INTRODUCTION 1

The Essential CIO Guide to AI

Index

Chapter 1: Why is AI trending now?

CIO: “Why is my CEO asking me this?”

TheevolutionoftheCIOrole

SurfingtheWaves

Chapter2:AframeworkforunderstandingAI

FormulatingaFrameworkforAI

AI≠Machines>Humans

AI≠BestAlgorithm

AI=TD+ML+HITL

ImportanceofHuman-in-the-loop

Chapter 3: Applying AI to your business

EngagingtheBusiness

FocusonOutcomesnotTechnologies

Explaining AI

SystemsofRecordwithUnstructuredData

EvaluatingyourVendors

Conclusion

Introduction

4

5

7

8

14

15

16

17

20

23

25

27

29

29

30

32

36

3

ThetopicofAIhasreachedsuchafeverpitchin

the mediawiththecoverageofdriverlesscars,

conversationalbots and even movies made by AI that

it’sonlyamatteroftimebeforeeveryCEOstartsasking

their CIO “What’s our AI strategy.” For many CIOs this

willbea“deerintheheadlights”momentsincethe

topicofAIissomulti-facetedit’shardtoknowwhereto

start.Weputtogetherthise-bookasaprimerforCIOs

wantingtogettogripswiththetopicofAI.

Introduction

INTRODUCTION 3

Inthise-book,westartbygivingsomeinsightand

contextintowhyyourCEOisaskingthisquestion,why

now,andwhyyou.Then,wewillgiveyouafoundational

frameworktothinkaboutAIsoyoucangiveyourCEO

athoughtfulresponse.Finally,wewilldiscusshowyou

asCIO,canengagethebusinessonthetopicofAIand

importantconsiderationswhenevaluatingAIvendors.

INTRODUCTION 4 4

Why is AI trending now?

C H A P T E R 1

WHY IS AI TRENDING NOW? 5

So, why is the CEO asking you this now? CEOs are

humanstooandtheyreacttotheirenvironment.Their

environmentisoftendominatedbyotherCEOs,their

board,andtheoutsideworld.AIasatopichasrisentothe

boardroomandthepopularpresswithevenVanityFair

recentlypublishinganarticletitled“Suddenly Everyone is

Obsessed with AI.”SoifyourCEOhasn’tbroachedtheAI

topicyet,theysoonwill.

CIO: Why is my CEO asking me this?

AIisadisruptivetechnology.AccordingtoClayton

Christensen,authorofTheInnovator’sDilemma,a

disruptivetechnology“enablesnewmarketstoemerge”

anddisruptsanexistingmarket.

YourCEO’ssuccessdependsonhowwelltheyanticipate

thesetechnologydisruptions,andusethemtoyour

company’sadvantage.Attheendoftheday,your

companywilleitherbepartoftheneweconomythat

arisesfromthedisruption,orpartoftheoldorderthat

fadesintooblivion.AndifAIisthenextbigtechnological

disruptiontohitcompanies,yourCEOwantstobeonthe

rightsideofthisdisruption.

WHY IS AI TRENDING NOW? 6

NowthatwehaveabriefideaastowhyAIis

suddenlybecomingsuchabigdeal,andwhyyour

CEOcaresaboutit,let’slookattheroleoftheCIO

andhowyou’reexpectedtodealwiththisnewtrend.

AsCIOyoumaybethinkingwhyisthisquestion

directedatme?Whyisn’theaskingtheCFO,CTO,

CMO,orCOO?Toanswerthatquestionweneedto

putAIinthehistoricalcontextoftheroleoftheCIO.

A disruptive technology “enables new markets to emerge” and disrupts an existing market.CLAYTONCHRISTENSENAUTHOR,THEINNOVATOR’SDILEMMA

TheEvolutionoftheCIOrole

WilliamSynnott,formerSeniorVicePresidentof

theBankofBoston,andWilliamGruber,former

professorattheMITSloanSchoolofManagement,

firstformallydefinedtheroleoftheCIOin1981.

TheydefinedtheCIOasthejobtitlecommonly

giventothemostseniorexecutiveinanenterprise

responsiblefortheinformationtechnologyandcomputer

systems that support enterprise goals.

Upuntilabout2005theCIOmandatewasclear.

