ThestateofAIin2022—andahalfdecadeinreview

December2022

Theresultsofthisyear’sMcKinseyGlobalSurveyonAIshowtheexpansionofthe

technology’susesincewebegantrackingitfiveyearsago,butwithanuanced

pictureunderneath.1Adoptionhasmorethandoubledsince2017,thoughthepro-

portionoforganizationsusingAIhasplateauedbetween50and60percentfor

thepastfewyears.AsetofcompaniesseeingthehighestfinancialreturnsfromAIcontinuetopullaheadofcompetitors.TheresultsshowtheseleadersmakinglargerinvestmentsinAI,engaginginincreasinglyadvancedpracticesknowntoenable

scaleandfasterAIdevelopment,andshowingsignsoffaringbetterinthetight

marketforAItalent.Ontalent,forthefirsttime,welookedcloselyatAIhiringand

upskilling.ThedatashowthatthereissignificantroomtoimprovediversityonAI

teams,and,consistentwithotherstudies,diverseteamscorrelatewithoutstandingperformance.

Fiveyearsin

review:AIadoption,impact,andspend

Thismarksthefifthconsecutiveyearwe’veconductedresearchgloballyonAI’sroleinbusiness,andwehaveseenshiftsoverthisperiod.

First,AIadoptionhasmorethandoubled.2In2017,20percentofrespondentsreportedadoptingAIinatleastonebusinessarea,whereastoday,thatfigurestandsat50percent,thoughitpeakedhigherin2019at58percent.

Meanwhile,theaveragenumberofAIcapabilitiesthatorganizationsuse,suchasnatural-languagegenerationandcomputervision,hasalsodoubled—from1.9in2018to3.8in2022.Amongthese

1Inthesurvey,wedefinedAIastheabilityofamachinetoperformcognitivefunctionsthatweassociatewithhumanminds(forexample,

natural-languageunderstandingandgeneration)andtoperformphysicaltasksusingcognitivefunctions(forexample,physicalrobotics,autonomousdriving,andmanufacturingwork).

2In2017,thedefinitionforAIadoptionwasusingAIinacorepartoftheorganization’sbusinessoratscale.In2018and2019,thedefinitionwasembeddingatleastoneAIcapabilityinbusinessprocessesorproducts.In2020,2021,and2022,thedefinitionwasthatthe

organizationhasadoptedAIinatleastonefunction.

2ThestateofAIin2022—andahalfdecadeinreview

capabilities,roboticprocessautomationandcomputervisionhaveremainedthemostcommonlydeployedeach

year,whilenatural-languagetextunderstandinghasadvancedfromthemiddleofthepackin2018tothefrontofthelistjustbehindcomputervision.

ResponsesshowanincreasingnumberofAIcapabilitiesembeddedinorganizationsoverthepastfiveyears.

AveragenumberofAIcapabilitiesthat

respondents’organizationshaveembeddedwithinatleastonefunctionorbusinessunit1

50

56

475850

20

.

ShareofrespondentswhosaytheirorganizationshaveadoptedAIinatleastonefunction,%

3.93.1

●

3.8

2.31.9

2018

2019

2020

2021

2022

201720182019202020212022

%ofrespondentswhosaygivenAIcapabilityisembeddedinproductsorbusinessprocessesinatleastonefunctionorbusinessunit2

Roboticprocessautomation39

Computervision34 Natural-languagetextunderstanding33Virtualagentsorconversationalinterfaces33

Deeplearning30

Knowledgegraphs25Recommendersystems25Digitaltwins24

Natural-languagespeechunderstanding23Physicalrobotics20

Reinforcementlearning20Facialrecognition18

Natural-languagegeneration18Transferlearning16

Generativeadversarialnetworks(GAN)11Transformers11

1Thenumberofcapabilitiesincludedinthesurveyhasgrownovertime,from9in2018to15inthe2022survey.2QuestionwasaskedonlyofrespondentswhosaidtheirorganizationshaveadoptedAIinatleastonefunction.

