重新定義真實資產(chǎn)：巨型趨勢及其對投資策略的影響+Megatrends+and+Their+Impact+On+Investment+Strategies

REDEFININGREALASSETS:

Megatrendsand

theirimpact

oninvestment

strategies

Megatrendsarenotfixed

Megatrendsunderpindemandforrealassetsthroughouteverymarketcycle.Theselong-

term,structuraltrendsallowinvestorstobe

forward-lookingintheirinvestmentstrategies,approachingtheshiftingdynamicsofreal

estate,naturalcapitalandinfrastructurewithconfidence.”

However,thesemegatrendsarenotfixed.Wedevelopedourmegatrendframeworkin2015,buteventsofthelastfiveyears–thepandemic,warinUkraine,costoflivingcrisistonameafew–haverefinedouranalysis.

Weseesometrendsareaccelerating,somearebeingdisrupted,whileafewremainontheirprevioustrajectory.Thispublicationisacollectionofourlatestthinking;itexplorestheopportunitiesandriskstobefoundineachmegatrendandthe

implicationsforrealassetinvesting.

Thedriversforthesemegatrendsarevaried,affectingassetclassesindifferentwaysandtodifferentdegrees.Theyarealsodeeplyinterconnectedandoftenreinforce

oneanother;digitalizationandtheriseofartificialintelligence(AI),forexample,

boostsdemandforelectricityandenablesactivitiessuchashybridworkingand

onlineshopping,whichimpacturbanizationandthenatureofcities.Wecanalso

expecttechnologyanddigitalizationtorespondtotheneedsoftheagingpopulation,transforminghealthcareandlifesciences,whilerealestateandinfrastructurewillhavetoadaptbuildingsandservicestobettermeettheneedsoftheelderly.

Otherforcessuchasshiftinggeopoliticalsentiment,theneedtoadapttoclimate

changeandthetransitiontoalowcarboneconomyareallacceleratingchangesininfrastructuredemands.Naturalcapital,whichincludesfarmlandandtimberland,isimpactedheavilybyclimateandwillevolvetotakeadvantageoftheopportunitiespresentedbythetransitiontothelowcarboneconomy,butchangesinurbanizationandtechnologyaretransformingtheopportunitysetaswell.

Thesearejustsomeexamplesofhowmegatrendsareevolving,andhowtheyimpact

realassetsindifferentways.Thefollowingarticlesprovideinsightsforthelong-termopportunitiesofrealestate,infrastructureandnaturalcapital,emphasizingthethreadsthatconnecttheseassetclasses,andthedifferentdynamicsatplay.Eacharticleis

designedtogiveinvestorsaclearerindicationofhowthesemegatrendscouldaffectportfolioallocationstorealassets,helpingthemtoinvestwithconfidence.

AbigailDean

GlobalHeadofStrategicInsights,NuveenRealAssets

2

ACCELERATION

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DIGITALIZATION

AIdeliverstransformativechange

URBANIZATION

Urbanizationadaptswithgrowingmobility

n

A

o

i

t

c

c

p

u

r

e

l

e

GLOBAL

INTERCONNECTEDNESS

Tradeprotectionand

sanctionsdrivedecoupling

TRANSITIONTOLOWCARBONECONOMY

r

t

a

Transitiontoalowcarboneconomypowersgrowth

s

i

i

on

u

a

t

i

t

i

o

n

D

C

o

n

n

GROWTHOFTHEEAST

Continuedgrowthdespitegeopoliticaldisruption

RISINGINEQUALITY

Despitethegrowthofthemiddleclass

AGINGPOPULATION

Agingpopulationboostdemandforalternatives

CLIMATECHANGE

Climatechangeandnaturelossmaterialize

Megat

rends

Transformativetechnology

Transitiontoalowcarboneconomypowersgrowth

Acceleration

DISRUPTION

4

ACCELERATIONCONTINUATION

Risinginequality

Transformativetechnology

Artificialintelligence(AI),specificallygenerativeAI(GenAI),ispoisedtoaffectvirtuallyeverysectoroftheglobaleconomyandtransformtheworkforce.