Deploythe6orsokeytechnologiestosupportthe

business:AccountingforFinance,Payroll&Benefitsfor

HR,CRMforsales,CallcentersforSupport,Emailand

Securityforallemployees.TheITfunctioncollectedthe

businessrequirementsandthenselectedanddelivered

theapplication.Itwasverylinear,typicallytook12+

monthsandwouldonlychangeevery5years.

ThisnewCIOrolewasnotconsideredaglamorousor

evenmission-criticalroleinitially.Itwaspredominantly

measuredasacostcenterandatonepointtherolewas

sounappreciatedthatthejokestartedcirculatingthat

CIOstoodfor“CareerisOver.”

WHY IS AI TRENDING NOW? 7

SurfingtheWaves

Butlikemanyexecutiveroles,CIOshavehadtoevolve

inresponsetotheirchangingenvironment.ForCIOs

thebiggestchangeintheirenvironmentwasthe

natureoftechnologyavailabletotheenterprise.These

changeswouldappearaswavestotheITfunction,

startingfromfarawaybutgaininginpowerasthey

approached.EitherCIOshadtolearntoridethewave,

orbeoverpoweredbythewave.Upuntilabout2005

therewasjustonewave,whichwasthetransition

frommainframestoclient-servertechnology, but in the

last15yearsthefrequencyandpowerofthewaveshas

increased.AgreatCIOislikeagreatsurfer.Theycansee

thewavefromfarawayandtheycantimehowandwhen

to ride it.

After20+yearsofcalm,glassyseathefirstbigwavehit.

BiggerandfasterthananythingaCIOhadexperienced

previously.Drownorride,thosewereyourchoices.

WHY IS AI TRENDING NOW? 8

WHY IS AI TRENDING NOW? 9

The Three Waves

On premise to Cloud & Mobile & Social

Small Data toBig Data

Unintelligent applications to AI

WHY IS AI TRENDING NOW? 9

The first wave: On premise to Cloud & Mobile & Social Salesforcewasthefirstcloudvendortoreach$1Bin

revenuein2009andpavedthewayforthemainstream

adoptionofcloudapplicationsintheenterprise.

ServiceNowandWorkdayhavesincejoinedSalesforce

inthe“$1billionrevenue”clubforpure-playcloud

applicationscompanies.

Thecloudwavewasalsoamplifiedbythesocialand

mobiletechnologies,whichincreasedthevolumeof

datasharedacrosscompanyboundaries.Thelaunchof

theiPhone,andtheevenmoreprolificAndroidmobile

ecosystemsbeganthemobilerevolution.Atthesame

time,socialnetworkingplatformslikeFacebook,Twitter,

andLinkedInweregainingmassadoptionglobally,

connectingnotjustconsumers,butprofessionals.This

fundamentallychangedthewayenterprisesfunction,and

CIOshadtoadaptaccordingly.

This cloudwaveprofoundlychangedtheroleoftheCIO

intwomajorways.First,ITswitchedfrombeingacapital

costtoavariableoperatingcostwherethepremium

was on speed and agility. This stressed the IT org that

hadbeenbuiltforstabilityandgovernance.Ratherthan

planforperiodicserverhardwareandlegacysoftware

upgrades,CIOsshiftedtoSaaStoolstosupporttheir

businessfunctions,andtopubliccloudvendorstorent

serversandcomputingresourcesbythehour.

Second,theenduserprovisioningofcloudandBYOD

mobiledynamicchangedthebalanceofpower.Previously,

IT would tell employees what they would use. Now,

employeeschoosewhatappstheywanttouseand

bypassIT.Ratherthandealwithjust6-8majorbusiness

applicationsfortheentirecompany,theynowhadto

supportatleasta10Xincreaseinapplications.Asan

exampleoftheexplosivegrowthjusttheMarketing

functionhad4,000cloudapplicationsavailabletothem.

WHY IS AI TRENDING NOW? 10

TheCIOhadtodevelopnewpoliciesandframeworks

toco-optratherthanignorethistrend.JustastheCIOs

werecatchingtheirbreath,asecondwavehitthem.

The second wave: Small Data to Big Data

TheconstantduringthefirstwavewasthatIT’sprimary

responsibilitywasstillenablingbusinessprocesses.This

forcedITtofocusalmostexclusivelyontheapplications

runningunderneaththosebusinessprocesses.Asthe

conceptofthedataitselfbeingvaluableandneeding

managinghitthemainstreamin2011withtheMcKinsey

GlobalInstitutepublicationof“Bigdata:Thenext

frontierforinnovation,competition,andproductivity,”

theroleoftheCIOchangedonceagain.

