AI赋能能源系统：解锁可持续AI，助力韧性能源转型

Unlocking sustainable AI for November 2025 Table of contents Executive summary04 1. Introduction06 2.1.Key applications of AI in energy systems082.1.1.System optimization and control092.1.2.Asset lifecycle management112.1.3.End-useefficiencyandmanagement132.2.The interconnectedness of AI applications152.3.Measuring the impact of AI15 3. Sovereignty and AI18 3.1.Sovereign AI considerations in energy systems193.2.Resilience gains from AI in energy systems20 4. Unlocking sustainable sovereign AI 4.1.Key considerations224.2.CreatinganinclusiveAI future24 Foreword Energy systems around the globe stand at aninflection point. Many leaders in the energysector are navigating a transformation ofscale and complexity, as they balance surgingdemand, environmental considerations, and the Energy producers and manufacturers, technologycompanies, financial services, and policymakers Additionally, as AI becomes increasinglyembedded in critical infrastructure, it’simportant that leaders work to upholdprinciples of sovereignty, transparency,and accountability. Fostering local capacity, AI is rapidly becoming a catalyst for measurableprogress in energy systems. Leaders acrossthe sector are deploying AI-driven solutionsto optimize their operations, strengthenreliability, and unlock substantial economic andenvironmental gains. From automated methaneleak detection that saves billions while reducing This report provides a timely and actionableroadmap for leaders to harness AI to help driveefficiency, sustainability, and long-term resiliencein energy systems. Explore these insights, learnhow other leading organizations have applied The potential impact of AI on energy systemsis vast—by 2030, strategically leveraging AIcould enable energy savings that far exceedthe technology’s energy consumption, deliverhundreds of billions in annual cost reductions, Jennifer SteinmannDeloitte Global Sustainability Executive summary Energy systems face mounting challenges, notably demand, environmental concernsand the need for enhanced resilience.1Artificial Intelligence (AI), with its vasttransformative potential, can offer a unique opportunity to help optimize operations,strengthen reliability and unlock substantial economic and environmental benefits.2,3 •Planninganddecision-makingsupport•Improving operations and It is important to recognize that system optimization, assetlifecyclemanagementandend-useefficiencyandmanagementoften overlap and reinforce each other in practice, as manysuccessful AI applications integrate functionalities across machine learning and remote sensing to continuously monitornetworks,resultinginannualglobalsavingsofnearlyUS$6billionbyreducingemissionsandoperationalcostsandenablingfaster repairs (seeBox 1). Additionally, Emerald AI’s ConductorplatformcanenableAIdatacenterstodynamicallyreduce •Technology companiesare among the engines of innovationinthefieldofAI,andtheyarekeytotailoringAItotheneedsofthe energy sector. By investing in complementary technologiesliketheInternetofThings(IoT)anddigitaltwins,technologycompanies can provide advanced solutions for importantchallengesintheenergysectorsuchasgridstability,demandforecasting and predictive maintenance. They can help ensure The deployment of AI solutions across energy systems can helpdeliverscalablevaluefromtheoutset,reachingsignificantlevelsof energy savings, cost reductions and avoided emissions in the •By2030,AI-enabledenergysavingsmayreachmorethan3,700 terawatt hours (TWh), largely exceeding the technology’sprojected energy consumption.8,9By 2050, anticipated savings •AIcandelivermorethanUS$200billionofannualcostsavingsby2030andalmostUS$500billionby2050.Dependingonthescenario,thisrepresentsUS$11trillionincumulativesavings •AI-driven emission reductions can reach up to 660 megatonsofcarbondioxideequivalent(MtCO2eq) in 20309—asignificantcontributiontoglobalgreenhousegas(GHG)mitigationefforts.11However,bysustainablyreducingtheemissionsassociatedwithbothend-usesandenergyproductionacross •Financial services providersare important for scalingsustainableandresilientAI-driveninnovation.Bydeployinginnovativefinancinginstruments,suchasgreenandsustainability-linkedbonds,concessionalloans,andmezzaninefinancingmechanisms,theycansupport AsAIbecomesmoreembeddedincriticalinfrastructure,questionsofsovereignty—controloverdata,algorithms,anddecision-making—areincreasinglysalient.12SovereignAIprinciplesemphasizetransparency,accountability,localcapacity-building,andsafeguardingsensitivedatatoensure •Governments and policymakerscan play an importantroleincreatingtheconditionsforresponsibleandsovereignAIadoptioninenergysystems.Byestablishingstandards,harmonizingsecuredata-sharingframeworksandinvestinginhigh-quality,interoperabledatasets,governmentsandpolicymakerscanacceleratecollaborativeAIinnovationandoptimizeregionalenergysystems.Differentpolicyapproacheshavebeenobservedglobally.Formanyjurisdictions,economic Integrating AI into energy systems has the potentia