5

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GenAIalonecouldaddbetween

$2.6and$4.4trilliontoannual

globalGDPandisexpected

toautomate60-70%oftasks

currentlyperformedbyemployees.1

Comparedtopreviouswavesofautomation,these

changesinthelabormarketwilldisproportionately

impactworkerswithhigherwagesandeducational

attainment.However,advancesinAIareexpected

toacceleratelaborproductivitygrowthbetween0.1-

0.6%annuallythrough20401dependingontherateoftechnologyadoptionandredeploymentofworkertime.TounderstandAIasamegatrend,wemustunderstandhowAIhasevolvedandtheopportunitiesandrisksitwillbringacrossrealassets.

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WHAT’SCHANGED

AIandmachinelearningalgorithmshave

beeninuseformanydecades.ButGenAI

suchasChatGPTbringsrenewedattentiontohowthesetransformativetechnologieswillchangeourdailylivesandphysicalworld.

GenAI’sabilitytocreatenewinformationfromexistinginformationwillenablea

fundamentalshiftintheeconomicsof

businessandwhite-collarindustries.

GenAIpresentsopportunitiesandrisksforbothcorporationsandindividualworkers.Largelanguagemodelsdonotnecessarilycompetewithexistingsoftwarebutare

nowcompetingwithpartsofcompanies

andpeople.Workerswhodonotlearnto

embraceAItoenhancetheirworkareatriskofobsolescence.

However,thesetoolsalsopresentsignificantopportunitiesforindividuals.Forthefirsttime,thosewithoutdatascienceortechnicalexpertisecanharnessthefullpowerof

AI,democratizinginnovationacrossanorganization.Everyonethroughoutan

organizationnowhastoolstoreconsiderwhatshouldbeversuswhathasbeen,

andanabilitytoreimaginehowwecan

betterutilizeexistingtechnologies.We

arestillintheearliestinningsoftheseusecases,butadvancesarebeingmadeataremarkablepace.

Artificial

intelligence

Machinelearning

Deep

learning

IMPLICATIONSAND

OPPORTUNITIESFORREALASSETS

HIGHERIMPACT

LOWERIMPACT

NATURALCAPITAL

Changingclimateandnatureloss

Transitiontolowcarboneconomy

GrowthofglobalSouthandEast

Protectionismdrivesdecoupling

Urbanizationandtheevolutionofcities

Transformativetechnology

Risinginequality

Agingpopulation

INFRASTRUCTURE

Transitiontolowcarboneconomy

Changingclimateandnatureloss

Transformativetechnology

GrowthofglobalSouthandEast

Protectionismdrivesdecoupling

Urbanizationandtheevolutionofcities

Agingpopulation

Risinginequality

REALESTATE

Agingpopulation

Risinginequality

Transitiontolowcarboneconomy

Transformativetechnology

GrowthofglobalSouthandEast

Urbanizationandtheevolutionofcities

Changingclimateandnatureloss

Protectionismdrivesdecoupling

7

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CONTINUATION

DISRUPTION

Realestate

Newtechnologies

poweredbyAIandGenAIarerapidlyemerging

acrosstherealestate

technology(Proptech)

world.Thesenewuse

casesarebeingtested

alongtherealestatevaluechain,fromacquisition,todevelopmentand

redevelopment,inoperationsand

throughdisposition.

Ingeneral,AIis

enablingtheindustrytoevolveinwaysthatwillcreatemoredynamic,

efficient,sustainableandcustomer-focusedrealestateexperiences.

HOWCOULDAICHANGEREALESTATE?

