and categorise traffic types and segments in real-time, thus enabling operators to better monetise emerging roaming services.

By leveraging machine learning models, operators can differentiate enterprise traffic by use case and facilitate premium billing for mission-critical 5G standalone connections.

According to research author Alex Webb, AI-based segmentation “will differentiate enterprise traffic by use case; enabling premium billing of mission-critical 5G standalone connections, thus reducing revenue leakage.”

The report, titled ‘Global Roaming Clearing Market: 2023-2028,’ recommends that operators adopt AI segmentation tools to combat revenue leakage from 5G roaming on standalone networks.

As 5G standalone networks utilise the 5G core – as opposed to the 4G infrastructure relied upon by 5G non-standalone networks – individual pricing strategies must be employed for each type of network. This ensures that the pricing accurately reflects the Quality of Service (QoS) offered by these networks, considering factors such as higher throughput and lower latency.

In essence, the adoption of AI-driven segmentation tools emerges as a critical strategy for telecom operators to optimise network resource distribution, identify enterprise traffic suitable for use case-dedicated network slices, and ultimately curb revenue leakage in 5G roaming connections.

The full report is available here (paywall)

(Photo by Ian Talmacs on Unsplash)

See also: AT&T plans most wireless traffic to flow across Open RAN by 2026

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