Appledore on the present and future of agentic AI in telecom

By Sulagna Saha April 2, 2026

Collected at: https://www.rcrwireless.com/20260402/test-measurement/appledore-on-the-present-and-future-of-agentic-ai-in-telecom

Operators are seeing more success with agentic AI where use is localized, not cross-domain, said Patrick Kelly of Appledore Research

Although the telecom industry has been typically slow in its uptake of new technologies, a shiny new tech has caught their fancy, and it has been peppering telco conversations these past few months. It’s agentic AI. 

Communications service providers (CSP) are getting up to speed with agentic AI, with many beginning to experiment with agentic tools to refine their operating models. 

In a newly-published report, Appledore Research digs into the early business impacts of agentic AI in telecommunications. In this episode of RCR TV program, Pulse, I sat down with Patrick Kelly, founder and principal analyst, to understand some of the ways operators are using the technology today — and what lies ahead. 

For years, rule-based systems and analytics have been CSPs’ go-to for network operations. But a complexity sprawl, growing customer expectations, and intermittent network issues causing sluggish services in peak hours, are forcing them to look for new ways to optimize operations. 

During his research over the past five months, Kelly has found that the impact of agentic AI has been profound across CSPs, but “tightly bound” at this stage.

“It’s a fairly nascent market right now,” Kelly said. “Just from our point of view, we see a lot of proof of concepts [PoCs]. And we think we’ll see some of those PoCs make their way commercially into the marketplace.”

At present, there are a handful of use cases that CSPs have their eyes on. Key among them are fault isolation, root cause analysis, and network performance analysis.

“There’re tens of thousands of alarms that come into every Tier 1, Tier 2 operators’ network every day. The fundamental problem is how do you eliminate the noise and really get your teams focused on the root cause of that problem.”

To cut the noise and the grunt work that comes with it, some CSPs are tapping into agentic AI tools for automating network monitoring, identification of anomalies, and root cause analysis. AI agents can observe the network around the clock, isolate issues and flag them in real time — sometimes even before they occur — and effectively shorten root cause analysis which is typically a long and winding workflow, ensuring faster mean time to repair (MTTR).

With telco networks becoming increasingly cloud-native and software-dependent, operational complexities have been on the rise. “I think this is where this technology can help optimize and maybe provide a little more productivity to the teams that are dealing with a lot of these issues.” That he said will enable them to make services perform better at the user end.

However, the best opportunity for operators to leverage agentic AI, according to Kelly, is to optimize the mobile radio access network [RAN] where AI can enable cell sleeping for better energy-efficiency, unlock dynamic resource allocation, and help transition from manual and static configuration to self-optimization.

A key takeaway, Kelly noted, is that operators are seeing more success where implementation is domain-specific. “So rather than trying to go cross domain, looking at a specific area of workflow in their business, bound that, and then really focus on that,” he said. 

According to Appledore’s estimation, the global agentic AI market is set to reach $6.2 billion by 2030, up from just $92 million in 2025. Kelly predicts investments to flow into four core areas: digital enablement, service management and operations, network security, and IT and enterprise resource planning (ERP).

As for whether there is a risk of agents replacing human engineers in the future, Kelly said that the narrative is overblown. “I see it more as a productivity enhancer. All of the use cases with the operators we’re talking to, they’re still looking at risk mitigation.” Which makes it unlikely for them to rely entirely on agents. 

“I still see human experts in the loop for the foreseeable future,” he concluded.