AI基础设施趋势报告 AI infrastructure trends report 2026

2026

AI

infrastructuretrendsreport

Page02

Contents

03Executivesummary

04Introduction

05Keyinsights

06Methodology

07Insight1

Efficiencyisacatalystforinnovation09Insight2

Dependability,cost-effectiveness,

andtransparencyarenon-negotiable012Insight3

Greatercontrolprovidesgreaterconfidence014Insight4

Expertsupportfillsknowledgegaps016Insight5

Adaptabilityandsimplicityarerequirements018Insight6

ResponsibleAIandsustainabilityarerisingpriorities

020AIwillprovidetheedge,andinfrastructurewilldecidewhowins

021Buildingthefuturefaster:partneringfortransformativegrowth

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Executivesummary

Notlongago,AIwasconsideredanexperiment,handedoff

totechteamseagertoexploreitspossibilities.Today,it’s

rewiringhowbusinessesoperate,solvechallenges,anddrivegrowth.Acrosseveryindustry,teamsareracingtotapintothevalueoflargelanguagemodels(LLMs),automation,and

next-generationintelligenttoolsasAIbecomesanessentialpartofeverydaywork.

TheAIimperative

Tobetterunderstandhoworganizationsarenavigatingthisshiftastheymoveinto2026,CrusoepartneredwithMetaLabtosurveyandinterviewenterpriseand

digital-nativebusiness(DNB)leadersonthefrontlinesofambitiousAIimperatives.

Thefindingspaintaclearpicture:teamsareturningtoAItoclearawayfriction

andfreeupresources—notsimplytodomorewithless,buttocreatespace

forcreativityandinnovationtoflourish.Onerespondentputitthisway:“AIwillbecentraltoourinnovationstrategy,helpingusstayaheadofindustrytrendsanddelivercutting-edgesolutionsthatdifferentiateusinthemarket.”

ButthisracetorealizeAI’spromiseisfarfromstraightforward.Despitestrongambition,mostorganizationsfaceahostofinfrastructure-relatedbarriers.

Barrierstobuildingthefuture

Thestrugglepersistsbecausethetraditionalcloudecosystemwasnotdesignedfortheageofintelligentautomation.Decision-makersinourresearchsurfaceacommonsetofchallenges:

•PerformancebottlenecksanddowntimethaterodeconfidenceandslowAIprojectdelivery

•Unpredictableandopaquecoststhatmakeitnearlyimpossibletoscaleresponsibly

•Fragmentedsupportandalackofdomainexpertise,leavingorganizationswithgapsbetweenambitionandexecution

•Limitedcontrolovercriticalinfrastructure,makingteamsvulnerable

Throughoutthisreport,weexaminethesepersistentbarriers—and,moreimportantly,explorestrategiesforovercomingthem.

Infrastructureasthenewdifferentiator

Forward-lookingteamsarerethinkingnotjusthowtheyuseAI,butalsohowthey

buildit.They’refindingabetterwaywithinfrastructurepartnerswhocanenable

speedandperformancewithoutcompromisingsecurity,sustainability,oreaseof

use.ThisistheshiftCrusoeispioneering:averticallyintegratedapproach,builtfromthegroundupforAI.ThisAIfactorymodelverticallyintegratesenergy,hardware,

datacenter,cloud,andmanagedAIservicesintoasingle,cohesiveplatform.It’sanewparadigmthatacceleratesvaluecreationwhilealigningwiththedemandsofbothtoday’sbusinessandthefuturewell-beingofpeopleandtheplanet.

Ifyou’renavigatingAIinitiatives,ourresearchoffersaroadmap—andacalltoaction.We’llshowhowanew,purpose-builtapproachtoAIinfrastructureisenabling

organizationstomovefaster,withgreatercontrol,tocreatemeasurableimpact.

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Introduction

Acrossnearlyeverysector,theconversationaroundAI

haschanged.RatherthanaskingwhereAIcanaddvalue,

teamsarenowactivelyseekingwaystotranslateAI’spotentialintorealbusinessresultsatscaleandatspeed.Inpractice,

thismeansdeployingAIforfrauddetection,predictive

analytics,intelligentdocumentprocessing,supplychainoptimization,customerserviceautomation,personalizedmarketing,andmore.