Datacenters

Datacentersareexperiencing

unprecedenteddemandandisthefirst

sectortodirectlyseethepositiveimpactsoftheAIboom.GenAIandcloudcomputingplatformgrowthrequiresrobustdata

infrastructure,leadingtoanincreasedneedforadvanceddatacenterswithspecializedcoolingandpowerrequirements.Theglobaldatacenterrentalmarketisforecasttogrowatafive-yearcompoundannualgrowth

rateof23%,upto36%iscontributedby

thedemandforAI.2AIandcloud-driven

demandareexceedingconstrainedsupply,creatingrecordlowmarketvacancyandall-timehighpre-letmarketabsorption.

Office

Thereisanear-perfectcorrelationbetweeneducationalqualificationsandGenAI

impact.3LegalservicesareprojectedtobethemostaffectedbylargelanguagemodelslikeChatGPT.Thesectoriscloselyfollowedbyfinancialactivitieslikebankingand

insurance,professionalservicesincludingaccountingandconsulting,technology

sectorspecialtieslikecomputerdata

processingandmediasectors.ThedegreeAIwillinfluencethesesectorsremains

unclear,meaningitwilltaketimetounravel

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theimplicationsforrealestateinvestorsintheofficespace.

Retail

Thepushandpullbetweentheethicaluseofcustomerdataandprivacywillcontinuetobetopofmindforretailersandtechnologycompanies,butwilllikelyproduceoutsizedbenefitsthatunlockenhancedcustomer

experience,newproductdiscovery,highersalesvolumesandlargercustomerlifetimevalues.Ontheretailerside,GenAIhasthepotentialtocreateoperatingefficiencies

acrossthevaluechaine.g.inventory

management,salesforecastingandanalysis.Whilepotentiallydisruptiveintheshort-

term,AIhasthepotentialtocreateamoreseamlessomni-channelexperience.For

physicalretail,AIcouldalsoenhance

analyticsleadingtoprofitability,adeeperrelationshipwithcustomersandbetterrealestateoutcomes.

Multifamilyandmixeduse

AI-poweredtoolscanofferresidents

increasinglypersonalizedexperiences.

Forexample,leasingchatbotsandsmart

hometechnologiescancustomizesettingsforlighting,temperatureandsecurity.

Furthermore,GenAIandthepermanenceofhybridworkwillcontinuetoincreasetheshareoftheworkforcethatisself-employedorworkingforsmallcompanies.

AIusecases

Marketanalysis

Dealsourcing/siteselection

Enhancedunderwriting/duediligence

Toolscanhelpinvestorsidentifyoff-market

acquisitiontargetsbasedonspecifiedcriteria.

AIalgorithmscananalyzedatasetstoidentify

markettrends,predictfuturemarketconditionsandsuggesttheoptimaltimeforacquisition.

AIcanbeusedas

co-pilotsforinvestment

underwritingthatsummarizeandanalyzeconfidential

investmentmemoranda(CIMs)andstreamlineduediligence.

Assetvaluationandappraisal

Investorreporting

Automatedvaluationmodelscanprovideaccuratepropertyappraisalsbyanalyzing

historicaldata,markettrendsandalternativedatasourceslikesatelliteimagery.

Dataandimagescanbe

automaticallygeneratedforinvestorreports.

Buildingoperations

AIisimprovingfault

detectionanddiagnostic

(FDD)softwareandenablingnewsmartbuildinguse

cases.Propertymanagementapplicationscannowimprovereal-timeenergymanagementandpredictivemaintenance.

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Infrastructure

Thetransportationand

intermodallogistics

industrieshavebeen

earlyandsignificant

adoptersofAI,bringingadvancementsin

operationalefficiency,

safety,customerserviceandenvironmental

sustainability.WeexpectthenextwaveofAIto

enhancethefunctionalityofmanyoftheAIuse

casesbeingdeployedinintermodaltransportationandlogisticstoday.

HOWCOULDAICHANGEINFRASTRUCTURE?

