Telecom networks are highly energy-intensive, and as digitalization continues to advance, so does the demand for energy. Notably, telecom networks account for a substantial portion of global electricity consumption.
As the number of 5G and IoT devices rises, energy consumption has grown exponentially, creating a pressing need for more sustainable practices within the telecom sector. However, given the vast amount of data, the complexity of infrastructure, and the demand for seamless connectivity, optimizing energy use in telecom networks has become a challenge.
To address this challenge, telecom operators are turning to artificial intelligence (AI) to unlock new opportunities for energy efficiency. AI allows for real-time monitoring, data analysis, and automated decision-making that can optimize network energy consumption, streamline operations, and enhance sustainability.
Related: Asia Pacific’s Telecom Sector Pursues Green Revolution
Are Energy-Efficient Networks Necessary Beyond CSR Compliance?
According to the International Energy Outlook 2011, energy demand in developing Asia is expected to grow by 2.9% per year until 2035, significantly outpacing the global average of 1.6%. The rise in energy demand brings with it a host of challenges, including environmental sustainability, affordability, and energy security. However, energy efficient networks stand out as one of the most cost-effective means of addressing these challenges. Energy efficiency in telecom networks is no longer just a Corporate Social Responsibility (CSR)-driven goal; it is a strategic necessity.
Energy efficiency is often hailed as the most affordable way to increase energy supply, particularly in Asia, where energy demand is projected to grow rapidly. The Asian Development Bank (ADB) highlighted that a megawatt of power saved through energy efficiency costs about half or even less than adding a megawatt of coal-fired generating capacity. As such, energy efficiency has been viewed as the least expensive and most efficient way to meet rising energy demands in Asia. This aligns with the broader view that improving energy efficiency can have multiple benefits.
According to the GSMA, energy consumption accounts for 20-40% of network operating expenses (OpEx) for telecom operators. Interestingly, Nokia found that replacing legacy site equipment improved efficiency by 44%, demonstrating that modernization efforts can significantly cut costs. Today, Asian operators are managing multiple network generations simultaneously—2G, 3G, 4G, and 5G—which increases overall energy consumption. Smart network load optimization, such as AI-driven traffic management and dynamic power scaling, can reduce energy usage without compromising performance.
Beyond cost savings, energy efficiency directly improves network performance. Lower energy consumption leads to reduced heat output, minimizing the risk of overheating and hardware failures. Energy-efficient networks also offer faster and more consistent service, ensuring a better user experience. In response, telecom operators are virtualizing the network core and modernizing RAN infrastructure.
The ADB further emphasized that energy efficiency initiatives help increase the sustainability of energy systems by contributing to energy security, reducing harmful environmental impacts, and mitigating greenhouse gas (GHG) emissions.
Latest: Investment Potential in Indonesia's Expanding Data Center Market
Building Energy-Efficient Networks in Asia
Telcos across Asia are increasingly leveraging AI to optimize energy consumption in their networks, creating more efficient networks that prioritize both economic and environmental sustainability.
The Philippines’ Globe Telecom (Globe) has been a front-runner in utilizing AI to enhance energy efficiency. Through the integration of machine learning (ML) algorithms and AI-based analytics, Globe Telecom has significantly improved its network’s energy consumption while enhancing its sustainability efforts. The impact of Globe Telecom’s AI-driven energy management system has already yielded remarkable results. In just one year, Globe achieved significant energy savings, totaling approximately 187,774 kWh of electricity. This reduction in energy consumption helped curb 139 metric tons of carbon dioxide (CO2) emissions, showcasing the effectiveness of AI and ML in not only improving operational efficiency but also reducing the company's environmental impact.
Furthermore, Globe Telecom successfully reduced its energy consumption by 4.2% through Qualcomm’s AI-driven Edgewise solution, which optimizes the management of network equipment. Joel Agustin, Head of Service Planning and Engineering, explained that this innovative technology dynamically adjusts network operations based on real-time traffic and usage, ensuring energy efficiency without compromising service quality.