CIO’shadtobecomefamiliarwiththe5Vs(Volume,

Velocity,Variety,Variability,andVeracity)ofbigdata.

Theyhadtounderstandnewstorageandcompute

approachessuchasMapReduce,Hadoop,Spark,and

Cassandra.Theyhadtobuildanalyticscapabilitiesto

presentthedatatobusinessowners.Thescopeoftheir

worlddramaticallyexpanded.

Thiswaveisstillinmotion.Ithasn’tcrashedonthe

shoreyet.Butonthehorizonthebeginningsofathird

wave are emerging.

The third wave: Unintelligent applications to AI

Duringtheexplosionofthenumberofcloudapplications

beingusedinsideanorganization,theseapplicationswere

stillunintelligent.Namely,theapplicationitselfdidn’tdo

anythingunlessahumantookanaction–respondedto

asupportticket,updatedasalesopportunity–ormaybe

preprogrammedadefinedruletofollow–suchasnurture

aleadbasedontheleadactivities.Theseapplications

werepredominantlybackwardlooking.Theytoldyouwhat

WHY IS AI TRENDING NOW? 11

hadalreadyhappened.Butwiththecollectionofsuch

bigdatasetsfromthepreviouswave,therewasnow

abusinessimperativetogleanmorevaluefromthem.

Thismeantonething.Applicationsneededtobecome

intelligentandpredictwhathadnotyethappened.

ForAItobecomepossibleweneededadvancesin4

areas:dataavailability,processingpower,machine

learningtalent,machinelearningcloudofferings.All4

advanceshaveoccurredinthelast24monthssoAIfor

the enterprise is now possible.

AIrequiresstructureddata.Whilestructureddata

referstotextfilesthatareneatlylabeledwithrowsand

columnsthatcaneasilybeorderedandprocessedby

dataminingtools,80%ofbusinessrelevantinformation

isstillunstructured.Thisincludestexts,e-mails,digital

images,audio,video,andsocialmediaposts.Tomake

thisunstructureddatausefultothetaskathand,you

needhumanstoapplytheirintelligenceincategorizing

andlabellingthedatasoitbecomesstructuredandcanbe

ingestedbyamachinelearningmodel.

AIrequiresmassiveprocessingpower.Thisprocessing

powerisnowavailable,throughadvancesinmulti-corechip

designsandtheapplicationofGPUs.Ascientistworkingon

anAIprogramatGooglefiguredoutthatifyouuseGPUs

insteadofCPUsyoucangetcomputingtasksdonealot

quickerwithalotlessresources.Ittookjust64GPUstodo

thejoboriginallydesignatedfor2000CPUs.

AIrequiresmachinelearningtalentandmachinelearning

platforms.AccordingtoLinkedIn,therearenowatleast

180,000datascientistsinNorthAmerica and the big 5

technologyplayers–Amazon, Google, IBM, Microsoft, and

Salesforce–areactivelytargetingthemwithcloudmachine

WHY IS AI TRENDING NOW? 12

learningofferings.Google’sCEOhasstatedtheyare

now an AI-first(ratherthanmobile-first)companyand

Microsoft’sCEOhasarticulated10rulesforAI.

Thefirstexamplesofintelligenceapplicationsemergedin

marketingandsales,withcompaniessuchasQuantcast

doingpredictivetargetingandEverstring and Infer doing

predictiveleadscoring.Butnowwe’reseeingAIstartto

emergeinfieldsasdiverseasautomotive, healthcare, and

retail.

Sothewavesareappearingonthehorizon.It’sonlya

matteroftimebeforetheyhittheenterprise.Nowthat

youknowwhythewavesareappearing,whatcanyoudo

toprepare?What’stheequivalentoflearningtosurfwhen

itcomestoAI?

Next,wewillgiveyouafoundationalframeworktothink

aboutAIandhowitrelatestoyourbusiness,soyoucan

giveyourCEOathoughtfulresponse.

