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with
Behindthe
AIHype
The2024Stateof
LLMsinBusiness
Processes
I
Contents
01Overview
02TopFindings
03Chapter1:What’sDrivingAIAdoption
05Chapter2:ActivatingLLMsinBusinessProcesses
10Chapter3:TheOutcomesofGenerativeAIinBusinessProcesses
15Chapter4:GovernanceofAIinBusinessProcesses
18Chapter5:TheRoleofPeopleinaWorldofAutonomousAIandAgents
23Chapter6:AIAgentsTheFutureofBusinessProcesses
28Conclusion
29MethodologyDemographics
32AboutUserEvidence
Overview
MarketsentimentaboutgenerativeAIhasentered
anewera.Earlyhypeisfading.Businessleaders
haveaclearerviewofitsstrengthsandchallenges.
Majorpress,suchastheWallStreetJournal,TheEconomist,andothershavewonderediftheAIhype
over-promisedandunder-delivered.Butveryfewhaveconsideredakeyvaluedriverforcompanies:
Businessprocessesandoperations.AslegendarybusinessthinkerTomDavenportwroteinHBR:“MostAI
applicationstodateseektoimproveagiventask.Butthisismissingthelargerpicture;smartcompaniesare
viewingtheintroductionofAIastherationaleforanewlookatend-to-endprocesses.”
Severalfirms,suchasMcDonalds,AirCanada,andIBMhaveexperiencedhighprofilefailureswithearly
generativeAIprojects.ConventionalwisdomsaysgenAIissuesaremodelchallenges:Waysthatlarge
languagemodels(LLMs)needimprovement.However,McKinseynotesthatitis“importanttorecognize
thatthemodelitselfmakesuponly15percentofthesuccess[ofanAIproject].”ThereismuchmoretoanAI
strategythantrainingdata,modelweights,andpromptengineering.
TocreateconsistentbusinessvaluewithAI,companiesmustalsoaddressprocesschallenges.Theseinclude:
HowgenAIisactivatedinbusinessprocesses.HowAIaccessesthelatestdata.HowAIrisksaregoverned,
andhowhumanoversightaccountabil
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