New research has shown that communication service providers (CSPs) worldwide believe that deploying artificial intelligence (AI) software is essential to reducing fast-rising network energy demand and emissions, spurred by internet traffic growth.
The research conducted by Nokia and GSMA Intelligence, an industry authority on global mobile operator data, insights, reports and forecasts, also revealed that most CSPs surveyed said that energy efficiency is either “very important” or “extremely important” in their network transformation strategy to counter rising energy consumption and emissions.
Along with the use of renewables, AI energy management software is central to many CSP strategies to shrink their environmental footprint, due to those solutions’ ability to be used quickly and effectively across an entire network with little to no human intervention.
GSMA Intelligence, found that 83% of CSPs surveyed see energy efficiency as a major network transformation driver that will grow in importance as 5G is operationalized by industry; while 67% expect their energy costs to rise over the next three years based on current trends.
Global internet traffic has risen exponentially in recent years due to a convergence of factors like increased television and movie streaming, video conferencing from remote working, and online gaming as 4G and now 5G become a larger share of the mobile customer base.
Such activities require more energy consuming telco equipment and bandwidth capacity, as well as large amounts of data stored in an ever growing number of energy consuming data centres. As businesses and enterprises tap advanced 5G services, like network slicing, further demands will be made on telco networks, data centres, and energy consumption.
Many CSP respondents acknowledged they are still in the early planning and testing stages of getting their AI efforts off the ground with respect to energy efficiency. Still, nearly 50% of CSP respondents said they expect to achieve energy savings of 10% to 20% over the next two years as AI energy solutions are rolled out and optimized.
Speaking on the research, Volker Held, Head of Marketing for Managed Services, Cloud & Network Services at Nokia, said: “Reducing its carbon footprint is an important challenge for the telecommunications industry, given rising internet traffic trends and its implications for energy consumption. This research from Nokia and GSMA underscores the shared concerns of our industry and the variety of solutions and services that Nokia is working on with communication service providers to address this shared responsibility. AI solutions hold the promise of realizing quick and substantial energy efficiency gains and ensure we fully live up to our environmental and social responsibilities.”
Using zero-touch automation, AI programs can improve energy savings by closely aligning equipment usage patterns with real-time network demands; and identifying performance anomalies in underperforming network equipment that saps energy resources and requires replacement.
Beyond curtailing energy demand, AI-powered energy solutions are expected to drive other important outcomes, such as reducing the number of on-site visits personnel have to make to troubleshoot network issues.
The separate white paper by Nokia and GSMA Intelligence projects that the implementation of mobile and digital technologies, like 5G, 4G, private networks, and IoT sensors, could catalyze large carbon emission savings in manufacturing, power and energy, transportation, and buildings; all of which account for around 80% of global carbon emissions.
For example, annual manufacturing carbon savings from the rollout of smart factories at scale could save the equivalent of 28 million roundtrip flights from London to Los Angeles in a year; while energy savings from the widespread use of smart meters in homes, by more efficiently using resources when they are actually needed, would be enough to power 97 million homes in a year.
Also commenting, Tim Hatt, Head of Research and Consulting at GSMA Intelligence, said: “AI has clear and tangible benefits to improving the energy efficiency of telecom networks and is a big part of the solution in driving sustainable 5G networks. It’s important to deploy AI early in order to train the algorithms and continually optimize network ops and costs over the long run.”