埃森哲：生成式人工智能：人人可享的新时代报告-23正式版

AneweraofgenerativeAIforeveryoneThetechnologyunderpinningChatGPTwilltransformworkandreinventbusiness每日免费获取报告1、每日微信群内分享7+最新重磅报告；2、每日分享当日华尔街日报、金融时报；3、每周分享经济学人4、行研报告均为公开版，权利归原作者所有，起点财经仅分发做内部学习。扫一扫二维码关注公号回复：研究报告加入“起点财经”微信群。。TableofContents0304050812WelcometoAI’snewinflectionpointHowdidwegethere?|MilestonesinthejourneytogenerativeAIConsumeorcustomize:GenerativeAIforeveryoneAlookaheadatthefast-pacedevolutionoftechnology,regulationandbusinessEmbracethegenerativeAIera:SixadoptionessentialsThefutureofAIisaccelerating1921GlossaryandReferences22AuthorsAneweraofgenerativeAIforeveryone|2IntroductionWelcometoAI’snewinflectionpointChatGPThaswokenuptheworldtothetransformativepotentialofartificialintelligence(AI),capturingglobalattentionandsparkingawaveofcreativityrarelyseenbefore.Itsabilitytomimichumandialogueanddecision-makinghasgivenusAI’sfirsttrueinflectionpointinpublicadoption.Finally,everyone,everywherecanseethetechnology’struedisruptivepotentialforthemselves.Afoundationmodelisagenerictermforlargemodelswithbillionsofparameters.Withrecentadvances,companiescannowbuildspecializedimage-andlanguage-generatingmodelsontopofthesefoundationmodels.Largelanguagemodels(LLMs)arebothatypeofgenerativeAIandatypeoffoundationmodel.Businessleadersrecognizethesignificanceofthismoment.TheycanseehowLLMsandgenerativeAIwillfundamentallytransformeverythingfrombusiness,toscience,tosocietyitself—unlockingnewperformancefrontiers.Thepositiveimpactonhumancreativityandproductivitywillbemassive.Considerthat,acrossallindustries,Accenturefound40%ofallworkinghourscanbeimpactedbyLLMslikeGPT-4.Thisisbecauselanguagetasksaccountfor62%ofthetotaltimeemployeeswork,and65%ofthattimecanbetransformedintomoreproductiveactivitythroughaugmentationandautomation(seeFigure3).TheLLMsbehindChatGPTmarkasignificantturningpointandmilestoneinartificialintelligence.TwothingsmakeLLMsgamechanging.First,they’vecrackedthecodeonlanguagecomplexity.Now,forthefirsttime,machinescanlearnlanguage,contextandintentandbeindependentlygenerativeandcreative.Second,afterbeingpre-trainedonvastquantitiesofdata(text,imagesoraudio),thesemodelscanbeadaptedorfine-tunedforawiderangeoftasks.Thisallowsthemtobereusedorrepurposedinmanydifferentways.ChatGPTreached100millionmonthlyactiveusersjusttwomonthsafterlaunch,makingitthefastest-growingconsumerapplicationinhistory.1AneweraofgenerativeAIforeveryone|3Howdidwegethere?Machinelearning:AnalysisandpredictionphaseThefirstdecadeofthe2000smarkedtherapidadvanceofvariousmachinelearningtechniquesthatcouldanalyzemassiveamountsofonlinedatatodrawconclusions–or“learn”–fromtheresults.Sincethen,companieshaveviewedmachinelearningasanincrediblypowerfulfieldofAIforanalyzingdata,findingpatterns,generatinginsights,makingpredictionsandautomatingtasksatapaceandonascalethatwaspreviouslyimpossible.MilestonesinthejourneytogenerativeAIDeeplearning:VisionandspeechphaseThe2010sproducedadvancesinAI’sthatsearchenginesandself-drivingcarsusetoclassifyanddetectobjects,aswellasthevoicerecognitionthatallowspopularAIspeechassistantstorespondtousersinanaturalway.perceptioncapabilitiesinthefieldofmachinelearningcalleddeeplearning.BreakthroughsindeeplearningenablethecomputervisionGenerativeAI:Enterthelanguage-masteryphaseBuildingonexponentialincreasesinthesizeandcapabilitiesofdeeplearningmodels,the2020swillbeaboutlanguagemastery.TheGPT-4languagemodel,developedbyOpenAI,marksthebeginningofanewphaseintheabilitiesoflanguage-basedAIapplications.Modelssuchasthiswillhavefar-reachingconsequencesforbusiness,sincelanguagepermeateseverythinganorganizationdoesdaytoday—itsinstitutionalknowledge,communicationandprocesses.2AneweraofgenerativeAIforeveryone|4Consumeorcustomize:GenerativeAIforeveryoneAneweraofgenerativeAIforeveryone|5Consumeorcustomize:GenerativeAIforeveryoneConsumeorcustomize:GenerativeAIforeveryoneEasy-to-consumegenerativeAIapplicationslikeChatGPT,DALL-E,StableDiffusionandothersarerapidlydemocratizingthetechnologyinbusinessandsociety.Theeffectonorganizationswillbeprofound.TheabilityofLLMstoprocessmassivedatasetsallowsthemtopotentially“know”We’reataphaseintheadoptioncyclewhenmostorganizationsarestartingtoexperimentbyconsumingfoundationmodels“offtheshelf.”However,thebiggestvalueformanywillcomewhentheycustomizeorfinetunemodelsusingtheirowndatatoaddresstheiruniqueneeds:everythinganorganizationhaseverknown—theentirehistory,context,nuanceandintentofabusiness,anditsproducts,marketsandcustomers.Anythingconveyedthroughlanguage(applications,systems,documents,emails,chats,videoandaudiorecordings)canbeharnessedtodrivenext-levelinnovation,optimizationandreinvention.ConsumeGenerativeAIandLLMapplicationsarereadytoconsumeandeasytoaccess.CompaniescanconsumethemthroughAPIsandtailorthem,toasmalldegree,fortheirownusecasesthroughpromptengineeringtechniquessuchasprompttuningandprefixlearning.Customize97%ofglobalexecutivesagreeAIfoundationmodelswillenableconnectionsacrossdatatypes,revolutionizingwhereButmostcompanieswillneedtocustomizemodels,byfine-tuningthemwiththeirowndata,tomakethemwidelyusableandvaluable.Thiswillallowthemodelstosupportspecificdownstreamtasksallthewayacrossthebusiness.Theeffectwillbetoincreaseacompany’sefficacyinusingAItounlocknewperformancefrontiers—elevatingemployeecapabilities,delightingcustomers,introducingnewbusinessmodelsandboostingresponsivenesstosignalsofchange.andhowAIisused.3AneweraofgenerativeAIforeveryone|6Consumeorcustomize:GenerativeAIforeveryoneCompanieswillusethesemodelstoreinventtheCreating.GenerativeAIwillbecomeanessentialcreativepartnerforpeople,revealingnewwaystoreachandappealtoaudiencesandbringingunprecedentedspeedandinnovationinareaslikeproductiondesign,designresearch,visualidentity,naming,copygenerationandtesting,andreal-timepersonalization.Companiesareturningtostate-of-the-artartificialintelligencesystemslikeDALL·E,MidjourneyandStableDiffusionfortheirsocialmediavisualcontentgenerationoutreach.DALL·E,forexample,createsrealisticimagesandartbasedontextdescriptionsandcanprocessupto12billionparameterswhentransformingwordsintopictures.ImagescreatedcanthenbesharedAutomating.GenerativeAI’ssophisticatedunderstandingofhistoricalcontext,nextbestactions,summarizationcapabilities,andpredictiveintelligencewillcatalyzeaneweraofhyper-efficiencyandhyper-personalizationinboththebackandfrontoffice—takingbusinessprocessautomationtoatransformativenewlevel.OnemultinationalbankisusinggenerativeAIandLLMstotransformhowitmanagesvolumesofpost-tradeprocessingemails—automaticallydraftingmessageswithrecommendedactionsandroutingthemtotherecipient.Theresultislessmanualeffortandsmootherinteractionswithcustomers.wayworkisdone.Everyroleineveryenterprisehasthepotentialtobereinvented,ashumansworkingwithAIco-pilotsbecomesthenorm,dramaticallyamplifyingwhatpeoplecanachieve.Inanygivenjob,sometaskswillbeautomated,somewillbeassisted,andsomewillbeunaffectedbythetechnology.Therewillalsobealargenumberofnewtasksforhumanstoperform,suchasensuringtheaccurateandresponsibleuseofnewAI-poweredsystems.Considertheimpactinthesekeyfunctions:Advising.AImodelswillbecomeanever-presentco-pilotforeveryworker,boostingproductivitybyputtingnewkindsofhyper-personalizedintelligenceintohumanhands.Examplesincludecustomersupport,salesenablement,humanresources,medicalandscientificresearch,corporatestrategyandcompetitiveintelligence.Largelanguagemodelscouldbeusefulintacklingtheroughly70%ofcustomerservicecommunicationthatisnotstraightforwardandcanbenefitfromaconversational,powerfulandintelligentbot,understandingacustomer’sintent,formulateanswersonitsownandimprovetheonInstagramandTwitter.5Protecting.Intime,generativeAIwillsupportCoding.SoftwarecoderswillusegenerativeAItoenterprisegovernanceandinformationsecurity,protectingagainstfraud,improvingregulatorycompliance,andproactivelyidentifyingsignificantlyboostproductivity—rapidlyconvertingoneprogramminglanguagetoanother,masteringprogrammingtoolsandmethods,automatingcodewriting,predictingandpre-emptingproblems,andmanagingsystemdocumentation.AccentureispilotingtheuseofOpenAILLMstoenhancedeveloperproductivitybyautomaticallygeneratingdocumentation–forexample,SAPconfigurationrationaleandfunctionalortechnicalspecs.ThesolutionenablesuserstosubmitrequeststhroughaMicrosoftTeamschatastheywork.Correctlypackageddocumentsarethenreturnedatspeed—agreatexampleofhowspecifictasks,ratherthanentirejobs,willbeaugmentedandautomated.riskbydrawingcross-domainconnectionsandinferencesbothwithinandoutsidetheorganization.Instrategiccyberdefense,LLMscouldofferusefulcapabilities,suchasexplainingmalwareandquicklyclassifyingwebsites.6Intheshortterm,however,organizationscanexpectcriminalstocapitalizeongenerativeAI’scapabilitiestogeneratemaliciouscodeorwriteaccuracyandqualityofanswers.4theperfectphishingemail.7AneweraofgenerativeAIforeveryone|7Alookaheadatthefast-pacedevolutionoftechnology,regulationandbusinessAneweraofgenerativeAIforeveryone|8Alookaheadatthefast-pacedevolutionoftechnology,regulationandbusinessAlookaheadatthefast-pacedevolutionoftechnology,regulationandbusinessMomentslikethisdon’tcomearoundoften.ThecomingyearswillseeoutsizedinvestmentingenerativeAI,LLMsandfoundationmodels.What’suniqueaboutthisevolutionisthatthetechnology,regulation,andbusinessadoptionareallacceleratingexponentiallyatthesametime.Inpreviousinnovationcurves,thetechnologytypicallyoutpacedbothadoptionandregulation.Figure1:EachlayerofthegenerativeAItechstackwillrapidlyevolveApplications:GenerativeAIandLLMswillbeincreasinglyaccessibletousersinthecloudviaAPIsandbybeingembeddeddirectlyintootherapplications.Companieswillconsumethemastheyareorwillcustomizeandfine-tunethemwithproprietarydata.ThetechnologystackFine-tuning:Theimportanceofmodelfine-tuningwillcreatedemandforamultidisciplinarysetofskillsspanningsoftwareengineering,psychology,linguistics,arthistory,literatureandlibraryscience.ThecomplextechnologyunderpinninggenerativeAIisexpectedtoevolverapidlyateachlayer.Thishasbroadbusinessimplications.ConsiderthattheamountofcomputeneededtotrainthelargestAImodelshasgrownexponentially–nowdoublingbetweenevery3.4to10months,accordingtoFoundationmodels:Themarketwillrapidlymatureanddiversifyasmorepre-trainedmodelsemerge.Newmodeldesignswilloffermorechoicesforbalancingsize,transparency,versatilityandperformance.variousreports.8CostandcarbonemissionsData:Improvingthematurityoftheenterprisedatalifecyclewillbecomeaprerequisiteforsuccess–requiringmasteryofnewdata,newdatatypesandimmensevolumes.GenerativeAIfeatureswithinmoderndataplatformswillemerge,enhancingadoptionatscale.arethereforecentralconsiderationsinadoptingenergy-intensivegenerativeAI.“Thehottestnewprogrammingplatformisthenapkin.”PaulDaugherty,AccentureGroupChiefExecutive&ChiefTechnologyOfficerInfrastructure:CloudinfrastructurewillbeessentialfordeployinggenerativeAIwhilemanagingcostsandcarbonemissions.Datacenterswillneedretrofitting.Newchipsetarchitectures,hardwareinnovations,andefficientalgorithmswillalsoplayacriticalrole.ReferringtotheuseofOpenAItogenerateaworkingwebsitefromanapkindrawingAneweraofgenerativeAIforeveryone|9Alookaheadatthefast-pacedevolutionoftechnology,regulationandbusinessTheriskandregulatoryenvironmentAIsystemsneedtobe“raised”withadiverseandinclusivesetofinputssothattheyreflectthebroaderbusinessandsocietalnormsofresponsibility,fairnessandtransparency.WhenAIisdesignedandputintopracticewithinanethicalframework,itacceleratesthepotentialforresponsiblecollaborativeintelligence,wherehumaningenuityconvergeswithintelligenttechnology.Figure2:KeyriskandregulatoryquestionsforgenerativeAICompanieswillhavethousandsofwaystoapplygenerativeAIandfoundationmodelstomaximizeefficiencyanddrivecompetitiveadvantage.Understandably,they’llwanttogetstartedassoonaspossible.Butanenterprise-widestrategyneedstoaccountforallthevariantsofAIandassociatedtechnologiestheyintendtouse,notonlygenerativeAIandlargelanguagemodels.Intellectualproperty:HowwillthebusinessprotectitsownIP?Andhowwillitpreventtheinadvertentbreachofthird-partycopyrightinusingpre-trainedfoundationmodels?Dataprivacyandsecurity:HowwillupcominglawsliketheEUAIActbeincorporatedinthewaydataishandled,processed,protected,securedandused?Thiscreatesafoundationfortrustwithconsumers,theworkforce,andsociety,andcanboostbusinessperformanceandunlocknewsourcesofgrowth.ChatGPTraisesimportantquestionsabouttheresponsibleuseofAI.Thespeedoftechnologyevolutionandadoptionrequirescompaniestopaycloseattentiontoanylegal,ethicalandreputationalriskstheymaybeincurring.Discrimination:Isthecompanyusingorcreatingtoolsthatneedtofactorinanti-discriminationoranti-biasconsiderations?Productliability:WhathealthandsafetymechanismsneedtobeputinplacebeforeagenerativeAI-basedproductistakentomarket?It’scriticalthatgenerativeAItechnologies,includingChatGPT,areresponsibleandcompliantbydesign,andthatmodelsandapplicationsdonotcreateunacceptableriskforthebusiness.AccenturewasapioneerintheresponsibleuseoftechnologyincludingtheresponsibleuseofAIinitsCodeofBusinessEthicsfrom2017.ResponsibleAIisthepracticeofdesigning,buildinganddeployingAIinaccordancewithclearprinciplestoempowerbusinesses,respectpeople,andbenefitsociety—allowingcompaniestoengendertrustinAIandtoscaleAIwithconfidence.Trust:Whatleveloftransparencyshouldbeprovidedtoconsumersandemployees?HowcanthebusinessensuretheaccuracyofgenerativeAIoutputsandmaintainuserconfidence?Identity:Whenestablishingproof-of-personhooddependsonvoiceorfacialrecognition,howwillverificationmethodsbeenhancedandimproved?Whatwillbetheconsequencesofitsmisuse?AneweraofgenerativeAIforeveryone|10Alookaheadatthefast-pacedevolutionoftechnology,regulationandbusinessThescaleofadoptioninbusinessFigure3:GenerativeAIwilltransformworkacrossindustriesCompaniesmustreinventworktofindapathtogenerativeAIvalue.Businessleadersmustleadthechange,startingnow,injobredesign,taskredesignandreskillingpeople.Ultimately,everyroleinanenterprisehasthepotentialtobereinvented,oncetoday’sjobsaredecomposedintotasksthatcanbeautomatedorassistedandreimaginedforanewfutureofhuman+machinework.BankingInsurance54%48%36%40%43%33%34%31%12%24%26%10%12%15%18%WorktimedistributionbyindustryandpotentialAIimpactBasedontheiremploymentlevelsintheUSin202114%Software&PlatformsCapitalmarketsEnergy21%28%29%14%Lowerpotentialfor14%9%HigherpotentialforautomationHigherpotentialforaugmentationaugmentationorautomationNon-languagetasks34%33%Communications&MediaRetail13%7%21%12%22%46%GenerativeAIwilldisruptworkasweknowittoday,introducinganewdimensionofhumanandAIcollaborationinwhichmostworkerswillhavea“co-pilot,”radicallychanginghowworkisdoneandwhatworkisdone.Nearlyeveryjobwillbeimpacted–somewillbeeliminated,mostwillbetransformed,andmanynewjobswillbecreated.Organizationsthattakestepsnowtodecomposejobsintotasks,andinvestintrainingpeopletoworkdifferently,alongsidemachines,willdefinenewperformancefrontiersandhaveabigleguponlessimaginativecompetitors.40%ofworkinghoursacrossindustriescanbeimpactedbyLargeLanguageModels(LLMs)IndustryAverageHealth9%11%9%38%28%30%26%30%26%28%27%25%26%24%24%20%33%35%20%27%26%PublicServiceAerospace&DefenseAutomotive13%41%Whyisthisthecase?Languagetasksaccountfor62%oftotalworkedtimeintheUS.Oftheoverallshareoflanguagetasks,65%havehighpotentialtobeautomatedoraugmentedbyLLMs.6%13%50%HighTech8%16%15%50%50%Travel6%6%8%6%Utilities15%17%14%52%50%54%57%56%Source:AccentureResearchbasedonanalysisofOccupationalInformationNetwork(O*NET),USDept.ofLabor;USBureauofLaborStatistics.LifeSciencesIndustrialNotes:Wemanuallyidentified200tasksrelatedtolanguage(outNearly6in10organizationsplantouseChatGPTforlearningpurposesandoverhalfareplanningpilotcasesin2023.Over4in10wanttomakeaConsumerGoods&ServicesChemicals6%13%5%14%of332includedinBLS),whichwerelinkedtoindustriesusingtheirshareineachoccupationandtheoccupations’employmentlevelineachindustry.TaskswithhigherpotentialforautomationcanbetransformedbyLLMswithreducedinvolvementfromahumanworker.TaskswithhigherpotentialforaugmentationarethoseinwhichLLMswouldneedmoreinvolvementfromhumanworkers.NaturalResources5%11%64%largeinvestment.90%10%20%30%40%50%60%70%80%90%100%AneweraofgenerativeAIforeveryone|11EmbracethegenerativeAIera:SixadoptionessentialsAneweraofgenerativeAIforeveryone|12EmbracethegenerativeAIera:SixadoptionessentialsDivein,withabusiness-drivenmindsetTakeapeople-firstapproachGetyourproprietarydatareadyInvestinasustainabletechfoundationAccelerateecosysteminnovationLevel-upyourresponsibleAI1