Power

Astherenewablesindustrymaturesand

storageassetslikebatteriescomeonline,

AIcanbetterassessdemandpressure

pointsandenableusecaseslikebattery

optimization(todispatchattherighttime)andbatterylifeoptimization(ensuring

abatterydoesn’tgobelowrecovery).

Integrationofrenewableenergycanbe

smootherwithAI-poweredforecastsfor

renewableoutputs,helpingtointegratethemsmoothlyintothegrid.AImayalsoimprovesiteselectionforbatterydeployments,

enablingbetterinsighttoreducegridcongestionandtransmissioncoststoendcustomers.

Portlogistics

AI-poweredtoolsareexpectedtoimprovecontainermanagement,trafficflow

optimizationandcustomsclearance.

Forexample,technologycanbeusedto

optimizecontainerstorageandmovementswithinports.Thisincludespredictingthebeststoragelocationsforcontainersto

minimizemovementandaccelerateloading

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andunloadingprocesses.AIcanalso

helpmanagetheflowoftrucksandships,scheduledockassignmentsandimprove

loadingprocessestoreducecongestionandimproveefficiency.

Fleetmanagement

Advancedtechnologiesarebeingusedforfleetoptimization,particularlyaround

routes,fuelconsumptionandload

optimization.AIalgorithmsanalyzetrafficdata,weatherandotherfactorstodeterminethemostefficientroutesfortransportationfleets.Machinelearningmodelscanhelp

analyzedrivingpatternsandconditionstosuggestimprovements,leadingtoreducedfuelconsumptionandemissions.AIisalsousedtooptimallyallocateandschedule

cargoloadstomaximizecapacityusageandminimizeemptyreturntrips.

AIusecases

Predictive

maintenance

Autonomousvehicles

AIalgorithmscananalyzedatafromequipment

topredictfailures

beforetheyhappen,

reducingdowntimeandmaintenancecosts.

AIpowersself-drivingvehiclesandships,whichcouldrevolutionize

personal,publicand

logisticstransportation.

Supplychainoptimizationandresilience

AI’spredictivecapabilitieshelpinidentifyingsupplychain

fluctuationsanddisruptionsbeforetheyoccur,enhance

visibilityacrosssupplychains,andcanhelppromptproactivedecision-making.

Safetyandcompliance

AIisusedforreal-timemonitoringofoperationstoensurecompliance

withsafetystandardsandregulations.

Analyzingchangingweatherpatterns

AIforecastscanoptimize

renewableenergyproductionorpredictweather-related

disruptionstoplanalternativeroutesandsafeguardassets.

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Naturalcapital

WhiletheimpactsofAIonnaturalcapitalwillnotbeassignificant

asinrealestateandinfrastructure,AIwillenableimprovementsinproductivity,

sustainabilityandbiodiversity.

HOWCOULDAICHANGENATURALCAPITAL?

Farmland

AIandmachinelearningalgorithms

areenablingnewerpracticessuchas

precisionfarming,whichinvolvesthe

preciseapplicationofwater,fertilizers

andpesticides,basedonlyontheneeds

ofspecificareasofafieldwhichoptimizesresourceuseandreducescosts,potentiallyincreasingcropyields.AItoolscanalso

detectplantdiseasesandpestinfestationsearlythroughimagerecognition

technologies,minimizingpotentialdamage.

Timberland

AIcanaidinforestmanagement,improvemonitoringoftimberassetsandenhancesustainabilitypractices.Similarto

farmlandusecases,AI-enabledimage

recognitiontechnologiescanidentifytreespeciesandcountpopulationsoverlargeareas.Finally,AIsystemscanalsodetectsignsofwildfiresfromsatelliteandaerialimagerymorequickly.

