Using AI to Grow Revenue from New Real-Time 5G Services

New technologies offer mobile operators the opportunity to grow revenue in line with rising usage. AI tools can correlate usage patterns and uncover new ways to identify and support high-value users. Alongside AI, the arrival of 5G-Advanced and 5G standalone brings new tools to improve mobile network experience in key locations for those users. The goal is to boost loyalty and raise revenue. AI agents also improve network automation, making it possible to implement real-time adjustments that help key users.

It’s widely accepted that early 5G deployments failed to deliver an uplift in smartphone average revenue per user. Operators created new revenue streams from fixed-wireless-access offerings that benefited from the increased mobile network capacity gained from large amounts of new mid-band spectrum. However, the smartphone experience saw little difference. It was faster, but when the new spectrum filled up, it still faced problems at busy times in peak locations, on cell edges and outside the reach of the 5G mid-band spectrum in rural and suburban areas.

Mobile Data Volumes Will Continue to Rise Steadily

Despite market cynicism, mobile data usage continues to grow. Yes, the rate of growth has slowed, but it remains high. The exceptional growth rates of the period from 2019 to 2021 were boosted by a supply shock in the arrival of large amounts of C-band spectrum. They’re not a good comparison to the long-term ongoing trend of rising data usage.

Although there has been little new spectrum in the market in the past few years, mobile data still enjoys double-digit growth. Ericsson reports year-on-year mobile data growth of 20% — at this rate, mobile data volume will double approximately every four years. Similarly, Nokia predicts that wireless consumer data traffic will increase fourfold between 2024 and 2035, with a compound annual growth rate of 18%. Operators must find ways to boost revenue to adapt and raise profitability.

5G standalone is now a mainstream part of mobile operator deployments, but most operators haven’t yet used the new capabilities that it enables. Business teams must recognize that 5G standalone and 5G-Advanced finally give them the tools that were hyped by mobile suppliers 10 years ago, but which didn’t arrive with the non-standalone technology used for early 5G launches.

Operators Must Use 5G-Advanced to Improve Profitability

5G-Advanced allows operators to finely manage radio priorities for high-value users in busy locations. These users generate a disproportionate amount of revenue and, if they change provider, have a major impact on profitability.

Operators in China are already marketing 5G-Advanced packages using AI technologies which offer improved experience. China Unicom has focused on improving the uplink performance in a very large Ginseng market in Jilin. ZTE reported that its solution delivered a 583% increase in uplink capacity. Uplink is becoming increasingly important as more users make video calls or share live streams on social media. Historically, maintaining uplink performance was challenging because of the compact antennas on users’ devices, and their limited transmit power when communicating with a base station.

In Thailand, AIS used ZTE’s Air RAN solution during the Big Mountain Festival which hosted tens of thousands of people. Downlink utilization exceeded 80% and uplink rose above 60%, managed by an embedded intelligent computing board used to upgrade to an existing baseband unit. AIS reported that TikTok throughput was 24% higher and Line instant messaging increased 32%.

AI Aims to Deliver Dynamic Real-Time End-to-End Network Coordination

AI tools help operators to use the new capabilities of 5G-Advanced and automate key processes. Without this automation, operator teams will find it harder to dynamically respond to their competition, create flexible tiers for high-value users and deploy prioritized network experiences at concerts, sports arena and other short-term events.

Another capability that supports these experiences is network slicing. To date, most slices have been long-lived and operators have deployed a small number of slices at once. With greater network automation, business teams have more opportunities to dynamically create slices for key user segments, locations or events, and assure them so that they deliver on promises made to customers.

Importantly, AI-powered automation also removes silos within operators. These experiences must work end-to-end, with the core network and radio network coordinating and aligned to support user needs. ZTE is extremely active in marketing the benefits of agents to coordinate functions end-to-end, for example using its AirEngine plug-in board. It also uses multiple agents that tackle specific areas while collaborating to enable policies that span user profiles, radio cell settings and core network prioritization.

Segmenting the Real VIP Users With AI

One of the major strengths of machine learning and AI is to correlate metrics and uncover trends. User behaviour on mobile networks is incredibly complicated as it spans location, time, apps and multiple devices. Further complicating this is that users’ behaviour patterns are different when working compared with during leisure time. Segmentations have traditionally only tapped into a fraction of this complexity. With AI-powered tools in core networks and business support systems, operators have new ways to dynamically segment users and uncover patterns that they can target with premium packages or add-ons to boost revenue.

The new AI-powered RAN and possibilities for end-to-end assurance allow that understanding to be monetized. The goal is to boost loyalty and reduce churn at the same time as selling new services and generating revenue.