ThestateofAIin2022—andahalfdecadeinreview3

Thetopusecases,however,haveremainedrelativelystable:optimizationofserviceoperationshastakenthetopspoteachofthepastfouryears.

Second,thelevelofinvestmentinAIhasincreasedalongsideitsrisingadoption.Forexample,fiveyearsago,40percentofrespondentsatorganizationsusingAIreportedmorethan5percentoftheirdigital

budgetswenttoAI,whereasnowmorethanhalfofrespondentsreportthatlevelofinvestment.Going

forward,63percentofrespondentssaytheyexpecttheirorganizations’investmenttoincreaseoverthenextthreeyears.

ThemostpopularAIusecasesspanarangeoffunctionalactivities.

Topusecases

Usecasesbyfunction

MostcommonlyadoptedAIusecases,byfunction,%ofrespondents1

Serviceoperations2Productand/orservicedevelopmentMarketingandsalesRisk

Serviceoperationsoptimization24CreationofnewAI-basedproducts20

Customerserviceanalytics19

Customersegmentation19NewAI-basedenhancementsofproducts19

Customeracquisitionandleadgeneration17Contact-centerautomation16Productfeatureoptimization16

Riskmodelingandanalytics15Predictiveserviceandintervention14

1Outof39usecases.QuestionwasaskedonlyofrespondentswhosaidtheirorganizationshaveadoptedAIinatleastonefunction.2Eg,fieldservices,customercare,backoffice.

4ThestateofAIin2022—andahalf-decadeinreview

ThemostpopularAIusecasesspanarangeoffunctionalactivities.

Topusecases

Usecasesbyfunction

MostcommonlyadoptedAIusecaseswithineachbusinessfunction,%ofrespondents1

Serviceoperations2

Serviceoperationsoptimization

24

Contact-centerautomation

16

Marketingandsales

Customerserviceanalytics

19

Customersegmentation

19

Risk

Riskmodelingandanalytics

15

Fraudanddebtanalytics

11

Strategyandcorporate?nance

Capitalallocation7Treasurymanagement4M&Asupport4

Productand/orservicedevelopment

CreationofnewAI-basedproducts

NewAI-basedenhancementsofproducts

2019

Supplychainmanagement

Salesanddemandforecasting

Logisticsnetworkoptimization

109

Humanresources

Optimizationoftalentmanagement

Optimizationofworkforcedeployment

10

5

Manufacturing

13

Predictivemaintenance

11

Yield,energy,and/or

throughputoptimization

11

Simulations(eg,usingdigitaltwins,3Dmodeling)

1QuestionwasaskedonlyofrespondentswhosaidtheirorganizationshaveadoptedAIinatleastonefunction.2Eg,fieldservices,customercare,backoffice.

Third,thespecificareasinwhichcompaniesseevaluefromAIhaveevolved.In2018,manufacturingandriskwerethetwofunctionsinwhichthelargestsharesofrespondentsreportedseeingvaluefromAI

use.Today,thebiggestreportedrevenueeffectsarefoundinmarketingandsales,productandservicedevelopment,andstrategyandcorporatefinance,andrespondentsreportthehighestcostbenefits

fromAIinsupplychainmanagement.Thebottom-linevaluerealizedfromAIremainsstrongandlargelyconsistent.Aboutaquarterofrespondentsreportthisyearthatatleast5percentoftheirorganizations’EBITwasattributabletoAIin2021,inlinewithfindingsfromtheprevioustwoyears,whenwe’vealso

trackedthismetric.

Lastly,onethingthathasremainedconcerninglyconsistentisthelevelofriskmitigationorganizations

engageintobolsterdigitaltrust.WhileAIusehasincreased,therehavebeennosubstantialincreasesinreportedmitigationofanyAI-relatedrisksfrom2019—whenwefirstbegancapturingthisdata—tonow.

