非洲人工智能：产生影响的用例（英）-78正式版-WN8

AIforAfrica:UsecasesdeliveringimpactJuly2024Copyright©2024GSMAGSMAGSMACentralInsightsUnitTheGSMAisaglobalorganisationunifyingthemobileecosystemtodiscover,developanddeliverinnovationfoundationaltopositivebusinessenvironmentsandsocietalchange.Ourvisionistounlockthefullpowerofconnectivitysothatpeople,industry,andsocietythrive.TheCentralInsightsUnit(CIU)sitsatthecoreofGSMAMobileforDevelopment(M4D)andproducesin-depthresearchontheroleandimpactofmobileanddigitaltechnologiesinadvancingsustainableandinclusivedevelopment.TheCIUengageswithpublicandprivateRepresentingmobileoperatorsandorganisationsacrossthesectorpractitionerstogenerateuniqueinsightsandanalysismobileecosystemandadjacentindustrieschallenges,theGSMAdeliversforitsmembersacrossthreebroadpillars:onemerginginnovationsintechnologyfordevelopment.Throughourinsights,wesupportinternationaldonorstoConnectivityforGood,IndustryServicesandSolutions,andbuildexpertiseandcapacityastheyseektoimplementOutreach.Thisactivityincludesadvancingpolicy,tacklingtoday’sbiggestsocietal,underpinningthetechnologyandinteroperabilitythatmakemobilework,andprovidingtheworld’slargestplatformtoconvenethemobileecosystemattheMWCandM360seriesofevents.digitisationinitiativesinlow-andmiddle-incomecountriesthroughpartnershipswithinthedigitalecosystem.Contactusbyemail:centralinsights@WeinviteyoutofindoutmoreatFollowtheGSMAonTwitter/X:@GSMAAxumisanAfrocentricimpactcompanydedicatedtofosteringclimate-positive,digitallyinnovative,inclusivegrowthacrossAfrica,theMiddleEastandaroundtheworld.Thecompanyworkswithlocallyandgloballyinfluentialleadersthatseektodrivesustainabledevelopment,inclusionandprosperity.ThisinitiativehasbeenfundedbyUKAidfromtheUKGovernmentandissupportedbytheGSMAanditsmembers.TheviewsexpresseddonotnecessarilyreflecttheUKGovernment’sofficialpolicies.Throughstrategicleadershipandtheabilitytotransformideasintoreality,Axumpartnerswithdiversestakeholderstodrivepositivechange.Boastingover150yearsofcollectiveleadershipexperience,andateamofnearly100across10officesinAfricaandtheMiddleEast,AxumleveragesawealthofmultisectoralandmulticulturalexpertisetohelpclientsnavigatepressingglobalchallengesandrealiseAfricaandtheMiddleEast’simmensepotential.AuthorsandcontributorsAuthors:EugénieHumeauandTanviDeshpandeContributor:DanieleTricaricoAcknowledgementsThisreportdrawsonresearchconductedfortheGSMAbyAxum.ꢀWewouldliketothankGathoniKang'ethe,JamilaRaji,JonathanMunge,SalmaAitHssayene,IsisNyong’oMadisonandRobinMillerfortheircontribution.WewouldalsoliketothankDrEmmyChirchirandDrEmmelineSkinner(FCDOEastAfricaResearchandInnovationHub),KristinKlose(FCDOSouthAfricaResearchandInnovationHub)andOluwasegunAdetunde(FCDOWestAfricaResearchandInnovationHub)fortheirinputandfeedback.WewouldliketothankthefollowingindividualswhowerepartofourExpertAdvisoryGroupandprovidedguidanceandexpertiseduringtheresearchprojectthroughvariousengagements:AlbanOdhiambo(TonyBlairInstituteforGlobalChange),DeshniGovender(GIZ–FAIRForward),DrGirmawAbebeTadesse(MicrosoftAIforGoodLab),KateKallot(Amini),KoliweMajama(MozillaFoundation),LavinaRamkissoon(AfricanUnion),LilySteele(GlobalInnovationFund),LinetKwamboka(GlobalPartnershipforSustainableDevelopmentData),LukasBorkowski(Viamo),MatthewSmith(IDRC)andDrOlubayoAdekanmbi(DataScienceNigeria).Finally,wewanttothankthemanyindividualsandorganisationsthatcontributedtotheresearch.Afulllistoforganisationsconsultedfortheresearchislistedattheendofthereport.ContentsExecutivesummary41.Introduction