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INTERSECTIONWITHOTHERMEGATRENDS

Transitiontogreeneconomy

AIwillplayasignificantroleinhowthegridevolvesandhowthebuiltworldinteractswithit.Theneedforexpandedelectricity

capacityforbothdatacentersandEVchargingwillbeincreasinglyimportantintheevolutionofcitiesasthecompetitionforpowerbetweenhouseholds,businessesanddatacentersintensifies.

GrowthoftheSouthandEast

APACisembracingAImorequickly,butcertainsectorsthathaveexperiencedsignificantgrowthinthoseregions(e.g.,callcenters)areatsignificantrisk.However,AItoolscanmakecommunicationmoreseamless.

Agingpopulation

AIhasthepotentialtosignificantlyincreaseaveragelife

expectanciesbyenhancinghealthcareservicesandresearch

capabilities.Algorithmscananalyzecomplexmedicaldatamorequicklyandoftenmoreaccuratelythanhumans,leadingtobetterdiseasediagnosisandprediction.AIcanalsospeeduptheprocessofnewdrugdiscoveryandbringgreaterpersonalizationto

medicine,potentiallyincreasingtheeffectivenessoftreatments.

Decoupling/Protectionism

Advancechipmanufacturingandsupplychainsareglobalandcomplex.TherearepossiblysignificantfutureimplicationsforthedatacenterindustryascomplicatedAIsupplychainsareintertwinedwithgeopoliticallyimportantregionslikeTaiwan.

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RISKSANDLIMITATIONS

UnderstandingandaddressingthelimitationsofAIisessentialfortheresponsibleandeffectiveuseofthesepowerfultechnologies.

Generallimitations

GenAImodelscansometimesproduceoutputsthatare

nonsensical,irrelevantorfactuallyincorrect.Further,thequalityoftheoutputfromGenAImodelsisheavilydependentonthedatatheyaretrainedon.Ifthetrainingdataisbiasedorlimited,theAIcanperpetuateoramplifythebiasesinitsoutputs.Importantly,GenAIalsoraisesquestionsaroundauthorship,copyrightand

ethicaluse.Dataprivacyandcompliancedepartmentsareactivelyworkingtodevelopandrolloutupdatedpoliciesandguidelinesthattakeintoaccountthesenewconsiderations,especiallyastheyrelatetoconfidentialinformation.

Realassetidiosyncrasies

Realestateisahyper-localindustryanddatasourcesforreal

assetsareimperfecttoolsforcompletelyautomateddecision

making.Theavailabilityandrobustnessofintegrationswithlegacysoftwareandsystemsisasignificantandpersistentchallengein

therealestateindustry.ThePropTechandstartupecosystemispushingtochangetheseentrencheddynamics,butitwillcontinuetobeanuphillbattleasaccountingandpropertymanagement

systemincumbentshavevaryingincentivestoopenuptheirtechnologystacksmorefully.

HOWTRANSFORMATIVEWILLAIBE?

Fornow,AIisfullof

potential,exactlyhowfarreachingthistechnologycango,howitwillchangethewayweworkacross

vastlydifferentsectors

andhowfaritwillchangethecourseofrealasset

investmentsremainstobeseen.Changeistheonlyconstantwecanpredictwithcertainty.

PropTechboomedinthelate2010sand

2020s,introducingmanynew,innovative

technologiestotherealestateecosystem,

thoughnotallhavesurvived.iBuying,

atechnologythatsoughttostreamline

residentialhousingtransactionsbyusing

algorithmstosethousepricesforcashbuyers,isaclearexample.Despitethesingle-familysectorhavingthemostcomprehensive

datasources,anduserstypicallystaying

withinresidentialmarketswiththemost

homogenoushousingstock;someofthe

world’sleadingtechnologists,investors

andventurecapitalistscouldnotscale

sustainablycompetitivebusinesseswiththetechnology.iBuyingservesasacautionarytaleandunderscoreshowchallengingit

isfornewtechnologiestoreplace,orevenreplicate,realestateinvestmentandassetmanagementprofessionals.