ThestateofAIin2022—andahalfdecadeinreview5

AI-relatedcostdecreasesaremostoftenreportedinsupplychain

managementandrevenueincreasesinproductdevelopmentandmarketingandsales.

CostdecreaseandrevenueincreasefromAIadoptionin2021,byfunction,%ofrespondents1

Decreaseby10–19%

ServiceoperationsManufacturing

Humanresources

MarketingandsalesRisk

Supplychainmanagement52Productand/orservicedevelopment

Strategyandcorporate?nance

Averageacrossallactivites

1QuestionwasaskedonlyofrespondentswhosaidtheirorganizationshaveadoptedAIinagivenfunction.Respondentswhosaid“nochange,”“costincrease,”“notapplicable,”or“don’tknow”arenotshown.

4529106

423273

29253

282143

433085

4174

Increaseby6–10%

37

Increaseby≤5%

57

Decreaseby<10%

Decreaseby≥20%

Increaseby>10%

3184

2363

2046

14

13

10

10

9

10

8

8

30

20

48

70

70

36

43

58

28

59

63

65

33

33

32

24

27

10

18

16

19

13

61

31

41

41

14

17

1

11

Therehasbeennosubstantialincreaseinorganizations’reportedmitigationofAI-relatedrisks.

AIrisksthatorganizationsconsiderrelevantandareworkingtomitigate,%ofrespondents1

20192022

51

48

3536

30

28

22

1718

13

11

74o

Regulatorycompliance

displacement

1QuestionwasaskedonlyofrespondentswhosaidtheirorganizationshadadoptedAIinatleastonefunction;n=1,151.Respondentswhosaid“don'tknow/notapplicable”arenotshown.

2Thatis,theabilitytoexplainhowAImodelscometotheirdecisions.

Organi-zational

reputation

Personal/

individual

privacy

Equity

and

fairness

Workforce/

labor

Nationalsecurity

Physicalsafety

Explain-ability2

Cyber-security

Politicalstability

22

19

19

15

17

4

2

6ThestateofAIin2022—andahalfdecadeinreview

McKinseycommentary

MichaelChui

Partner,McKinseyGlobalInstitute

Overthepasthalfdecade,duringwhichwe’vebeenconductingourglobalsurvey,wehaveseenthe“AIwinter”turnintoan“AIspring.”However,afteraperiodofinitialexuberance,weappeartohavereachedaplateau,acoursewe’veobservedwithothertechnologiesintheirearlyyearsof

adoption.Wemightbeseeingtherealitysinkinginatsomeorganizationsoftheleveloforganiza-tionalchangeittakestosuccessfullyembedthistechnology.

Inourwork,we’veencounteredcompaniesthatgetdiscouragedbecausetheywentintoAI

thinkingitwouldbeaquickexercise,whilethosetakingalongerviewhavemadesteadyprog-

ressbytransformingthemselvesintolearningorganizationsthatbuildtheirAImusclesovertime.ThesecompaniesgraduallyincorporatemoreAIcapabilitiesandstandupincreasinglymore

applicationsprogressivelyfasterandmoreeasilythankstolessonsfrompastsuccessesaswell

asfailures.Theynotonlyinvestmore,buttheyalsoinvestmorewisely,withthegoalofcreatingaveritableAIfactorythatenablesthemtoincorporatemoreAIinmoreareasofthebusiness,firstin

adjacentoneswheresomeexistingcapabilitiescanberepurposedandthenintoentirelynewones.

Thereis,atahighlevel,anemergingplaybookforgettingmaximumvaluefromAI.Eachyearthat

weconductourresearch,weseeagroupofleadersengaginginthetypesofpracticesthathelp

executeAIsuccessfully.It’spayingoffintheformofactualbottom-lineimpactatsignificantlevels.WealsoseeiteverydayasweguideothersontheirAIjourneys.It’snoteasywork,butashas

beenthecasewithprevioustechnologies,thegainswillgotothosewhostaythecourse.

