Yesterday, a STL Partners webinar titled “Turning autonomy into margin: Agentic AI and the autonomous RAN,” suggested agentic AI is the missing layer that can turn RAN autonomy from a technical goal into a direct profit margin booster. It argues that operators should prioritize autonomy use cases by business impact, not just by how much automation coverage they add, and that the right roadmap can move autonomy from an engineering KPI to a commercial advantage.

The central message was that autonomy only matters if it improves economics (see poll results below). The webinar revealed that network operators need a dual-axis framework that combines the usual autonomous-network maturity view with a value-creation lens, so they can focus on the capabilities that scale into measurable business outcomes.

Agentic AI is presented as the practical enabler for moving beyond human-in-the-loop operations. In this framing, agents help orchestrate tasks, make decisions, and coordinate network actions in ways that support more closed-loop automation than traditional workflows can deliver.

The results of an “actuality” poll relating to RAN autonomy revealed that controlling costs and reliability were most important, with the enablement of new revenue growth through APIs and sensing only scoring 10.87% of respondents.  Similarly, results for an “aspirations” poll for RAN autonomy were also fairly evenly spread between reducing costs and optimizing the customer experience, with just 13.21% citing new revenue growth.

Source: STL Partners

Terje Jensen, SVP, global business security officer and head of network and cloud technology strategy at Telenor, said that he had expected to see network operators’ aspirations shift more clearly towards improving customer experience and even revenue generation, not just efficiency.

Darwin Janz, strategic technology planner at SaskTel, also thought network operators’ ambitions would be higher, but he noted that they still struggle to identify concrete, monetizable use cases. Without that, there’s a real risk of building technical solutions in search of a problem, rather than starting from clear enterprise needs and value, Darwin noted. “We really need to see those use cases and enterprise customer needs,” he added.

……………………………………………………………………………………………………………………….

The webinar was built around four practical questions:

1. Which use cases create real commercial impact?
2. How to shift from autonomy as an engineering metric to a margin driver?
3. Where agentic does AI add value today?
4. What data, orchestration, and organizational foundations are needed to scale beyond pilots.

For network operators, the implication is that autonomous RAN strategy should be tied to P&L outcomes such as lower operating cost, better resource utilization, and faster optimization cycles. The webinar’s message is that autonomy becomes strategically important only when it is deployed in a way that compounds across the network and business.

…………………………………………………………………………………………………………………..

References:

https://www.lightreading.com/network-automation/telcos-showing-limited-aspiration-for-ran-autonomy-benefit

The Financial Trap of Autonomous Networks: Scaling Agentic AI in the Telecom Core

Nokia to showcase agentic AI network slicing; Ericsson partners with Ookla to measure 5G network slicing performance