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Transitiontoalowcarboneconomypowersgrowth

Awarenessandexpectationssurrounding

sustainabilityandtheneedtotransitiontoalow

carboneconomicmodelarematuringglobally,drivingdemandandcreatingnewinvestmentopportunities.

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ThelandmarkParisAgreementof2015saw196parties

agreetohold“theincreaseintheglobalaveragetemperaturetowellbelow2°Cabovepre-industriallevels”andpursue

efforts“tolimitthetemperatureincreaseto1.5°Cabovepre-industriallevels.”Theagreementhasbeenadrivingforceinthetransitiontoalowcarboneconomy.Today,140nations(representing88%ofglobalemissions)and65%ofForbes

2000corporateshavemadenetzerocarboncommitments.675financialinstitutionshavingjoinedtheGlasgowFinancialAllianceforNetZero.Withinterimtargetsin2025-2030,thewindowforprogressisclosing.

Giventhescaleoftheinvestmentneededtofundthe

transition,investorsarefindingampleopportunitiesacrossassetclassestomitigateriskandgeneratereturns,while

recognizingthatcapitalalongsidethoughtfulgovernmentpolicyandtechnologicalinnovationwillbekeyforsuccess.

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Supportinginvestordemand,our

annualEQuilibriumsurvey

of

institutionalinvestorsfound70%ofrespondentsreportedESGfactorsinfluenceinvestmentdecisionmaking.Asimilar

proportionreportedgoingbeyondregulatoryrequirementsonthe

lowcarbontransition.

IMPLICATIONSAND

HIGHERIMPACT

LOWERIMPACT

OPPORTUNITIESFORREALASSETS

REALESTATE

Agingpopulation

Risinginequality

Transitiontolowcarboneconomy

Transformativetechnology

GrowthofglobalSouthandEast

Urbanizationandtheevolutionofcities

Changingclimateandnatureloss

Protectionismdrivesdecoupling

NATURALCAPITAL

Changingclimateandnatureloss

Transitiontolowcarboneconomy

GrowthofglobalSouthandEast

Protectionismdrivesdecoupling

Urbanizationandtheevolutionofcities

Transformativetechnology

Risinginequality

Agingpopulation

INFRASTRUCTURE

Transitiontolowcarboneconomy

Changingclimateandnatureloss

Transformativetechnology

GrowthofglobalSouthandEast

Protectionismdrivesdecoupling

Urbanizationandtheevolutionofcities

Agingpopulation

Risinginequality

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Realestate

Realestateaccounts

foraround39%of

totalglobalemissions.4Themagnitudeof

theeconomicand

socialtransformationrequiredaspartofthelowcarbontransitionpresentsopportunitiesandchallengesfor

theassetclass.

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ACCELERATION

CONTINUATION

Supply/demandimbalanceleadsvaluecreationforlowcarbonrealestate

Realestatefacesachronicundersupplyofsustainablebuildings.ArecentstudybyJLLfoundthatby2030therewillbea57%to

75%gap(dependingontheregion)5betweensupplyofsustainablespaceandoccupier

demands(Figure1).Evidenceofgreen

premiumsareemerging,andthesupply/

demandimbalanceshouldleadvaluesto

holdandincrease.Thedivergencewillonlyincrease,withnon-greenbuildingsbecominghardertotransact.

Best-in-classsustainableassetsinprimeareascancommandbetterrentsand

stickiertenants.

Transitionunlocksnewopportunities

Themarketassociatedwithretrofitting

existingbuildingstoimproveperformanceandextendtheirlifespanwillcontinuetothrive.AstudybytheUrbanGreenCouncilfoundthatannualinvestmenttomeetLocalLaw976inNewYorkalonewouldneedtoincrease13-fold,presentingaretrofitting

marketopportunityof$20billion.This

brown-to-greentransitionhasthepotentialtotransformthesector.