Thosetakingalongerview

havemadesteadyprogressby

transformingthemselvesinto

learningorganizationsthatbuildtheirAImusclesovertime.

ThestateofAIin2022—andahalfdecadeinreview7

AIuseandsustainabilityefforts

ThesurveyfindingssuggestthatmanyorganizationsthathaveadoptedAIareintegratingAIcapabilitiesintotheirsustainabilityeffortsandarealsoactivelyseekingwaystoreducetheenvironmentalimpactoftheirAI

use(exhibit).Ofrespondentsfromorganizationsthat

haveadoptedAI,43percentsaytheirorganizationsareusingAItoassistinsustainabilityefforts,and40per-

centsaytheirorganizationsareworkingtoreducetheenvironmentalimpactoftheirAIusebyminimizingtheenergyusedtotrainandrunAImodels.AscompaniesthathaveinvestedmoreinAIandhavemoremature

AIeffortsthanothers,highperformersare1.4times

morelikelythanotherstoreportAI-enabledsustain-

abilityeffortsaswellastosaytheirorganizationsare

workingtodecreaseAI-relatedemissions.Bothefforts

aremorecommonlyseenatorganizationsbasedin

GreaterChina,Asia–Pacific,anddevelopingmarkets,whilerespondentsinNorthAmericaareleastlikelytoreportthem.

WhenaskedaboutthetypesofsustainabilityeffortsusingAI,respondentsmostoftenmentioninitiativestoimproveenvironmentalimpact,suchasoptimiza-

tionofenergyefficiencyorwastereduction.AIuse

isleastcommonineffortstoimproveorganizations’

socialimpact(forexample,sourcingofethicallymadeproducts),thoughrespondentsworkingforNorth

Americanorganizationsaremorelikelythantheirpeerstoreportthatuse.

Exhibit

OrganizationsareusingAIwithinsustainabilityefortsandareworkingtoreducetheenvironmentalimpactoftheirAIuse.

OrganizationsusingAIintheirsustainabilityeforts,%ofrespondents1

GreaterChina261

Asia–Pacic54Developingmarkets344

Europe39NorthAmerica30

Improvingtheorganization’senvironmentalimpact(eg,improvingenergyefficiency,optimizingtransportation)

Evaluatingsustainabilityefforts(eg,benchmarking)

Improvingtheorganization’sgovernance

(eg,regulatorycompliance,riskmanagement)

Improvingtheorganization’ssocial

impact(eg,sourcingethicalproducts)

OrganizationstakingstepstoreducecarbonemissionsfromtheirAIuse,%ofrespondents1

Developingmarkets353Asia–Pacic47

GreaterChina246Europe36

62

NorthAmerica31

Typesofsustainabilityefortsinwhichrespondents’organizationsareusingAI?

51

45

34

1OnlyaskedofrespondentswhoseorganizationshaveadoptedAIinatleastonefunction.FororganizationsbasedinGreaterChina,n=102;forAsia–Pacific,n=74;fordevelopingmarkets,n=118;forEurope,n=260;andforNorthAmerica,n=190.

2IncludesrespondentsinHongKongSARandTaiwanChina.

3?

IncludesrespondentsinIndia,LatinAmerica,MiddleEast,NorthAfrica,andsub-SaharanAfrica.

OnlyaskedofrespondentswhoseorganizationshaveadoptedAIinatleastonebusinessunitorfunctionwhosaidthattheirorganizationsareusingAIin

sustainabilityefforts;n=302.

8ThestateofAIin2022—andahalfdecadeinreview

Mindthegap:AI

leaderspullingahead

Overthepastfiveyears,wehavetrackedtheleadersinAI—werefertothemasAIhighperformers—andexaminedwhattheydodifferently.Weseemoreindicationsthattheseleadersareexpandingtheir

competitiveadvantagethanwefindevidencethatothersarecatchingup.