WHY IS AI TRENDING NOW? 13

A FRAMEWORK FOR UNDERSTANDING AI 14 14

Aframeworkforunderstanding AI

C H A P T E R 2

A FRAMEWORK FOR UNDERSTANDING AI 15

InChapter1,wegavesomeinsightandcontextintowhy

yourCEOisaskingthisquestion,whynow,andwhyyou.

InChapter2,wewillgiveyouafoundationalframework

tothinkaboutAIsoyoucangiveyourCEOathoughtful

response.

InthelastchapterweintroducedthemetaphoroftheCIO

beingabletoridethewavesoftechnologydisruption.

Toavoidbeingknockedoffyourboardandsweptoutto

sea,firstyoumustdevelopasolidconceptualframework

forunderstandingAI.Onceyouhavethat,youcanengage

withthebusiness,andevaluateyouroptionsforworking

withvendorsprovidingAIsolutions.

Formulating a Framework for AI

Let’sstartoffwithsomedefinitionsofwhatAIisnot.

ThisisnecessarybecausethemediacoverageofAIisnot

thoughtfulbutoftenhyperbolic.

AI ≠ Machines > Humans

For the last 30 years the media has loved to portray AI

asthereplacementofhumansbymachines,whether

it’sSchwarzeneggerintheTerminatororAliciaVikander

in ExMachina.ThisisthewrongmentalmodelforAIin

theenterprise.Therightframingishowcanmachines

augmenthumans,notreplacethem.Eventherecentthe

mediacoverageofGoogle’sDeepMind/AlphaGovictory

overLeeSedolwassimplisticallyportrayedasmachine

defeatshuman.Themoreaccuratedescriptionwouldbe

machineplusmanyhumansdefeatssinglehuman.

Machineshaveadvantagesthathumansdonot:speed,

cost,andconsistency.Humanshaveadvantagesthat

machinesdonot:taskcomplexityandbreadthoftask

capability.Thechallengeistofindtherightwaytoblend

humansandmachines,notreplacehumanswithmachines.

Asareminderthatmachinesaren’treadytotakeoverfrom

humansjustyet,anumberofrobotsinDARPA’srobotics

challenge last year struggled to open a door.

The more accurate description would be machine plus many

humans defeats single human.

M Y T H # 1

A FRAMEWORK FOR UNDERSTANDING AI 16

AI ≠ Best Algorithm

For many people the terms AI and algorithm are

synonymous.ThebestalgorithmcreatesthebestAI

solution.Facebookhasthebestnewsfeedalgorithm,

Netflixhasthebestmovierecommendationalgorithm,

andGooglehasthebestadplacementalgorithm.

Wethinkthisisincomplete.AIandalgorithmare

notsynonymousterms.Algorithmsareanecessary

componentofAI,butnotadefiningone.Manyleading

expertssuchasAlexanderWissner-Grossnowclaim

data–andnotalgorithms–arethekeylimitingfactor

todevelopmentofhuman-levelartificialintelligence.

M Y T H # 2

A FRAMEWORK FOR UNDERSTANDING AI 17

HereviewedthetimingofthemostpublicizedAI

advancesoverthepast30years,withtheevidence

suggestingmanymajorAIbreakthroughshaveactually

beenconstrainedbytheavailabilityofhigh-quality

training datasets.

Tofurtherillustratethis,let’stakealookatsomeof

the researchpublishedbyGoogleonartificialneural

networks(ANN)thatuselearningalgorithms.Google

wastraininganartificialneuralnetwork–acomputational

modelthatdrawsinspirationfromhowbrainswork–in

imageclassification.Oneofthetaskswasidentifying

dumbbells. The ANN was trained by showing them many

examplesofwhatGooglewantedthemtolearn,hoping

theyextracttheessenceofthematterathand(e.g.,a

dumbbellneedsahandleand2weights),andlearnto

ignorewhatdoesn’tmatter(adumbbellcanbedifferent

weights,sizes,colors,ororientation).

A FRAMEWORK FOR UNDERSTANDING AI 18

SOURCE:SPACEMACHINE

UnfortunatelytheANNfailedtocompletelydistillthe

essenceofadumbbell.

Maybeit’sneverbeenshownadumbbellwithoutan

arm holding it. These mistakes highlight that we need

tobecarefulbeforecompletelyremovinghumansfrom

theprocess.Ahumancanimmediatelyseethemistake

whileamachinecannot.ThiselementiscalledHuman-

in-the-loop(HITL).