ImplementingAIshouldbe

straightforward,buttherealityfor

mostorganizationsisriddledwith

roadblocks.Inconsistentaccessto

high-performancecompute,sluggish

deploymentcycles,operational

complexity,limitedcontroloverdata

environments,andunpredictablecostsallconspiretoslowprogress.Theresultisawideninggapbetweenwhat’s

possiblewithAIandwhat’sactually

beingdelivered.We’reataninflectionpointaswelooktothefutureofwhatAIwillenable.Togetthere,it’ssimplynotenoughtoadvanceincrementally.

Thisreportprovidesadata-driven

perspectivefromleadersatthecenterofAItransformation,offeringablueprintforachievingambitiousgoalsthroughinfrastructurethat’sdesignedforthe

futureofAI.

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Key

insights

1.Efficiencyisacatalystforinnovation

AIisbeingdeployedfirstandforemosttodriveoperationalefficiency.Butforleadingorganizations,efficiencyisjustthelaunchpad.Byclearingfrictionandfreeingupresources,AIispavingthewayforfreshcreativity,fasterinnovationcycles,andstrongerbusinessimpact.

2.Dependability,cost-effectiveness,andtransparencyarenon-negotiable

CompaniesbuildingAIexpecttheircloudproviderstodeliverreliable

performance,predictablecosts,andtransparency.Yet,mostfindthatcurrentproviders—especiallyhyperscalers—fallshort.Persistentgapsherelimit

businessvalueandstallAIprogress.

3.Greatercontrolprovidesgreaterconfidence

Leadersareincreasinglyuneasywithover-relianceontraditionalcloud

vendorsandopaquesystems.They’redemandingmoredirectcontrolover

theirAIinfrastructuretominimizesurprises,reducerisk,andensuretheir

goalsaren’tlimitedbysomeoneelse’sroadmap.Theshifttowardend-to-endintegrationreflectsanewexpectation:infrastructurepartnersshouldclear

hurdlesandempowerteamstobringtheirvisiontolife.

4.Expertsupportfillsknowledgegaps

AIadoptionisoutpacinginternalexpertise.Buildersarelookingtocloud

partnersforproactive,expertsupportthatcanbridgeinternalknowledge

gapsandacceleratesuccess.Manyarewillingtoswitchprovidersforbettersupport,evenwhentechnologyiscomparable.

5.Adaptabilityandeaseofusearerequirements

ThegrowingcomplexityofAIandcloudenvironmentsisaweightonboth

businessandtechnicalteams.CompaniesbuildingAIwantadaptable,

easy-to-usesolutionsthatreducetheburdenofintegration,supportarangeofworkflows,andmakeitsimpleforteamstodeliverresultsatscale.

6.ResponsibleAIandsustainabilityarerisingpriorities

Whilenotalwaysthefirstfilterforselection,responsibleAIpracticesand

sustainabilityaregainingground—particularlyfordigital-nativebusinessesandasESGcommitmentsshapelong-termpriorities.Providerswho

demonstrateacommitmenttoresponsibleAIandsustainableoperationsareincreasinglyfavored.

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Methodology

QuantitativesurveyMarch2025

Participantsincluding:

152

70

Decision-makers

Influencers

(C-suite,VPs,ExecutiveDirectors)

(Directors,SeniorManagersin

fromlargeenterprises($500M+inrevenueor$8B+valuation)

AI/ML/Engineering)

79

31

Decision-makers

Practitioners

fromdigital-nativebusinesses

(DataScientists,Developers,Engineers)

CrusoeengagedMetaLabtoconductanin-depth,mixed-methodsresearchstudythatwouldcaptureboththebreadthanddepthofdecision-maker

experienceacrossindustries.

Respondentsweredrawnfromacross-sectionofindustries,includingtechnology,mediaandentertainment,manufacturing,automotive/robotics,enterpriseSaaS,

andgeneralsoftware.AllparticipantshaddirectresponsibilityforevaluatingorimplementingAIandcloudinfrastructurewithintheirorganizations.

Qualitativeinterviews

Inadditiontothesurvey,in-depthinterviewswereconductedwithselect

decision-makers.Theseconversationsprovidedrichercontextandfirsthandperspectiveonproviderselection,painpoints,andemergingneeds.

Samplerigorandcomposition

•TheresearchincludedorganizationsfromNorthAmericaandkeyglobalmarkets.

•Industryquotasensuredbalancedrepresentationacrossmajorsectors.

•Alldecision-makerssurveyedhaddirectstrategicorbudgetaryinfluenceoverAI/cloudinvestments,ensuringexecutive-levelperspectiveandactionableinsight.

