Indosat Ooredoo Hutchison and Nokia use AI to reduce energy demand and emissions
Indonesian network operator Indosat Ooredoo Hutchison has deployed Nokia Energy Efficiency (part of the company’s Autonomous Networks portfolio – described below) to reduce energy demand and carbon dioxide emissions across its RAN network using AI. Nokia’s energy control system uses AI and machine learning algorithms to analyze real-time traffic patterns, and will enable the operator to adjust or shut idle and unused radio equipment automatically during low network demand periods.
The multi-vendor, AI-driven energy management solution can reduce energy costs and carbon footprint with no negative impact on network performance or customer experience. It can be rolled out in a matter of weeks.
Indosat is aiming to transform itself from a conventional telecom operator into an AI TechCo—powered by intelligent technologies, cloud-based platforms, and a commitment to sustainability. By embedding automation and intelligence into network operations, Indosat is unlocking new levels of efficiency, agility, and environmental responsibility across its infrastructure.
Earlier this year Indosat claimed to be the first operator to deploy AI-RAN in Indonesia, in a deal involving the integration of Nokia’s 5G cloud RAN solution with Nvidia’s Aerial platform. The Memorandum of Understanding (MoU) between the three firms included the development, testing, and deployment of AI-RAN, with an initial focus on transferring AI inferencing workloads on the AI Aerial, then the integration of RAN workloads on the same platform.
“As data consumption continues to grow, so does our responsibility to manage resources wisely. This collaboration reflects Indosat’s unwavering commitment to environmental stewardship and sustainable innovation, using AI to not only optimize performance, but also reduce emissions and energy use across our network.” said Desmond Cheung, Director and Chief Technology Officer at Indosat Ooredoo Hutchison.
Indosat was the first operator in Southeast Asia to achieve ISO 50001 certification for energy management—underscoring its pledge to minimize environmental impact through operational excellence. The collaboration with Nokia builds upon a successful pilot project, in which the AI-powered solution demonstrated its ability to reduce energy consumption in live network conditions.
Following the pilot project, Nokia deployed its Energy Efficiency solution to the entire Nokia RAN footprint within Indonesia, e.g. Sumatra, Kalimantan, Central and East Java.
“We are very pleased to be helping Indosat deliver on its commitments to sustainability and environmental responsibility, establishing its position both locally and internationally. Nokia Energy Efficiency reflects the important R&D investments that Nokia continues to make to help our customers optimize energy savings and network performance simultaneously,” said Henrique Vale, VP for Cloud and Network Services APAC at Nokia.
Nokia’s Autonomous Networks portfolio, including its Autonomous Networks Fabric solution, utilizes Agentic AI to deliver advanced security, analytics, and operations capabilities that provide operators with a holistic, real-time view of the network so they can reduce costs, accelerate time-to-value, and deliver the best customer experience.
Autonomous Networks Fabric is a unifying intelligence layer that weaves together observability, analytics, security, and automation across every network domain; allowing a network to behave as one adaptive system, regardless of vendor, architecture, or deployment model.
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2 thoughts on “Indosat Ooredoo Hutchison and Nokia use AI to reduce energy demand and emissions”
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It’s truly inspiring to see major players like Indosat Ooredoo Hutchison and Nokia taking meaningful steps toward sustainability using AI. The fact that they’re leveraging AI to intelligently shut down unused radio units and optimize energy use—especially in cooling systems—is a powerful example of how advanced technology can directly contribute to reducing emissions.
This isn’t just a win for operational efficiency, it’s a significant move for environmental responsibility in the telecom industry. As networks continue to grow in scale and complexity, these kinds of innovations could be game-changers on a global level. I hope to see more operators around the world adopt similar solutions. This is the kind of leadership and forward-thinking we need in the era of climate change.
AI may have a big role in transforming the 5G/6G RAN and mobile operator business. Nokia supports Indosat in its strategy of accelerating innovation with AI-RAN and using AI for more efficient energy utilization.
However, it remains to be seen if AI RAN will be deployed by most wireless network operators. To date these are the operators with Active Deployments or Live Trials of AI RAN:
-SoftBank (Japan): A founding member of the AI-RAN Alliance, SoftBank has been a primary driver of the technology, having already moved beyond theory to implement AI-RAN in live networks for energy efficiency and traffic management.
-T-Mobile (USA): Collaborating with NVIDIA, Ericsson, and Nokia, T-Mobile has established an AI-RAN Innovation Center. It is actively integrating AI-RAN technologies into its development process and plans field evaluations in 2026 to prepare for 6G.
-KT (South Korea): Launched South Korea’s first AI-RAN trial on a live 5G network in 2025, utilizing specialized AI processors in Nokia base stations to improve capacity and reduce data loss.
-Indosat Ooredoo Hutchison (Indonesia): Became the first operator in Southeast Asia to launch AI-RAN, using a solution that combines Nokia’s 5G Cloud RAN and NVIDIA’s AI Aerial platform.
-SK Telecom (South Korea): Partnering with Samsung to lead the 6G era using AI-RAN technology, focusing on advanced radio resource management.
-Vodafone (Global): Joined the AI-RAN Alliance in July 2025 and is committed to using AI to optimize radio performance across its global footprint.
-MásOrange (Spain): Deployed the Ericsson Intelligent Automation Platform (EIAP) to automate its RAN operations using AI-driven network management tools.