DISRUPTION

Theriseofgovernmentsubsidiestosupportgreenretrofitprovidesaninstitutional-grademeansofinvestinginthetransition.For

borrowers,lowcarbonreadyassetscanseereducedborrowingcostsof10+basispoints(bps)aslendersunderstandgreenassets

holdlessriskwhilealsolookingtoincreasetheirshareofsustainablefinancingproducts.

Challengesmustbeovercomeforthetransition

Thechallengesintransitioningtoalow

carboneconomycannotbeunderestimated.Thisisparticularlytruegiventhelimited

timetoeffectwholesalechangeinanindustrythatcanbeslowtoreact.

Thecostoftransitionisconsiderable.

McKinseyexpects$1.7trillionisrequiredannuallyto2050todecarbonizebuildings.7Thequestionofhowthiswillbefundedisacomplexone,butpoliticalresponsesandinvestmentfromtheprivatesectorwill

beessential.

Buildings,theirtechnicalsystemsand

whopaysforutilitiesarenotalways

straightforward,givingrisetosplit

incentives.Sectorssuchasretail,

warehousingorindustrialdonotyet

havesignificantoccupierdemandforlowcarbonspace.

Thisimpactsthepaybackofimprovementsand

doesnotincentivizerapidadoption.Inthesesectorsthereislimitedlandlordcontrolwiththemajorityofenergyconsumptionbytenants.Tenantengagement,includingthroughgreenleasing8,isessential.

Overall,therealestatesectorhasthecapabilities

totransitiontoalowcarbonmodel,spurredonby

emergingtechnologyandcertaintyofferedbyclearergovernmentpolicy.However,thehighlevelsofcapitalexpenditurerequiredmeansthatthereisariskof

strandedassets.

Figure1:Occupationalrequirementscomparedtodevelopmentpipeline

Supply/demand

UNITEDSTATES

5.3

1.8

7.1

DEMANDSUPPLY

75%

unmet

demand

EUROPE

2.2

1.7

3.9

DEMANDSUPPLY

57%

unmet

demand

ASIAPACIFIC

4.6

2.7

1.9

DEMANDSUPPLY

59%

unmet

demand

Source:JLL2024

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Infrastructure

Thetransitiontoalowcarboneconomythat

supportseconomic

growthisbeingdrivenbyambitiousglobalgoals

andrapidlyincreasingdemandsforpower.

Climategoalstopofmindin

drivingdemandforrenewables,decarbonization

Tomeetthesedemands,theInternationalEnergyAgencyexpectsinvestmentin

renewablesmustdoubleto￡1.2trillionperyearby2030.

AtCOP28,nearly200nationsagreed

totriplerenewableenergycapacityanddoubleenergyefficiencyby2030tomeetinternationalnetzerogoalsasoutlinedintheParisAgreement.9

TheEUrevisedRenewableEnergyDirective,adoptedin2023,raisestheEU’sbinding

renewableenergytargetfor2030toa

minimumof42.5%.Astheenergysectoris

responsibleformorethan75%oftheEU’sgreenhousegasemissions,increasingthe

shareofrenewableenergyacrossdifferentsectorsoftheeconomyiskeytoreducingnetgreenhousegasemissionsbyatleast55%

by2030,andtobecomingaclimate-neutralcontinentby2050.10

Thesecommitmentsreflecttheurgentneedtoreducecarbonemissions,presenting

newopportunitiestodeploycapitalintothesector.Overthepastdecade,thegrowthofrenewableenergy,suchaswindandsolar,hasconsistentlyoutperformedexpectationswhilstthecosttodeployrenewableshas

decreasedcconsiderablyandthisgrowthstoryisonlygettingstronger.11

Carbonintensityofelectricitygeneration,2000-2013

Gramsofcarbondioxide-equivalentsemittedperkilowatt-hourofelectricitygenerated

AsiaUnitedStatesEurope(Ember)World

700

600

500

400

300

200

100