Sothisbringsustoamorecompleteworking

definitionofAIfortheenterprise.

A FRAMEWORK FOR UNDERSTANDING AI 19

WebelievethisistheessentialequationthattheCIO

needstounderstandifAIistobeacommercialsuccess

inside an enterprise. So, let’s break it down and imagine

acompanyistryingtocreateanAIsolutionthatcan

categorizecustomersupportticketsbyseveritylevelbased

ontheunstructuredtextshowinganexchangebetween

acustomerandacustomersupportrepdiscussinga

particulartopicorproblemwithinthesupportticket.

TD isTrainingData.TrainingDataisasetofinputswiththecorrectoutputsorexamples

withthecorrectlabelsthatcanbeusedtotrainthe

machine.Inthisexample,theinputistheunstructured

textinsideasupportticket.Theoutputoransweristhe

label“severitylevel,”whichhasbeenappliedbyhumans

accordingtodefinitionsofseveritylevelsspecifictothe

companyinquestion.Anautomotivemanufacturerwill

wanttodefinetheseseveritylevelsdifferentlyfroma

retailbankerorawearabletechnologycompany.

AI = TD + ML + HITL

Training Data Machine Learning Human-in-the-loop

AI = TD + ML + HITL

A FRAMEWORK FOR UNDERSTANDING AI 20

ML is Machine Learning.TheMachineLearning

capabilityistheabilitytoconvertTraining

Dataintoapredictivemodelthatcanbeappliedtonew

inputs–inthiscasenewsupportticketswithunstructured

text.YouwanttheMachineLearningmodeltoapplyits

predictivepowertocreatenewoutputs–inthiscasethe

“severitylevel”label.Oneoftheadvantagesofmachines

comparedtohumansistheirabilitytounderstand

theirownconfidencelevel.Humansarenotoriously

overconfidentatevaluatingtheirownjudgments. So you

canacceptorrejectthepredictionbasedontheMachine’s

ownassessmentofitsconfidencelevel.Forexample,ifa

supporttickethaswordsandphrases,whichhaven’tbeen

seeninthetrainingdata,orseenveryinfrequently,then

themachinewillobjectivelyassessitsownconfidence

levelasbeinglowforthatparticularprediction.

AI ≠ Machines > Humans

M Y T H

M Y T H

T R U T H

AI ≠ Best Algorithm

AI = TD + ML + HITL

A FRAMEWORK FOR UNDERSTANDING AI 21

HITL is Human-in-the-loop. This is the

criticalthirdcomponentofcommercially

viableAI.IftheMachineLearningmodelisnotconfident

initspredictionitcanrouteittohumanstoreviewand

answer.Inthisblendedmodel,youtakeadvantageofthe

speedandscaleofMachineLearningtoaddresstheless

difficulttasks,whilethehumanshandlethehardertasks.

Theresult–anautomatedbusinessprocessfasterand

moreaccuratethanhumansormachinesalone.Humans

andmachinesarebettertogether.

A FRAMEWORK FOR UNDERSTANDING AI 22

Earlierthisyear,Facebookfacedcriticismsthatits

Trendingfeaturewassurfacingnewsstoriesbiasedagainst

conservatives.Inresponsetothiscriticismthecompany

firedallthehumaneditorsforTrending,replacingthem

withanalgorithmthatpromotesstoriesbasedentirelyon

whatFacebookusersaretalkingabout.

Importance of Human-in-the-loop ImagineaDataScientistgoingtotheVPCustomer

Supportandsaying“Ihaveamachinelearningmodel

thatisright70%ofthetime.Ithinkweshould

deployitintoproductionforclassifyingoursupport

ticketsandstopusinghumans.”TheVPCustomer

SupportwilllaughattheDataScientistandsay,“I

cannotaffordtobewrong30%ofthetime.SoI

can’tuseyourmodel.”

Sohowcancompaniesmovebeyondthisimpasse?

ThesolutionisanapproachcalledHuman-in-the-

loopwherethemodelhandlespredictionswhere

it’sconfidentbuthandsoffpredictionsforhuman

reviewwhereit’snotconfident.Ifyoudeploy

MachineLearningwithoutHuman-in-the-loopthen

youaresayingyouhave100%confidenceinallthe

predictionsfromthemodel.Ifyoudothis,youwill

haveavoidablebadoutcomes.