Stakeholderandecosystemlens

Tofurthergroundtheresearchinreal-worlddelivery,weintegratedinputfrom15

internalCrusoestakeholdersandlayeredincompetitiveandtrendanalysisacrosstheAI/cloudecosystem.

Theresultisaresearch-backedviewintowhatdecision-makerstrulyneedfromtheirAIinfrastructurepartners,whatstandsintheirway,andwherethenext

opportunitiesforvaluecreationaredeveloping.

Insight

Efficiencyisacatalystforinnovation

ForAIleaders,capturingthevalueofAIbeginsnot

withmoonshots,butwithimmediategainsinefficiency.Acrossourresearch,thesinglemostcommon

motivatorforAIinvestmentisamandatetostreamlineoperationsandfreeupresources.69%oftheleaderswesurveyedsayimprovingoperationalefficiencyis

theirtoppriorityforAIinitiatives.

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Insight1:Efficiencyisacatalyst

forinnovation

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Decision-makers’motivationsfordrivingAIinitiatives

Butdecision-makersareclearthat

operationalefficiencyisnotthe

ultimategoal.Rather,it’saspringboardforsomethinggreater.55%of

respondentsprioritizeAIasameanstoincreaserevenue,and52%see

itasapathwaytodriveinnovation.

Thissignalsthatefficiencygainsaremeanttofuelbroaderbusinessvalue.51%citestayingcompetitiveasa

primarymotivator,recognizingthateveryadvantagesecurednowcouldbethedifferencebetweenleadingcompetitorsorplayingcatch-up.

Thisperspectiveisechoedacross

industriesandorganizationaltypes

inopen-endedresponses.One

executivecapturedthesentimentthisway:“Byautomatingkeyaspectsofouroperations,we’llbeabletodrastically

reduceinefficienciesandcutdownonhumanerror.Thiswillfreeupourteamstofocusonmorecreativeandstrategictasks,leadingtofasterinnovation

cyclesandbetterdecision-makingpoweredbydata-driveninsights.”

Percentage(%)

69%Improveoperationalefficiency

58%Enhancethecustomerexperience

55%Increaserevenue

52%Driveinnovation

52%Staycompetitiveinthemarket

50%Enablenewbusinessmodels

23%

Pressurefrominvestors

29%Drivedifferentiation

Thebottomline:

Efficiencycreatescapacityforwhatcomesnext.OrganizationsthatuseAItoclearoperationalfrictionarepositioningthemselvestocapturenewopportunities,adapttochange,andleadtheirmarketswithspeedandcreativity.

Insight

Dependability,

cost-effectiveness,andtransparency

arenon-negotiable

AIcloudinfrastructuremustdomorethanprovidecomputepower.Ourresearchrevealsthattoday’sleadersviewcostcontrol,security,performance,reliability,andscalabilityastablestakesforasuccessfulAIinitiative.

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Insight2:Dependability,cost-effectiveness,

andtransparencyarenon-negotiable

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AIcloudinfrastructuremustdomorethanprovidecomputepower

AttributeTablestakesDifferentiatedNotimportant

Yettherealityofthecurrentmarket

oftenleavesorganizationsinthelurch.Manyteamscontinuetoencounter

gapswheretheseexpectationsare

concerned,especiallyasworkloads

scaleinsizeandcomplexity.Oneleaderputitthisway:“Thecloudprovider

weuseacrossourenterprisemust

beeasilymaintained,beperformant,bewellsupported,andmeetour

compliancestandards.Otherwise,allourAIinitiativeswilljustfail.”

Ourdatarevealsthepainpointswithhyperscalersaroundthesenon-negotiables:

•Securityandcomplianceconcernswereratedasthemostpressing

painpoint,withanaveragerelevancescoreof6.86outof10.

•Performanceissues(includingdowntimeandlatency)followedclosely,at6.84outof10.

•Scalabilitychallenges—theability

toflexresourcesasbusinessneedsevolve—camethird,at6.65outof10.

•Costmanagement(unpredictable

pricing,hiddenfees)wasratedfourth,at6.58outof10.

