Artificial intelligence (AI)-infused radio access network (RAN) technology celebrated a loud first birthday at this week’s Mobile World Congress (MWC) Barcelona event, highlighted by a strong focus on opportunities but also highlighting a long road AI-RAN still has to travel.

“Formal” efforts toward unifying AI-RAN began just ahead of last year’s MWC Barcelona event, when a handful of big-name vendors and operators through their support behind the aptly named AI-RAN Alliance organization. Those names included Amazon Web Services (AWS), Arm, Ericsson, Microsoft, Nokia, Samsung Electronics, SoftBank, Nvidia, DeepSig, T-Mobile US, and Northeastern University.

The framing goal of the group steer the use of AI into RANs for better performance, lower operating costs, greater efficiencies, and to support new business models. That work was to include using AI to improve RAN spectral efficiency, combine the two for more efficient network utilization, and deploy AI at the network edge to support new services.

Those goals did progress over the proceeding 12 months, with a number of operators and vendors pushing AI-RAN agendas.

One of the more notable moves came late last year when T-Mobile US partnered with Nvidia, Ericsson, and Nokia on an AI-RAN Innovation Center that will house a focused effort on tying together cloud-based RAN and AI development. The carrier noted in a presentation that the goal is to integrate cloud-based RAN and AI using unified infrastructure that can scale to serve millions of mobile users at once.

“AI-RAN will enable new AI algorithms to unlock the full potential of wireless networks,” T-Mobile US’ presentation noted. “These AI algorithms would be rapidly developed with software-defined RAN, trained on AI data centers, and fine-tuned with physically accurate digital twins. This will lead to dramatic improvements in spectral and energy efficiencies.”

That momentum continued to the lead up of this week’s MWC Barcelona event, including Verizon tapping Samsung and Qualcomm for a multivendor deployment using an AI-infused RAN management application running on a RAN intelligent controller (RIC).

AI-RAN Alliance membership growth also surged over the past year, with the organization touting 75 total members. That organization’s growth was also highlighted by it naming former head of the O-RAN Alliance to head the AI-RAN Alliance work.

Analysts have pointed to the benefits AI can bring to the deployment and management of cloud-based open RAN networks, which are more complex orchestration challenges due to the disaggregated multivendor ecosystem. The use of AI could help close performance gaps for open RAN architectures compared with legacy RAN models.

Adam Koeppe, SVP of technology planning at Verizon, explained that Verizon’s broader cloud-based network virtualization efforts have laid the foundation for greater AI usage.

“Where I see our evolution occurring is when you have an advanced cloud platform, as we do, you have an orchestration layer on top that we already have, and you then find ways to incorporate new AI capabilities on top of that, that’s going to allow your engineers and your operators to interface differently. It’s going to allow you to pull different insights out of the customer experience and help inform your optimization of the network for those experiences,” Koeppe said. “But it’s all based on that foundation of having cloud-based infrastructure, deployment of cell-site software, [and an] orchestration layer running on top of that, AI becomes kind of the next steppingstone in that highly advanced network architecture that we’ve already deployed.”

Is AI-RAN on track? That “steppingstone” comment does highlight the continued work that is needed toward realizing this AI-RAN goal. Ian Hood, CTO for telecommunications at Red Hat, noted in a press briefing ahead of this week’s event that there remains some trepidation toward fully embracing any new technology.

“There's always hesitancy in the market to take on new things,” Hood said, referencing the continued challenges around open RAN technology. “We have to make sure that it’s easy enough to automate and scale and deliver those business benefits to that portion of the network. … So we're going to make this so that it’s easy to add this and add that value to this business. So there is some hesitancy, but we're working through this, and it's an ongoing effort for our industry.”

Chivas Nambiar, GM of telco at Amazon Web Services (AWS), expressed similar concerns, which could delay the influence of the AI-RAN Alliance and broader adoption of AI-RAN until the next big investment cycle.

“There's a fair bit of work in that alliance to try and figure out what the next phase of running RAN functions on top of GPU accelerated infrastructure looks like. I think that's still pretty early in the conversation,” Nambiar said. “So far, a lot of people are playing around with it, but my expectation, personally, is that as we get closer to that 6G evolution that's where it's really going to start to become a decision point of whether we see the cost and performance benefits of the GPU infrastructure running these functions, and that supersedes what we see in custom built accelerator costs.”

Despite the hurdles, analysts see an AI-RAN opportunity.

Téral Research predicts the global AI-RAN market will grow from $1.7 billion this year to $10.4 billion in 2030, adding that the “current ecosystem is vibrant.”

“Long term, the industry focus among both operators and vendors will continue shifting toward the [AI-RAN] concept, which does not rely on open interfaces for implementation and aims to address the need for better monetizing network assets at the edge,” ABI Research Analyst Larbi Belkhit forecast in a recent report, adding that the RIC “is expected to be a part of this concept; however, an AI orchestrator will be necessary to manage both the RAN and the various AI workloads running on the infrastructure.”