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TELUS is using its brownfield Open RAN transformation as the operational foundation for AI-RAN and broader AI-enabled automation.
For TELUS, Open RAN is increasingly about more than disaggregation or supplier diversity. The Canadian operator’s brownfield transformation illustrates how openness, virtualization and programmability can create the foundations for a more intelligent network — and, ultimately, for AI-RAN.
The starting point was unusually pragmatic. TELUS was already facing a major equipment transition driven by hardware lifecycle requirements, changes to Canada’s telecom supply-chain rules and its evolving vendor strategy. Rather than simply replace existing equipment, the operator used that refresh cycle to change the RAN architecture itself.
“We were in our hardware refresh cycle, and we were anyway swapping our network,” TELUS Director of RAN Strategy Sushil Rawat said. “So it helps when you’re riding a ongoing hardware refresh cycle and just change the architecture because then the technology itself does not cost more to do that truck rolls and and make those changes in the network.”
That alignment speaks to the economics of brownfield Open RAN. Replacing equipment with significant residual value can undermine otherwise compelling TCO assumptions. For TELUS, architectural transformation became part of work that already had to happen. As Rawat put it, “It’s it’s out of necessity. It’s not just out of choice of a technology that you make.”
TELUS’ resulting architecture is deliberately multivendor. Samsung provides key elements including virtualized RAN software, radios, orchestration capabilities and the RIC platform, while the deployment also incorporates third-party radios, COTS servers, an independent cloud layer and applications from multiple suppliers.
The important point is that TELUS sees openness as something that has to work operationally, not merely exist in a specification. “We have at least kept this principle where we will have openness in the architecture, and not only on paper, but also exercise having interoperability with third party,” Rawat said.
That architecture is now scaling quickly. Rawat said roughly 25% of the network was running Open RAN as of July 2026, with TELUS targeting approximately 40% by year-end, 50% by the end of 2027 and 100% by the end of 2029.
But the more consequential shift may be operational. TELUS’ original Open RAN business case included the SMO, RIC, tool consolidation and simplification of its automation environment. Those same architectural elements create natural insertion points for AI.
Rawat described current AI-for-RAN work as an evolution of automation. TELUS is applying smaller AI agents to repeatable operational tasks while treating less deterministic activities more cautiously. “I would call it an extension of automation, which is more self-defined,” he said. “Now, with the help of AI, I think it is becoming more reusable and easier to configure an AI agent to to develop certain use case.”
For TELUS, however, AI-RAN ultimately has to translate into measurable network performance. “When it comes to from my perspective, AI RAN is how does AI increase the efficiency of the RAN stack that is deployed, right?” Rawat said. “How do we deliver more data? How do we deliver more data using the same spectrum asset that you have?”
That outcome-driven approach extends to accelerated compute. Rawat said he does not currently see a need to deploy GPUs at cell sites over the next 12 months, although TELUS is already using accelerated computing centrally for model training and anomaly detection. If new technology delivers performance unavailable today, however, “There might be an opportunity to do that.”
The harder problem is governance. Once AI agents move from analysis to making changes in a production network, TELUS sees identity management, access control, conflict management and established change-management processes as essential.
“You can build a use case. You can demonstrate it in lab, quick and easy,” Rawat said. “Taking it to the production, scaling it for day-to-day operation. This is a very important aspect of it.”
TELUS’ journey points to a broader relationship between Open RAN and AI-RAN. Openness does not automatically make a network intelligent. But by separating hardware and software, introducing programmable control layers and enabling multivendor applications, Open RAN creates an architecture in which intelligence can be introduced more rapidly — and progressively moved from recommendation toward autonomous action.