Cost

Security&compliance

Performance

Enterprisescaleinfrastructure

Reliability

Scalability

Easeofintegration

Managedservices

(

e.g.training

inference)

Note:Tablestakescriteriawereconsistentacrossorganizationtype(enterprisevs.DNB)andindustry

Insight2:Dependability,cost-effectiveness,

andtransparencyarenon-negotiable

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Decision-makers’hyperscalerpainpoints

Weightedrank

6.84

Performanceissues(e.g.downtime,latency,inconsistentservicequality)

6.65

Scalabilitychallenges(

e.g.limited

flexibility,resoucecontraints,difficultyautomatingscaling)

Costmanagement(e.g.unpredicatablepricing,hiddenfeed,highchargesforscaling)

6.17

Suppportandcustomerservice(e.g.slowresponsetimes,poorqualityofsupport,lackofpraocativeassistance)

6.58

Inotherwords,whatmanyproviders

advertiseasdifferentiatorsare

6.86

Securityandcomplianceconcerns(

e.g.data

privacyissues,inadequatesecuritymeasures,

compliancechallenges)

actuallythebareminimumneededforenterprisesandDNBstosucceedwithAI.Adecision-makerexplained:“Oneofthebiggestchallengeswefacewith[ourcloudprovider]ismanagingcostsandscalability,aspricescanescalatequicklywithincreasedusage.ThiscanlimitourabilitytoscaleAIinitiatives

efficientlyandmayrequireadditionalbudgetplanning.

5.98

Integrationandcompatibility(e.g.difficultyintergatingwithexistingsystems,vendorlock-in)

4.88

Complexity(e.g.steeplearningcurve,

managementoverhead)

4.644.63

Datatransferandstorage(e.g.highdata

transfercosts,inefficientstoragemanagement)

Vendorlock-inandmigration(e.g.difficultymigratingworkloads,highmigrationcosts)

3.53Environmentalimpact(e.g.highcarbonemissions,unsustainableinfrastructure)

Thebottomline:

Uncompromisingdependability,cost-effectiveness,andtransparencyarethenewbaselineforbuildingwithAI.

Insight

Greatercontrolprovidesgreaterconfidence

AsAIambitionsintensify,sodotheanxietiesaround

dependenceontraditionalcloudproviders.Manyleadersinourstudyvoicedagrowingsenseofvulnerabilityas

over-relianceonthird-partycloudsleavesorganizations

exposedtounexpecteddisruptions,costspikes,performanceinconsistencies,andshiftingproviderpriorities.

Thisquestforagencyisproducingashiftinhowdecision-makersevaluateAIinfrastructurepartners.Leaderspinpointtheneedfordirectoversightofperformanceandsecurity,ratherthan

outsourcingcoreoperationstofragmentedsupplychainsorexternalvendors.

VerticalintegrationinanAIfactorymodel,givingteams

completecontroloverthefullAIstack,isemergingasahighlydifferentiatedattribute.Inourstudy,98%ofdecision-makersrated“completecontrol(building,owning,andoperating)overtheirowndatacenters”asimportant.Notably,itwastheonly

attributemoreoftenseenasadifferentiatorthanameretablestake,outscoringevenestablishedprioritieslikeperformance,security,andreliability.

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Insight3:Greatercontrolprovidesgreaterconfidence

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Importanceofcloudprovider

attributesfordecisionmakers

Onetermthatsurfacedasespecially

resonantintheresearchis“theAI

factory.”Whilehyperscalerswere

designedforgenericdatastorageandcompute,decision-makersnowexpectproviderstobe“purposefullybuiltfor

AI”—fromthephysicalinfrastructuretothesoftwarelayerandeverythinginbetween.

DefiningtheAIfactory:

Averticallyintegratedapproach

Legacycloudswerenotbuiltto

deliverwhattoday’sleadersdemand:independentcontrol,transparency,

andpurpose-builtperformance.EntertheAIfactory,anewparadigmforthefutureofenterpriseAI.

TheAIfactoryisanend-to-end,

verticallyintegratedplatformthat

uniteseverylayerofthestack—fromenergysourcing,tohigh-performancedatacenterconstruction,totheAI

cloudandmanagedservicesthat

bringitalltogether.Unlikelegacy

providersthatpatchtogethergenericcomputeandstoragesolutions,theAIfactoryisspecificallydesignedfortheuniquespeed,scale,andcomplexityofmodernAIworkloads.

Fordecision-makers,verticalintegrationtranslatesintomorethanefficiency

alone.Itgivesorganizations:

•Greatercontrolovertheirowndestiny

•Reducedriskandfewerpointsoffailure

•Improvedperformanceandreliability

Normalizedutilityranking

100%High-performance

99%Security&compliance

98%Reliability

98%

Completecontrol(building,owningandoperating)overtheirowndatacentres(i.everticalintegration)

97%ManagedAIservices

97%Easeofintegrationwithexistinginfrastructure95%ResponsibleAIpractices

Thebottomline:

Becauseverticalintegrationissotiedtotangiblebusinessbenefits—control,speed,riskmitigation—it’sbecomeacompelling,highly

valuedapproach.FortheleadersreshapingAI,controllingmoreofthestackisthesurestwaytobuildwithconfidence,adaptquickly,and

unlockthefullpromiseofAI.