First,wehaven’tseenanexpansioninthesizeoftheleadergroup.Forthepastthreeyears,wehavedefinedAIhighperformersasthoseorganizationsthatrespondentssayareseeingthebiggest

bottom-lineimpactfromAIadoption—thatis,20percentormoreofEBITfromAIuse.Theproportionofrespondentsfallingintothatgrouphasremainedsteadyatabout8percent.ThefindingsindicatethatthisgroupisachievingitssuperiorresultsmainlyfromAIboostingtop-linegains,asthey’remorelikelytoreportthatAIisdrivingrevenuesratherthanreducingcosts,thoughtheydoreportAIdecreasing

costsaswell.

Next,highperformersaremorelikelythanotherstofollowcorepracticesthatunlockvalue,such

aslinkingtheirAIstrategytobusinessoutcomes.3Alsoimportant,theyareengagingmoreoften

in“frontier”practicesthatenableAIdevelopmentanddeploymentatscale,orwhatsomecallthe

“industrializationofAI.”Forexample,leadersaremorelikelytohaveadataarchitecturethatismodularenoughtoaccommodatenewAIapplicationsrapidly.Theyalsooftenautomatemostdata-related

processes,whichcanbothimproveefficiencyinAIdevelopmentandexpandthenumberofapplicationstheycandevelopbyprovidingmorehigh-qualitydatatofeedintoAIalgorithms.AndAIhighperformersare1.6timesmorelikelythanotherorganizationstoengagenontechnicalemployeesincreatingAI

applicationsbyusingemerginglow-codeorno-codeprograms,whichallowcompaniestospeedup

thecreationofAIapplications.Inthepastyear,highperformershavebecomeevenmorelikelythan

otherorganizationstofollowcertainadvancedscalingpractices,suchasusingstandardizedtoolsets

tocreateproduction-readydatapipelinesandusinganend-to-endplatformforAI-relateddatascience,dataengineering,andapplicationdevelopmentthatthey’vedevelopedin-house.

HighperformersmightalsohaveaheadstartonmanagingpotentialAI-relatedrisks,suchaspersonalprivacyandequityandfairness,thatotherorganizationshavenotaddressedyet.Whileoverall,we

haveseenlittlechangeinorganizationsreportingrecognitionandmitigationofAI-relatedriskssincewebeganaskingaboutthemfouryearsago,respondentsfromAIhighperformersaremorelikely

thanotherstoreportthattheyengageinpracticesthatareknowntohelpmitigaterisk.TheseincludeensuringAIanddatagovernance,standardizingprocessesandprotocols,automatingprocessessuchasdataqualitycontroltoremoveerrorsintroducedthroughmanualwork,andtestingthevalidityof

modelsandmonitoringthemovertimeforpotentialissues.

3AllquestionsaboutAI-relatedstrengthsandpracticeswereaskedonlyofthe744respondentswhosaidtheirorganizationshadadoptedAIinatleastonefunction,n=744.

ThestateofAIin2022—andahalfdecadeinreview9

OrganizationsseeingthehighestreturnsfromAIaremorelikelytofollowstrategy,data,models,tools,technology,andtalentbestpractices.

Shareofrespondentsreportingtheirorganizationsengageineachpractice,1%ofrespondents

Strategy

Data

Models,tools,andtech

Talentandwaysofworking

HavearoadmapthatclearlyprioritizesAIinitiativeslinkedtobusinessvalueacrossorganization

HaveanAIstrategythatisalignedwiththebroadercorporatestrategyandgoals

Seniormanagementthatisfullyalignedandcommittedtoorganization’sAIstrategy

HaveaclearlydefinedAIvisionandstrategy

AppointedacredibleleaderofAIinitiativeswhoisempoweredtomovethemforwardincollaborationwithpeersacrossbusinessunitsandfunctions

Systematicallytrackacomprehensivesetofwell-de?nedKPIstomeasuretheincrementalimpactofAIinitiatives

HaveaclearframeworkforAIgovernancethatcoverseverystepofthemodeldevelopmentprocess

