TechForge

10th March 2026

As Indosat scales its AI-RAN infrastructure, telecom leaders are gaining a potential real-world blueprint for improving network efficiency.

Telecoms execs face continuous pressure to extract better returns on investment from their latest cellular rollouts. Consolidating hardware offers a pathway to reduced capital expenditure and new service models.

Following a commitment announced at MWC alongside Nokia and NVIDIA, Indonesian operator Indosat is pushing past laboratory concepts. The company aims to establish a broader AI grid that serves both urban centres and rural communities.

Validating AI-RAN hardware for network efficiency

Processing radio access operations and AI applications on shared GPUs requires careful execution. Indosat validated this shared hardware model by executing the first AI-driven 5G call in the Southeast Asian region.

During the live demonstration, operators showcased ultra-low latency capabilities by remotely controlling a robot situated in Surabaya in real-time.

Replacing legacy hardware with modern compute clusters requires adapting operational practices and developing local expertise. To bridge the skills gap, Indosat launched a dedicated facility in Surabaya. Students from leading local universities will partner with the operator to develop use cases spanning healthcare, education, and agriculture.

Vikram Sinha, CEO of Indosat, views this social impact as a core business driver. “When you talk about AI-RAN, I think it is much more than technology,” he noted. “We are working hand-in-hand on making sure that what we do helps people.”

Building collaborative infrastructure models

Technology directors evaluating private networking solutions can look to this AI-RAN deployment as an example of cross-industry partnership in action. Expanding advanced network architecture requires breaking down internal silos and participating in broader ecosystems.

A wider industry consortium is already forming, featuring players like Nokia, NVIDIA, Indosat, SoftBank, and T-Mobile US. These collaborative groups allow participants to pool resources, share implementation lessons, and distribute development costs.

Sinha advises peers to commit fully once they decide to adopt these new infrastructure models. “First thing first, you have to believe in it,” he remarked. “And if you believe in something, go all in,” he added.

The cooperative model is proving its viability despite early doubts from some observers. Technology like AI-RAN holds value only if it generates tangible operational efficiency improvements and solves actual problems for network users and businesses.

See also: Qualcomm: Prepping telecom infrastructure for AI-native 6G rollouts

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About the Author

Senior Editor

Ryan Daws is a senior editor at TechForge Media with over a decade of experience in crafting compelling narratives and making complex topics accessible. His articles and interviews with industry leaders have earned him recognition as a key influencer by organisations like Onalytica. Under his leadership, publications have been praised by analyst firms such as Forrester for their excellence and performance. Connect with him on X (@gadget_ry), Bluesky (@gadgetry.bsky.social), and/or Mastodon (@gadgetry@techhub.social)

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