Insight

Expertsupportfillsknowledgegaps

AsorganizationsacceleratetheirAIambitions,manyare

comingupagainstalackofinternaltechnologicalexpertise.

Inourresearch,decision-makersconsistentlycitedcomplexityinAImodeldevelopmentanddeploymentastheirgreatest

roadblock,closelyfollowedbyalackofskilledAItalentontheirteams.Onerespondentexplains:“ThebiggestbarrierisalackofskilledAItalent.ThisiscausingadelayinourAIadoption,

impactingourabilitytoinnovateandkeeppacewithcompetitors.”

Mostorganizationshaven’tyetbuiltoutthedeepin-house

expertiserequiredtodevelop,deploy,andmaintainAIatscale.Thechallengeiscompoundedbyacrowdedecosystemoftoolsandservices,whereevenexperiencedtechnicalteamscan

struggletoidentifybestpracticesortroubleshootcomplexissues.

Thisiswheretheroleofthecloudproviderisbeingfundamentallyredefined.Expert-level,proactive,andconsultativesupportisacriticaldifferentiatorand,insomecases,thedecidingfactorwhenselectingorretainingaprovider.Manyorganizationsinourstudyhavedroppedvendorswhodeliveredontechnologybutfailedtodeliveronpartnershipandsupport.

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Insight4:Expertsupportfillsknowledgegaps

Initiatives

Decision-Makers’BarriersforAI-Driven

Thenumbersmakethestakesclear:

•“ComplexityofAImodel

developmentanddeployment”

rankedasthetopchallenge,with

anaveragerelevancescoreof5.40outof10.

•“LackofinternalAIexpertise”closelyfollowedat5.16.

•Inopen-endedresponses,decision-makersrepeatedlyemphasizedthe needfor“knowledgeableguidance,”“proactiveinsight,”and“real-time

troubleshooting”—oftenplacingasmuchvalueonexpertsupportasontechnologyfeatures.

Oneleaderstates:“We’vedropped

cloudproviderswherethetechwas

better,buttheirteamwasn’tgood

enough.Theycouldn’tkeepupwith

us.Weexpectthoughtleadershipandknowledgeablesupport.”

Ultimately,leadersneedmorethanahelpdesk.Theywantatruepartnerwhocanproactivelyidentifyrisksandopportunities,guidingteamsthroughunfamiliarterritory.Theyvaluedeep,domain-specificexpertiseandreal-worldbestpractices.Andtheyneed24/7,high-touchsupport,notjust

ticket-basedtroubleshooting.

Weightedrank

5.405.32

ComplexityofHighCosts

AImodeldevelopmentanddeployment

5.16

LackofInternalAIexpertise

5.10

Dataprivacyandsecurityconcerns

4.404.28

3.98

Lackofinfrastrucutre

Regulatoryorcomplianceconcerns

3.47Lackofleadershipbuiy-in

UncertainROI

Thebottomline:

ExpertsupportiscriticaltoasuccessfulAIimplementation.The

organizationsthatsucceedwillbethosethatsurroundthemselveswiththerightmixoftechnologyandpartnership,bridgingknowledgegaps

andempoweringteamstomovefrompilottoproductionwithconfidence.

Insight

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Adaptabilityandease

ofusearerequirements

AsteamsdeploymoreadvancedAImodelsandworkflows,

complexityhasbecomeastubbornroadblock.Acrossour

research,adaptabilityandeaseofuseemergedashigh-impactcriteria,especiallyforcompaniesjugglinglegacysystems,newcloud-nativeworkloads,andhybridoperatingenvironments.

Easeofuseisthemostfrequentlycitedexperientialgap

inhyperscalersolutions.Inopen-endedsurveyresponses,

decision-makersflaggedsteeplearningcurves,convoluted

userinterfaces,andtheneedforspecializedtrainingasmajorfrictionpoints.“We’vedefinitelyfeltagapwhenitcomesto

easeofuse.Asmuchaswelovethescalabilityandfeatures,we’vestruggledwiththecomplexityofcertainservices,”onerespondentexplained.