A FRAMEWORK FOR UNDERSTANDING AI 23

MACHINELEARNINGWITHOUTHUMAN-IN-THE-LOOPLEADSTOBADOUTCOMES

Within72hours,accordingtotheWashingtonPost,the

topstoryonTrendingwasafakestoryabouthowFox

NewsiconMegynKellywasapro-Clinton“traitor”who

hadbeenfired.AHuman-in-the-loopapproachwould

havepreventedthisobviouslyflawedoutcome.

IfyouapplyHuman-in-the-loopthenyouhavestarted

toautomateabusinessprocess.Initiallythatbusiness

process–sayclassifyingsupporttickets–is100%human.

ThentheMachineLearningmodelhandlesthehigh

confidentcases,whichismaybe10-20%ofthevolume,

buthumansstillhandlethevastmajoritybecausethe

modelisnotyetconfidentenough.Overtimethemodel

continuestoingestnewtrainingdata–thehumanoutput

–andbecomesmoreaccurateandmoreconfident,so

thepercentageofworkdonebythemodelincreases.

Additionally,thevolumeofworkthatcanbehandledby

thissemi-automatedprocessdramaticallyincreases.

AIismachinesaugmentinghumans,notreplacinghumans.

Inthethirdandfinalchapter,wewilltalkabouthow

to engage the business and think through important

considerationsforevaluatingvendors.

A FRAMEWORK FOR UNDERSTANDING AI 24

Machine → High Confidence PredictionsHuman → Low Confidence Predictions

A FRAMEWORK FOR UNDERSTANDING AI 25 25

Applying AI toyour business

C H A P T E R 3

APPLYING AI TO YOUR BUSINESS 26

Inthefirstchapter,wegavesomeinsightandcontextinto

whyyourCEOisaskingthisquestion,whynow,andwhyyou

theCIO.Inthesecondchapter,wegaveyouafoundational

frameworktothinkaboutAIsoyoucouldgiveyourCEOa

thoughtfulresponse.Inthischapterwewilldiscusshowyoucan

engagethebusinessonthetopicofAIandconsiderimportant

criteriawhenevaluatingAIvendors.

APPLYING AI TO YOUR BUSINESS 27

Engaging the Business

So now you have the AI=TD+ML+HITLconceptual

modeltoapplytoyourbusiness,it’stimetostart

engagingwithyourexecutivecounterpartsin

marketing,product,sales,andcustomersupport.

Inbusiness,theexplosivegrowthofcomplexand

time-sensitivedataenablesdecisionsthatcangiveyou

acompetitiveadvantage,butthesedecisionsdepend

onanalyzingataspeed,volume,andcomplexitythatis

toogreatforhumans.AIisfillingthisgapasitbecomes

ingrainedintheanalyticstechnologyinfrastructurein

industrieslikehealthcare,financialservices,andtravel.

TosuccessfullyapplyAItoyourbusinessthefirstplace

tolookiswhereverdataisbeinganalyzed.Whenever

dataneedstobeanalyzed,AIistheperfectvehicle

toachievethis.Withcompaniescollectingmassesof

APPLYING AI TO YOUR BUSINESS 28

informationthanksmostlytosocialmedia,makingsense

ofthisinformationandfindingvalueisperfectforAI.

Salesisacommonfunctionofanyenterpriseand

Salesforcepredictsthatnearly60%ofbusiness’sales

teamswillincreasetheiruseofsalesanalyticsthisyear.

Forexample,companiescannowuseanalyticstodecide

whichsalesrepresentativesshouldgetwhichleads,what

timeofdaytocontactacustomer,andwhetherthey

shoulde-mailthem,textthem,orcallthem.

Marketingisanotherfunctionoftheenterprisethatcould

begreatlyenhancedbytheuseofAI.AIisdrivinghuge

changeinthewayenterprisescantargetaudiencesfor

marketingandadvertising-evenforsmallercompanies.

This means that businesses are able to target their spend,

increaseROIandallowadvertisingtodowhatitshould

-givepeopleadvertstheywanttosee.Forexample,in

programmaticadbuyingontheWeb,computersdecide

whichadsshouldruninwhichpublishers’locations.