AllotherrespondentsAIhighperformers2

0

20

60

80

40

100

Strategy

Data

Models,tools,andtech

Talentandwaysofworking

AllotherrespondentsAIhighperformers2

HaveabilitytointegratedataintoAImodelsasquicklyasneeded(eg,innearrealtime)

Integratestructuredinternaldata(eg,adatalakethatcontainscustomerdataacrossbusinessunits)touseinAIinitiatives

Integrateexternaldata(eg,opensource,purchased)touseinAIinitiatives

Integrateunstructuredinternaldata(eg,textualcall-centerlogs)touseinAIinitiatives

GeneratesyntheticdatatotrainAImodelswhenthereareinsufficientnaturaldatasets

HaveamodularenoughdataarchitecturetorapidlyaccommodatetheneedsofnewAIusecases

Automatemostdata-relatedprocesses(eg,datalabeling,dataqualitycontrol)

HavescalableinternalprocessesforlabelingAItrainingdata

12

PracticesshownherearerepresentativeofthosewiththehighestdeltasbetweenAIhighperformersandotherrespondents.Notallpracticesareshown.Respondentswhosaidthatatleast20percentoftheirorganizations’EBITin2021wasattributabletotheiruseofAI.

10ThestateofAIin2022—andahalfdecadeinreview

OrganizationsseeingthehighestreturnsfromAIaremorelikelytofollowstrategy,data,models,tools,technology,andtalentbestpractices.

Shareofrespondentsreportingtheirorganizationsengageineachpractice,1%ofrespondents

Strategy

Data

Models,tools,andtech

Talentandwaysofworking

DevelopAImodelsthatcanprovideaccurate,usableresultsleveragingsmalleramountsofdata(ie,“smalldata”)

RegularlyrefreshAImodelsbasedonclearlydefinedcriteriaforwhenandwhytodoso

Developedin-housetheend-to-endplatformusedforAI-relateddatascience,dataengineering,andapplicationdevelopment

Useastandardizedtoolsettocreateproduction-readydatapipelines

Developmodularcomponents(eg,datamodellayers,datapipelines)sotheycanbereusedinAIapplications

RefreshAI/machinelearningtechstackatleastannuallytotakeadvantageofthelatesttechnologicaladvances

AutomatethefulllifecycleforAImodeldevelopment(eg,fromdataingestionandqualitycontrolthroughmodelmonitoring)

Usetheorganization’sownhigh-performancecomputingclusterforAIworkloads

AllotherrespondentsAIhighperformers2

0

20

60

80

40

100

Strategy

Data

Models,tools,andtech

Talentandwaysofworking

AllotherrespondentsAIhighperformers2

TakeafulllifecycleapproachtodevelopinganddeployingAImodels

IntegrateAItechnologiesintobusinessprocesses(eg,day-to-dayoperations,employeeworkflows)

TeamsfordatascienceandAIdesignanddevelopmentcollaboratetobuildandimproveAIapplications

Havewell-definedcapability-buildingprogramstodeveloptechnologypersonnels’AIskills

TrainnontechnicalpersonneltouseAItoimprovedecisionmaking

AIdevelopmentteamsfollowstandardprotocols(eg,toolframeworks,developmentprocesses)forbuildinganddeliveringAItools

0

20

60

80

40

100

12

PracticesshownherearerepresentativeofthosewiththehighestdeltasbetweenAIhighperformersandotherrespondents.Notallpracticesareshown.Respondentswhosaidthatatleast20percentoftheirorganizations’EBITin2021wasattributabletotheiruseofAI.

