Nokia and Indosat committed to nationwide AI-powered radio access network (RAN) rollout.

Nokia and Indosat have signed a strategic network modernization and AI-RAN rollout agreement that puts their Nvidia-powered collaboration on a path to actual commercial deployment across Indonesia. The deal makes Nokia the key 5G RAN supplier for Indosat's low- and mid-band 5G rollout nationwide, and formally locks in NVIDIA's GPU-accelerated AI-RAN platform as the compute foundation for both AI-enhanced RAN functions and edge AI workloads on Indosat's network. On the hardware side, the modernization brings Nokia's latest radio portfolio into the network, including the next-generation Habrok and Pandion models, alongside the Levante baseband platform, centralized RAN (C-RAN) systems, and Nokia's network management and automation tools. This represents a full network refresh designed from the start to be AI-ready rather than retrofitted later.

The current agreement builds on a collaboration that started with an MoU at MWC 2025, when Indosat, Nokia, and Nvidia first agreed to develop and deploy AI-RAN together. That was followed in late 2025 by the launch of an AI-RAN Research Centre in Surabaya, positioned as a long-term R&D hub for AI-native wireless and edge AI in Indonesia. At MWC 2026, the partners demonstrated an AI-powered 5G call linking Barcelona and Jakarta in real time, cited as the first AI-powered 5G call in Southeast Asia. However, these were proofs of concept; the new agreement is a deployment roadmap with an explicit timeline to move from lab conditions to field trials on Indosat's live network in Indonesia by the end of 2026, focused on validating spectral efficiency gains, energy savings, and AI service performance in real-world conditions. Assuming those trials go well, broad commercial AI-RAN deployments are expected to begin across Indosat's footprint in 2027.

The architecture combines three things on a single, software-defined infrastructure: AI-for-RAN uses machine learning to optimize how the network operates through dynamic resource allocation, traffic prediction, and interference management; AI-on-RAN runs edge AI inferencing workloads like video analytics or generative AI on the same hardware that handles baseband processing; and AI-and-RAN treats that hardware as a multi-purpose platform, hosting connectivity and third-party AI workloads concurrently. Technically, this means cloud-native RAN functions running as Nokia anyRAN/Cloud RAN software, orchestrated via Kubernetes on GPU-accelerated servers, with Nvidia supplying the AI Aerial platform. Indosat envisions the architecture as a single intelligent "AI mesh" layer combining centralized AI processing with distributed AI-RAN nodes, distributing intelligence and connectivity to millions of devices and users. If the trials and 2027 rollout hold to schedule, the network would support low-latency consumer services like AR/VR and cloud gaming, alongside enterprise applications including smart city traffic monitoring and AI-based video analytics in private 5G factory deployments.

The deal slots neatly into Indonesia's "Golden Indonesia 2045" vision, which calls for transforming the country into a high-income, digitally advanced economy by its centenary. This rollout is explicitly framed as supporting that goal, with practical benefits for a large, geographically dispersed market where coverage outside Java remains uneven. The low- and mid-band 5G focus is aimed at improving connectivity in underserved areas while managing dense urban capacity needs without proportionally increasing hardware and energy costs. Strategically, the deal reinforces the broader Nokia-Nvidia alliance, positioned as a Western-aligned counterweight to Ericsson, Huawei, and ZTE in critical telecom infrastructure. NVIDIA has committed a $1 billion investment in Nokia as part of that partnership, and Indosat joins a roster of early AI-RAN operators that includes T-Mobile US, SoftBank, and Vodafone. If the trials succeed, Indonesia would position itself among the earliest adopters of commercial AI-RAN globally, ahead of regional peers like Singapore, Malaysia, and Vietnam.

However, skepticism around AI-RAN persists. Analysts have repeatedly questioned the high capex and opex of GPU hardware, particularly in a tight-ARPU market like Indonesia, where the economics of replacing purpose-built RAN silicon with general-purpose accelerators remain unsettled. Energy consumption is a persistent open question—GPU-accelerated cell sites need to demonstrate that their efficiency gains actually offset their power draw versus traditional RAN systems, and so far that case rests largely on vendor claims. There are also concerns about operators locking themselves into Nvidia's specific AI ecosystem, a familiar worry for anyone who has watched the data center market over the past few years. The real test will come with the field trials, which must prove that AI-RAN's laboratory performance translates into real-world advantages at scale.