Massivevolumesofdigitaladsandanever-endingflowof

clickstreamdatadependonmachinelearning,notpeople,

todecidewhichwebadstoplacewhere.FirmslikeDataXu

usemachinelearningtogenerateupto5,000different

modelsaweek,makingdecisionsinunder15milliseconds,

sothattheycanmoreaccuratelyplaceadsthatcustomers

aremorelikelytoclickon.

CustomersupportisalsoripeforanAImakeover,asmany

oftherepetitiveaspectsofcustomerservicescouldbe

handledbyanartificialintelligence.Whetherconsumers

willbehappytospeaktoamachineisanothermatter

entirely,asautomatedswitchboardscontinuetobea

majorpressurepointforconsumerswhencontacting

businessesandorganizations.

APPLYING AI TO YOUR BUSINESS 29

Focus on Outcomes not Technologies

Avoidthetrapoftakingtheconversationwithyour

executivecounterpartsinMarketing,Product,Salesand

CustomerSupporttooquicklyintotechnospeak.Focus

theinitialconversationontheoutcomesthatmatterto

them.Agoodwaytofocustheconversationistostart

with2questions:

1. What are you already doing that you want to do faster/cheaper/better?

2. What are you not currently doing that you want to start doing?

Forexample,youmayhavetheSVPofCustomerSupport

saythats/heisnothappywiththequalityandconsistency

ofhowtheyclassifytheseveritylevelofsupporttickets

sinceit’stheindividualcustomersupportrepsdoing

theclassifyingandtheincentivesaremisaligned.Or

youmighthavetheVPProductsaytheyneedtostart

collectingrelevancedataforsearchqueriesandresults

tounderstandhowwelltheyaremeetingcustomer

demand.OryoumighthavetheCMOsaytheyneedto

startcollectingsentimentdatafromTwittertoestablish

abaselineforhowcustomersviewtheirbrandand

productssotheyarenotflyingblindwhentheyembarkon

expensivecampaigns.

Explaining AI

Onceyou’veestablishedtheoutcomesthatmatterto

yourexecutivecounterparts,youcanthenintroducethe

conceptofAI.Don’tleadwithit.ThegoalisnotAIforthe

sakeofAI,butAIthathelpsthebusinessmeetitsbusiness

objectives.Withtheclarityofthebusinessoutcomes

youwanttohelpdeliveragainst,youcannowintroduce

theconceptualframeworkwiththeAI=TD+ML+HITL

equation.Stepthroughtheequationandtranslatewhat

eachconceptmeanintermstheyunderstandtothem.

APPLYING AI TO YOUR BUSINESS 30

Forexample,iftheCMOwantstostartdoingsentiment

analysisatscalethenwalkthroughthefollowing:

Training Data:DownloadthetweetsfromTwitter

basedonthe#hashtagsand@mentionsthatmatter.

Definethequestionsandsentimentscaleyouwantto

use.Findhumanstoapplytheclassification.

Machine Learning: Createamodelthatcanpredict

sentimentbasedontheTrainingData.Applythe

predictivemodeltonewtweets.Modelassignsa

confidenceleveltoeachindividuallevelsentiment

prediction.

Human-in-the-loop: Usehumanstooverridethe

modelpredictionswithlowconfidence.Addthenew

humanlabeleddatatocontinuetotrainandimprove

the model.

Systems of Record with Unstructured Data

OnceyourexecutivecounterpartsinMarketing,

Product,SalesandCustomerSupporthaveasolid

foundationalunderstandingofhowAIcouldapply

totheirbusinesspriorities,thenyoucanmoveonto

takingstockofthenatureofthedatainthemission-

criticalcustomerandproductsystemsofrecord.

Specifically,youwanttounderstandwhatarethe

sourcesofunstructureddata(text,images,audio,

video)thatifstructuredcouldbetheinitial

training data.

Ifyou’relikethetypicalenterprisethenprobably

yourunstructureddatavolumeis4Xyourstructured

data volume.

