Cloudera has joined the AI-RAN Alliance, a global consortium dedicated to integrating artificial intelligence into telecommunications infrastructure. The move places Cloudera alongside companies such as NVIDIA, Dell, SoftBank, T-Mobile, KT and LG U+, with a shared goal of developing intelligent, AI-driven telecom networks.
Supporting edge AI and hybrid MLOps for telecoms
The AI-RAN Alliance aims to standardise how AI is integrated across radio access networks (RAN), focusing on edge computing, real-time data orchestration, and hybrid machine learning operations. As telecom operators move toward more virtualised infrastructure, AI presents an opportunity to improve service efficiency and unlock new commercial models. However, deploying AI at scale across distributed networks remains complex.
The Alliance, which includes founding member NVIDIA, was formed to address these challenges. Its members are working on shared infrastructure for AI optimisation, accelerating the development of edge AI applications and establishing real-world use cases to support the reliable rollout of AI in telecom networks.
Cloudera’s entry into the Alliance brings its experience in enterprise AI, data analytics and hybrid cloud architecture to the table. Its platform enables telecom operators to deploy, manage and scale AI workloads across hybrid, edge, and on-premises environments.
Focus on data orchestration and AI-native use cases
Cloudera will participate in the new ‘Data for AI-RAN’ working group, which focuses on standardising data orchestration, network automation powered by large language models (LLMs), and enabling hybrid MLOps across telecom AI workloads.
“Our goal is to help define the data standards, orchestration models, and reference architectures that will power intelligent, adaptive, and AI-native networks of the future,” said Abhas Ricky, Chief Strategy Officer at Cloudera. “Given our leadership in the domain — having powered data and AI automation strategies for hundreds of telecommunications providers around the world — we now look forward to accelerating innovation alongside fellow AI-RAN Alliance members, and bringing our customers along.”
As part of its role, Cloudera will also contribute to developing and validating reference architectures that operators can deploy in real environments. These models are expected to shorten the time between innovation and implementation, and support use cases such as real-time anomaly detection and SLA-driven network availability.
Regional commitment and industry collaboration
The company’s involvement is seen as particularly significant in Asia Pacific, where Cloudera aims to help regional telcos build more intelligent and efficient networks.
“We’re excited to join the AI-RAN Alliance and meaningfully contribute our data and AI platform expertise to help telcos across Asia Pacific build smarter, more efficient, and reliable telecom networks,” said Remus Lim, Senior Vice President, Asia Pacific & Japan, Cloudera. “Together, we want to unlock AI’s full potential to help telcos optimise costs, grow their revenues sustainably, and transform their networks into intelligent platforms that drive real-time innovation and long-term success.”
Other Alliance members welcomed Cloudera’s addition. “Cloudera is an incredible addition to the AI-RAN Alliance,” said Dr. Alex Jinsung Choi, Principal Fellow at SoftBank’s Research Institute of Advanced Technology and Chair of the Alliance. “The company’s leadership in data and AI, combined with their extensive telecommunications footprint, will play a vital role in advancing our shared vision of intelligent, AI-native networks.”
Jemin Chung, Vice President of Network Strategy at KT, added, “As AI becomes increasingly central to next-generation networks, the ability to harness data securely and at scale will be a key differentiator. Through this initiative, we look forward to defining best practices that enable AI-centric RAN evolution and improve operational intelligence.”
Cloudera’s platform will be used to demonstrate real-time decision-making at the edge, enabling scalable training data preparation, operational AI deployment and ensuring governance and orchestration from edge to core.