Seamlessintegrationwithexistinginfrastructureisanothertoppriority—particularlyforenterprises.Enterprise

decision-makersrankedintegrationasthefifthmost

importantattributewhenchoosingaprovider(DNBsrankediteighth),underscoringthechallengesofconnectingnew

AIplatformswithestablished,mission-criticalsystems.

Compatibilityissues,delayedrollouts,andtheneedfor

customworkaroundscanallstallprogressandinflatecosts.

Oneleaderputitsimply:“ThebiggestgapIhavewithAIcloudprovidersisthegapbetweenexpectationsandrealityintermsofeaseofuseandsupportforspecificAIneeds.”

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Insight5:Adaptabilityandeaseofusearerequirements

Importanceofcloudprovider

attributesfordecisionmakers

Keyfindings:

•“Easeofintegrationwithexisting

infrastructure”isratedasimportantby97%ofalldecision-makers.

Fordecision-makerswithlowerAI

confidenceorlessinternalexpertise,thedemandforadaptabilityis

evengreater.Theseleaderswant

moreindustry-specificsupportandtoolstobridgegapsintechnical

knowledgeandreducetheirteams’relianceonoutsideconsultants.

•Adaptablesolutionsthatcanflex

acrossindustriesandusecases

arealsohighlyvalued,with40%ofrespondentssayingtheyrequire

morespecializedsupportor

customizationtomeettheuniquedemandsoftheirsector.

AsAIcomplexitygrows,leadersare

searchingforsolutionsthattake

frictionoutoftheequation.Theyneedtoolsthatareintuitivetouse,integrateseamlesslywithexistingsystems,andadapttotheuniquedemandsoftheirindustryandteams.

Normalizedutilityranking

Completecontrol(building,owningandoperating)overtheirowndatacentres(i.everticalintegration)

95%ResponsibleAIpractices

99%Security&compliance

97%ManagedAIservices

100%High-performance

Easeofintegrationwithexistinginfrastructure

98%Reliability

98%

97%

Thebottomline:

Adaptabilityandeaseofusearenolonger“nicetohave”features.Theyareessentialforreducingcomplexity,acceleratingtime-to-value,andmakingAIaccessibletotheteamsthatwilldrivethe

nextwaveofinnovation.

Insight

ResponsibleAIandsustainabilityarerisingpriorities

AsAI’sreachexpands,sodoexpectationsforresponsible

useandmitigatingenvironmentalimpact.Whilecost,

performance,andreliabilitystilltopthelistformost

organizations,ourresearchshowsthatresponsibleAIand

sustainabilityarerisingrapidlyasdecisioncriteria—especiallyfordigital-nativebusinessesandESG-drivenorganizations.

ForDNBs,“responsibleAIpractices”rankedasthefifth

mostimportantattributewhenevaluatingcloudproviders

(outof15total),whileforenterprises,itrankedeighth.Many

respondentspredictthatastheirAIinitiativesmature—andasregulatoryandESGframeworksevolve—theseconsiderationswillbecomeessential,notoptional.

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Insight6ResponsibleAIandsustainabilityarerisingpriorities

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Iwillsay,responsibleAIpracticesareofemergingimportancetous.Wewanttomakesuretherearen’tanydestructive

ornegativeconsequencestotheworkweareputtingout[totheworld].

Decision-Maker

CEO&Co-founder

RealEstateFranchise

Akeyaspectofthisshiftistransparencyaroundenergysourcing.Increasingly,buildersexpectproviderstoclearly

demonstratehowAIworkloadsarepowered,particularlywithregardtorenewableenergy.Dissatisfactionisgrowingwithvagueorunsupportedsustainabilityclaims.FormanycompaniesandESG-focusedorganizations,energysourcingisnowviewedasanextensionofresponsibletechnology,and,insomecases,atiebreaker.Asoneleaderputit:“Toguarantee

responsibleandethicaldevelopmentanddeploymentofAI[solutions]at[ourorganization],wewillalwaysconsiderproviders’practices.”

Thecallforclarity,specificity,andproactivecommitmentisunmistakable.ResponsibleAIpracticesareincreasinglyatiebreaker—and,forsomeorganizations,aprerequisiteforconsiderationatall.

Thebottomline:

ResponsibleAIandsustainabilitymaynotbethefirstconcernforeveryorganizationtoday.Butasexpectationsriseandthemarketmatures,leadersrecognizethatthesevaluesarefastbecominga

definingstandardthatwillshapebothcompetitivepositioningandsocietaltrustintheeraofAI.

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AIwillprovidetheedge,and

infrastructurewilldecide

whowins

Asorganizati