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6AneweraofgenerativeAIforeveryone|13EmbracethegenerativeAIera:Sixadoptionessentials1Divein,withabusiness-drivenmindsetEvenwhennewinnovationshaveobviousadvantages,diffusingthemacrossanorganizationcanbechallenging,especiallyiftheinnovationisdisruptivetocurrentwaysofworking.ByexperimentingwithgenerativeAIcapabilities,companieswilldeveloptheearlysuccesses,changeagentsandopinionleadersneededtoboostacceptanceandspreadtheinnovationfurther,kick-startingthetransformationandreskillingagenda.AbankusesenhancedsearchtoequipemployeeswiththerightinformationAspartofitsthree-yearinnovationplan,alargeEuropeanbankinggroupsawanopportunitytotransformitsknowledgebase,empoweritspeoplewithaccesstotherightinformation,andadvanceitsgoalofbecomingadata-drivenbank.UsingMicrosoft’sAzureplatformandaGPT-3LLMtosearchelectronicdocuments,userscangetquickanswerstotheirquestions—savingtimewhileimprovingaccuracyandcompliance.Theproject,whichincludedemployeeupskilling,isthefirstoffourthatwillapplygenerativeAItotheareasofcontractmanagement,conversationalreportingandticketclassification.Organizationsmusttakeadualapproachtoexperimentation.One,focusedonlow-hangingfruitopportunitiesusingconsumablemodelsandapplicationstorealizequickreturns.Theother,focusedonreinventionofbusiness,customerengagementandprodictsandservicesusingmodelsthatarecustomizedwiththeorganization’sdata.Abusiness-drivenmindsetiskeytodefine,andsuccessfullydeliveron,thebusinesscase.Astheyexperimentandexplorereinventionopportunities,they’llreaptangiblevaluewhilelearningmoreaboutwhichtypesofAIaremostsuitedtodifferentusecases,sincethelevelofinvestmentandsophisticationrequiredwilldifferbasedontheusecase.They’llalsobeabletotestandimprovetheirapproachestodataprivacy,modelaccuracy,biasandfairnesswithcare,andlearnwhen“humanintheloop”safeguardsarenecessary.98%ofglobalexecutivesagreeAIfoundationmodelswillplayanimportantroleintheirorganizations’strategiesinthenext3to5years.10AneweraofgenerativeAIforeveryone|14EmbracethegenerativeAIera:Sixadoptionessentials2Figure4:GenerativeAIwilltransformworkacrosseveryjobcategoryTakeapeople-firstapproachWorktimedistributionbymajoroccupationandpotentialAIimpactBasedontheiremploymentlevelsintheUSin2021OfficeandAdministrativeSupportSalesandRelated57%49%28%45%25%27%21%33%31%30%29%22%29%27%29%23%25%23%15%16%8%6%14%14%23%24%Successwithgenerative13%AIrequiresanequalattentiononpeopleandtrainingasitdoesontechnology.Companiesshouldthereforedramaticallyrampupinvestmentintalenttoaddresstwodistinctchallenges:creatingAIandusingAI.ThismeansbothbuildingtalentintechnicalcompetencieslikeAIengineeringandenterprisearchitectureandtrainingpeopleacrosstheorganizationtoworkeffectivelywithAI-infusedprocesses.Inouranalysisacross22jobcategories,forexample,wefoundthatLLMswillimpacteverycategory,rangingfrom9%ofaworkdayatthelowendto63%atthehighend.Morethanhalfofworkinghoursin5ofthe22occupationscanbetransformedbyLLMs.ComputerandMathematicalBusinessandFinancialOperationsArts,Design,Entertainment,Sports,andMediaLife,Physical,andSocialScienceArchitectureandEngineeringLegal32%23%17%14%35%6%LowerpotentialforHigherpotentialforautomationHigherpotentialforaugmentationaugmentationorautomationNon-languagetasks26%20%26%22%25%25%58%22%44%31%40%59%31%28%30%24%9%9%9%0%OcccupationAverage38%In5outof22occupationgroups,GenerativeAIcanaffectmorethanhalfofallhoursworkedManagement17%PersonalCareandService8%32%HealthcarePractitionersandTechnicalCommunityandSocialServiceHealthcareSupport15%22%7%6%8%34%ProtectiveService6%23%50%43%EducationalInstructionandLibraryFoodPreparationandServingRelatedTransportationandMaterialMovingConstructionandExtractionInstallation,Maintenance,andRepairFarming,Fishing,andForestryProduction8%19%5%9%61%Source:AccentureResearchbasedonanalysisofOccupationalInformationNetwork(O*NET),USDept.ofLabor;USBureauofLaborStatistics.4%7%75%66%66%4%7%1%9%Notes:Wemanuallyidentified200tasksrelatedtolanguage(outof332includedinBLS),whichwerelinkedtoindustriesusingtheirshareineachoccupationandtheoccupations’employmentlevelineachjobcategory.TaskswithhigherpotentialforautomationcanbetransformedbyLLMswithreducedinvolvementfromahumanworker.TaskswithhigherpotentialforaugmentationarethoseinwhichLLMswouldneedmoreinvolvementfromhumanworkers.75%8%17%14%2%8%76%BuildingandGroundsCleaningandMaintenance9%0%7%84%ꢀꢁ1ꢀꢁꢂꢀꢁꢃꢀꢁꢄꢀꢁꢅꢀꢁꢆꢀꢁꢇꢀꢁꢈꢀꢁꢉꢀꢁ1ꢀꢀꢁAneweraofgenerativeAIforeveryone|15EmbracethegenerativeAIera:Sixadoptionessentials2Infact,independenteconomicresearchindicatesthatcompaniesaresignificantlyunderinvestinginhelpingworkerskeepupwithadvancesinAI,whichrequiremorecognitivelycomplexandjudgment-basedtasks.11Evendomainexpertswhounderstandhowtoapplydataintherealworld(adoctorinterpretinghealthdata,forexample)willneedenoughtechnicalknowledgeofhowthesemodelsworktohaveconfidenceinusingthemasa“workmate.”Figure5:Reinventingacustomerservicejob,taskbytaskToassesshowspecificjobswillbereinventedwithAI,anAccentureanalysisdecomposedonecustomerservicejobinto13componenttasks.Wefound:44Therewillalsobeentirelynewrolestorecruit,includinglinguisticsexperts,AIqualitycontrollers,AIeditors,andpromptengineers.InareaswheregenerativeAIshowsmostpromise,companiesshouldstartbydecomposingexistingjobsintounderlyingbundlesoftasks.ThenassesstheextenttowhichgenerativeAImightaffecteachtask—fullyautomated,augmented,orunaffected.taskswouldcontinuetobeperformedprimarilybyhumans,withlowpotentialforautomationoraugmentation.taskscouldbefullyautomated—suchasgathering,classifying,andsummarizinginformationonwhyacustomeriscontactingthecompany.5taskscouldbeaugmentedtohelphumansworkmoreeffectively—suchasusinganAIsummarytoprovidearapidsolutionwithahumantouch.Importantly,newjobtasksmightalsobeneededtoensurethesafe,accurateandresponsibleuseofAIincustomerservicesettings,suchasprovidingunbiasedinformationonproductsandpricing.AneweraofgenerativeAIforeveryone|16EmbracethegenerativeAIera:Sixadoptionessentials34GetyourproprietarydatareadyInvestinasustainabletechfoundationCustomizingfoundationmodelswillrequireaccesstodomain-specificorganizationaldata,Companiesneedtoconsiderwhethertheyhavetherighttechnicalinfrastructure,architecture,operatingmodelandgovernancestructuretomeetthehighcomputedemandsofLLMsandgenerativeAI,whilekeepingacloseeyeoncostandsustainableenergyconsumption.They’llneedwaystoassessthecostandbenefitofusingthesetechnologiesversusotherAIoranalyticalapproachesthatmightbebettersuitedtoparticularusecases,whilealsobeingseveraltimeslessexpensive.semantics,knowledge,andmethodologies.Inthepre-generativeAIera,companiescouldstillgetvaluefromAIwithouthavingmodernizedtheirdataarchitectureandestatebytakingause-casecentricapproachto