“Qualcomm’s AI-powered Energy Efficiency solution has enabled us to significantly reduce energy consumption across our RAN while maintaining optimal network performance for our customers.”
This partnership supports Globe's environmental goal of achieving net-zero carbon emissions by 2050 and exemplifies its commitment to sustainability in the telecommunications sector.
NTT DOCOMO and SK Telecom (SKT) are supporting this charge through their joint research on energy-efficient 5G networks. Their recent white papers detail that energy consumption can be reduced in base stations and telecom networks by analyzing current energy use and evaluating each sector to identify potential savings.
Nippon Telegraph and Telephone (NTT) is taking a futuristic approach with its Innovative Optical and Wireless Network (IOWN) initiative. Expected to be fully operational by 2030, IOWN aims to decentralize data centers in Japan using light-based networking, significantly reducing latency and cutting energy consumption by an astonishing 99%.
Nokia and Chunghwa Telecom (CHT) have expanded their partnership to optimize CHT's 5G network in Taiwan with AI-powered solutions. Nokia's MantaRay AI enables network monitoring and energy optimization, incorporating features such as deep-sleep mode and MIMO muting to conserve power. Meanwhile, Bharti Airtel (Airtel) and Nokia have also joined forces to deploy ‘Green 5G,’ integrating AI and ML to enhance energy efficiency in Airtel’s extensive 4G and 5G Radio Access Networks (RAN). This collaboration is expected to cut Airtel’s carbon emissions by approximately 143,413 metric tons of CO2 per year, reinforcing its commitment to sustainable telecom expansion. Nokia has also partnered with Vodafone Idea to strengthen India’s mobile network by incorporating AI-powered automation, energy-efficient RAN technologies, and intelligent network management into Vodafone Idea’s network, improving network performance while lowering power consumption.
In the Philippines, PhilTower and Huawei are collaborating to revolutionize telecom infrastructure using energy-efficient designs for shared towers and facilities. In Thailand, Huawei developed a green and intelligent campus network, while in Singapore, its optical backbone network solutions are enhancing the energy efficiency of the country’s vital networks. Huawei’s Fiber-to-the-Office (FTTO) solution has simplified network architectures, eliminating the need for extra-low voltage rooms, reducing optical module investments by 50%, and improving operations and maintenance efficiency by another 50%. Meanwhile, in Taiwan, Chunghwa Telecom aims to advance energy efficiency by establishing a network using All-Photonics Network (APN) technology. APN technology is inherently designed to optimize energy use by providing dedicated, streamlined network connections that reduce unnecessary power expenditures.
Interesting Read:
AI and the Future of Telecom Network Sustainability
The integration of AI into energy management is not only a current solution but also a pathway securing the future of sustainable telecom networks. As we look ahead, the potential of AI in optimizing energy usage will continue to evolve. In the near future, telecom networks could become fully autonomous, powered by AI that continuously learns from network data and optimizes energy consumption in real time.
AI is also expected to play an essential role in integrating renewable energy sources into telecom networks. By forecasting energy production from sources such as solar and wind, AI will allow telecom operators to adjust their energy consumption based on the availability of clean energy. Wind turbine costs have also fallen by 37-56%, making renewables a more viable and cost-effective option for telecom networks than traditional power grids. According to Tupl, the integration of AI and renewable energy will further reduce the telecom sector’s reliance on fossil fuels and contribute to the global effort to combat climate change.
Moreover, as telecom networks move beyond 5G, the complexity of the network infrastructure will increase. AI’s ability to scale and adapt to these changes will be crucial in ensuring that energy consumption remains manageable. Advanced AI technologies, such as deep learning and reinforcement learning, will enable telecom operators to create self-optimizing networks that are not only more efficient but also capable of adapting to changing traffic conditions and energy demands.
Latest Insights:
OpenAI, SoftBank to Boost AI Adoption in Japan
Malaysia’s Blueprint for AI Dominance in ASEAN
2025 Cloud Predictions: AI, Economics to Drive Growth and Change in IaaS
Website block quote
Removed the Jakarta and pollution sections as this article is specifically about AI in telecom network efficiency