APPLYING AI TO YOUR BUSINESS 31

SOURCE:IDCTHEDIGITALUNIVERSE,DEC2012

EXABYTES

APPLYING AI TO YOUR BUSINESS 32

Examples of unstructured data could include:

Tweetsfromcustomersdiscussing

yourproductsorbrand

Customerattributeswrittenintoasales

opportunityinSalesforceSalesCloud

orMicrosoftDynamicsCRM

Productdescriptionsandimagesinyour

productcataloguesystemofrecord

Relevancelabelsinyoursearchalgorithm

Emailconversationsbetweencustomersand

supportrepsinsupportticketsinyourSalesforce

ServiceCloud,MicrosoftDynamicsCRM

or Zendesk

Onceyouhaveunderstoodhowandwhereyourbusiness

iscollectingunstructureddata,andthepathtoturnthat

intostructuredtrainingdata,thenmachinelearningisa

possibility.

Evaluating your Vendors

ThethirdandfinalpartofhowtorespondtoyourCEO’s

question“WhatisourAIstrategy?”afterformulating

aframeworkandengagingthebusiness,isevaluating

yourvendors.Managingvendorriskhasbeenpartofthe

CIO’smandatesincetheroleemerged.Developingthis

competencehasbeenmoreimportantasthenumberof

vendorsexplodedwiththeemergenceofthecloudwave.

Ratherthanrehashallthetypicalconsiderationswhen

evaluatingvendors,let’scalloutthreefactorsworthyofextra

focusspecificallyforvendorsclaimingtodeliverAIsolutions.

APPLYING AI TO YOUR BUSINESS 33

Single Domain vs. General Purpose

SomevendorssuchasWise.iohavechosenasingle

domain(customersupport)whileotherssuchas

CrowdFlower and Sentienthavechosentobuildageneral

purposeplatformthatcanfulfillmanymachinelearning

usecasesfortext,images,audio,andvideodata.

Whileoneapproachisnotinherentlybetterthanthe

other,thereisalong-termtrendanddesireforCIOsto

rationalizethenumberofvendorstheymanagesothere

isaslightbiastowardsageneralpurposeplatform,if(and

it’sabigif)thatgeneralpurposeplatformcanmeetthe

businessneedsofthedifferentfunctions.

A

B

A

B

C

?

Sentiment Analyisis

Data Categorization

Data Validation

Transcription

Search Relevance

Data Collection & Enrichment

Image Anotation

Content Moderation

APPLYING AI TO YOUR BUSINESS 34

Black Box vs. White Box

Withtheemergenceof180,000datascientists

inNorthAmerica over the past 5 years, the

organizationalmodelofwheretheyfitisstill

developing.Somemorematureorganizationshave

aChiefDataOfficerwithacentralizeddatascience

function,butthemorecommonmodelseemstobe

adecentralizedmodelwithdatascientistssprinkled

acrossanorganizationinsidedifferentfunctions.

Inthedecentralizedscenariotherewillinevitablybe

abroadspectrumintheskillsetofthedatascientists

withinasinglecompany.Somewillhaveadvanced

machinelearningbackgrounds,whilesomewillhave

progressedtothedatasciencerolefrombeinga

softwareengineeroradataanalyst.Thosewiththe

advancemachinelearningchopsprobablywon’tbe

satisfiedwithablackboxapproachwhereit’snot

transparenthowanalgorithmworksandtheycan’t

finetunetheparameterweightings.Bearthisinmindwhen

consideringsolutionsthatareblackboxonly.

Point Solution vs. Integrated Platform

ManyvendorsclaimtobeAIsolutions,butasyounow

knowtheyareconflatingAIwithMachineLearning.

CommerciallyviableAIneedsthe3criticalcomponents

ofTrainingData,MachineLearningandHuman-in-the-

looptobeintegratedtogether.Soyouhaveachoice.

Eitherselect2or3differentvendorsforTrainingData,

MachineLearningandHuman-in-the-looporintegrate

themyourself.Evenwithwell-definedRESTfulAPIsthere

isstillacosttodothat.Orlookforasolutionthathas

TrainingData,MachineLearningandHuman-in-the-loop

integratedintoasingleplatform.

Training Data MachineLearnin g

Human-in -the-Loop

CONCLUSION 35

Conclusion

Nowthatyou’rearmedwithanapproachforhowto

engageyourbusinessonthetopicofAI,whywaitforyour

CEOtoask,“What’sourAIstrategy?”Insteadbeproactive

andtellyourCEO“Here’sourAIstrategy.”ThedaysofCIO

meaning“careerisover”arelonggone.It’stimeforthe

bestCIOstoseizetheinitiativeandridetheAIwave.

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