电信人工智能：2024年第三季度市场状况

AI and energy efficiency The GSMA is a global organisation unifying the mobile ecosystem todiscover, develop and deliver innovation foundational to positive businessenvironments and societal change. Our vision is to unlock the full powerof connectivity so that people, industry, and society thrive. Representingmobile operators and organisations across the mobile ecosystem andadjacent industries, the GSMA delivers for its members across three GSMA Intelligence is the definitive source of global mobile operator data,analysis and forecasts, and publisher of authoritative industry reports andresearch. Our data covers every operator group, network and MVNO inevery country worldwide – from Afghanistan to Zimbabwe. It is the most GSMA Intelligence is relied on by leading operators, vendors, regulators,financial institutions and third-party industry players, to support strategicdecision-making and long-term investment planning. The data is used as We invite you to find out more at www.gsma.com Our team of analysts and experts produce regular thought-leadingresearch reports across a range of industry topics. www.gsmaintelligence.cominfo@gsmaintelligence.com Authors Sayali BoroleSenior Analyst Peter JarichHead of GSMAIntelligence Tim HattHead of Research Navigatingenergy efficiency The telecoms industry stands at a critical juncture, where the push forenergy efficiency intersects with rapid technological advancements. At the GSMA, we are committed to supporting members in navigating thesecomplexities, ensuring sustainable growth while maintaining competitiveness.This report dives into the vital role of AI in enhancing energy efficiency within However, the importance of this report extends beyond efficiency. AI’sincreasing role brings its own set of energy challenges; this edition outlinesstrategies to mitigate these impacts. The report also addresses the essential For GSMA members and industry leaders, this report is not just a resource;it is also a call to action. As AI reshapes networks and energy landscapes,collaboration and knowledge sharing are key. We encourage you to engage Brian RobertsonHead of Industry Strategy, GSMA About the series This is the second report in a four-part series on AI strategy in telecoms. The research identifies theparts of the innovation cycle that matter most, and how they translate into commercial activity and Starting with this edition, the series explores how AI enhances security while introducing new risks.The series will examine the benefits and challenges, beginning with the critical security aspects of In tandem with the report series,GSMA Intelligence is developing anAI benchmark to track AI use and Market context This editiondelves into the role of AI in enhancing energy efficiency within the telecoms sector,addressing both energy demand and the potential offsets it creates. It highlights key use cases where 01 Executivesummary 02 03 State of the market AI adds to an already difficult energy view 03 ‘AI for telco’ and ‘telco for AI’ 01 AI can work for operators by significantly enhancing energyefficiency through methods such as RAN shutdowns anddynamic spectrum management. Equipment vendors are at theforefront of integrating AI to reduce energy costs. Over the next While transformative in their impact, 5G and AI technologieshave significantly increased energy consumption. Telecomsnetworks and data centres each account for about 1% of Looking ahead, fixed and mobile networks will continue to beput under strain from rising data traffic (growing at 30% peryear currently) and AI-driven applications in video, gamingand enterprise. The impact on hyperscalers is potentially moreacute. 5G expansion and rising enterprise workloads werealready traffic drivers. AI compute power for large language The flipside of AI helping operators is that network capacitywill also be critical to help enterprises benefit from AI in theirbusinesses – ‘telco for AI’. The support will come from increasednetwork capacity and indeed smarter capacity, as customers Assessing the impact over the long term 04 To understand the potential impacts of AI on energy usagein the long term, it helps to consider how operators are likelyto use AI in their business. This will play out over three broadphases for the rest of the 2020s, with early-adopter operatorsusing AI gradually joined by a larger share of the industry andeventually moving to an AI-native business model. Such amodel would see AI and automation coalesce across functions 02 Understanding the scale of the challenge It is easy to underappreciate the magnitude of energy riseswhen dealing in units of measurement such as terawatthours or tonnes of CO2. The incremental energy added byAI between now and 2030 could be equivalent to the entire AI in numbers 76% 60% 70% 1% Percentage of globalenergy use attributedto operator networks– fixed and mobile.The same is true ofdata centres. Whilethis may not seem Proportion of