ThestateofAIin2022—andahalfdecadeinreview11

Investmentisyetanotherareathatcouldcontributetothewideningofthegap:AIhighperformersare

poisedtocontinueoutspendingotherorganizationsonAIefforts.Eventhoughrespondentsatthose

leadingorganizationsarejustaslikelyasotherstosaythey’llincreaseinvestmentsinthefuture,they’re

spendingmorethanothersnow,meaningthey’llbeincreasingfromabasethatisahigherpercentageof

revenues.RespondentsatAIhighperformersarenearlyeighttimesmorelikelythantheirpeerstosaytheirorganizationsspendatleast20percentoftheirdigital-technologybudgetsonAI-relatedtechnologies.

Andthesedigitalbudgetsmakeupamuchlargerproportionoftheirenterprisespend:respondentsatAIhighperformersareoverfivetimesmorelikelythanotherrespondentstoreportthattheirorganizationsspendmorethan20percentoftheirenterprise-widerevenueondigitaltechnologies.

Finally,allofthismaybegivingAIhighperformersalegupinattractingAItalent.ThereareindicationsthattheseorganizationshavelessdifficultyhiringforrolessuchasAIdatascientistanddataengineer.RespondentsfromorganizationsthatarenotAIhighperformerssayfillingthoseroleshasbeen“verydifficult”muchmoreoftenthanrespondentsfromAIhighperformersdo.

Thebottomline:highperformersarealreadywellpositionedforsustainedAIsuccess,improvedefficiency

innewAIdevelopment,andaresultinglymoreattractiveenvironmentfortalent.Thegoodnewsfororganizationsoutsidetheleadergroupisthatthere’saclearblueprintofbestpracticesforsuccess.

RespondentsatAIhighperformersarenearly

eighttimesmorelikelythantheirpeerstosaytheirorganizationsspendatleast20percentoftheir

digital-technologybudgetsonAI-relatedtechnologies.

12ThestateofAIin2022—andahalf-decadeinreview

McKinseycommentary

BryceHall

Associatepartner

Overtheyearsofourresearch,we’vecontinuedtorefineourunderstandingofthespecific

practicesthatleadingcompaniesaredoingwellandthecapabilitiestheyhaveinplacetocapturevaluefromAI.Recently,anewsetof“frontier”practiceshasemergedasorganizationsshiftfromexperimentingwithAItoindustrializingit.Theseincludemachinelearningoperations(MLOps)

practicessuchasassetization,orturningelementslikecodeintoreusableassetsthatcanbeappliedoverandoverindifferentbusinessapplications.

Butovertheyears,we’vealsoconsistentlyseenasetoffoundationalpracticesthatthese

organizationsaregettingright.Throughourwork,we’velearnednottodescribetheseas“basic”practices,becausetheyaresomeofthemostdifficulttoimplement.Manyoftheseinvolvethe

peopleelementsthatneedtobeinplaceforcompaniestoadoptAIsuccessfully,suchashavingaclearunderstandingofwhatspecifictechtalentrolesareneededandsuccessfullyintegratingAIintobusinessprocessesanddecisionmaking.Asproveninmanycases,AIenginesandpeopletogethercancreatemuchmorevaluethaneithercanindividually.

AstheAIfrontieradvances,wecontinuetobeinspiredbysometrulyinnovativeapplicationsof

AI,suchastheuseofAItoidentifynewdrugs,createhyperpersonalizedrecommendationsfor

consumers,andpowerAIsimulationsindigitaltwinstooptimizeperformanceacrossavariety

ofsettings.AsindividualAIcapabilities,suchasnatural-languageprocessingandgeneration,

continuetoimproveanddemocratize,we’reexcitedtoseeawaveofnewapplicationsemergeandmorecompaniescapturevaluefromAIatscale.

ThestateofAIin2022—andahalfdecadeinreview13

AItalenttales:Newhotroles,continueddiversitywoes

OurfirstdetailedlookattheAItalentpicturesignalsthematurationofAI,surfacesthemostcommonstrategiesorganizationsemployfortalentsourcingandupskilling,andshinesalightonAI’sdiversityproblem—whileshowingyetagainalinkbetweendiversityandsuccess.

Hiringisachallenge,butlesssoforhighperformers

Softwareengineersemerge