72.Researchobjectivesandmethodology103.DefiningAIWhatisAI?141516AIfundamentalsinAfrica4.UsecasesdeliveringimpactKeytrendsacrossusecasesAgricultureandfoodsecurityEnergy2930354249Climateaction5.TowardsathrivingecosystemCreatingaconducivepolicyenvironmentFosteringpartnerships5657606364UnlockingfinancingatscaleSupportingresearchanddevelopment6.ConclusionandrecommendationsAnnexes6672ListoffiguresFigure1EstimatedannualvalueoftheAImarketFigure14dAllocationofusecasesbyownershipinAfricarelativetotheglobalmarketFigure14eAllocationofusecasesbytypeofsolutionFigure2PotentialvalueaddedbyAItotheAfricaneconomyFigure15Figure16Figure17Agriculture’scontributiontoGDPandlabourforcebycountryFigure3Figure4Figure5TheAIecosystemframeworkThefiveVsofbigdataOverviewofusecasesinagricultureandfoodsecurityExamplesofdatatypesandsourcesforAIfordevelopmentHeatmapofusecasesinagricultureandfoodsecuritybycountryFigure6Figure7GenerationandusageofdatasetsgloballyFigure18Figure19AccesstoelectricitybycountryPrevalenceofinternetcontentinAfricanlanguagescomparedtoglobalbenchmarksAfricancountrieswithmoredieselgeneratorcapacitythangridcapacityFigure20ElectricitygridmixinSub-SaharanAfricaFigure8Figure9AIinfrastructureandcomputelayersFigure21Figure22OverviewofusecasesinenergyCurrentandprojectedsmartphoneadoptionbycountryHeatmapofusecasesinenergybycountryFigure10Figure11Projectedpercentageof5GconnectionsbycountryFigure23CO2emissionsbyregionFigure24OverviewofusecasesinclimateactionSkillsetsrequiredbyAIbuildersandAIusersFigure25RemotesensingasatooltosupportclimateactionFigure12Figure13Whatmakesagoodprompt?Figure26HeatmapofusecasesinclimateactionbycountryDistributionofusecaseapplicationsbycountryFigure27Figure28AIpolicydevelopmentinAfricaFigure14aAllocationofusecasesbysectorFigure14bAllocationofusecasesbytypeofAITypesofactorsinvolvedinpartnershipsforAIFigure14cAllocationofusecasesbytypeoforganisationListoftablesTable1Table2Table3ResearchmethodologyTable5VenturecapitalinvestmentsinAIbycountryHungerassessmentbycountryTable6Table7CountryranksforR&DcapabilitiesVulnerabilitytoclimatechangeandreadinesstoimproveresilienceKeyrecommendationstosupportAIdeploymentandadoptionTable4VenturecapitalinvestmentsintechbycountryListofboxesBox1Buildinglocallanguagedatasets:ChallengesandopportunitiesBox5Usecasedeepdive:FoodsecurityforecastingBox2Whatarethebenefitsofedgecomputing?Box6Usecasedeepdive:EnergyaccessanddemandassessmentBox3'AskViamoAnything'bringsgenerativeAItechnologytodigitallydisconnectedcommunitiesBox7Usecasedeepdive:BiodiversitymonitoringBox8UNESCO’shumanrights-centredapproachtotheethicsofAIBox4Usecasedeepdive:PrecisionagricultureAIforAfrica:Usecasesdeliveringimpact2/76ListofacronymsAIArtificialIntelligenceIVRLLMMLInteractiveVoiceResponseLargeLanguageModelMachineLearningCDRDFSCallDetailRecordsDigitalFinancialServicesEWSEarlyWarningSystemMNOMobileNetworkOperatorNLPNaturalLanguageProcessingGDPGISGrossDomesticProductGeographicInformationSystemGenerativePre-trainedTransformerGraphicProcessingUnitNRMNaturalResourcesManagementPAYGPay-As-You-GoGPTGPUHPCPPPR&DSHSPublic-PrivatePartnershipResearchandDevelopmentSolarHomeSystemHighPerformanceComputingHWCHuman-WildlifeConflictIoTInternetofThingsUSSDUnstructuredSupplementaryServiceDataDefinitionsAIforDevelopment:Weusetheterm‘AIfordevelopment’torefertotheuseofAIanditsapplicationswiththepotentialtoaddressdevelopmentchallengesinlow-andmiddle-incomecountries.Computervision:AtypeofAIthatenablescomputersandothermachinestoidentifyandinterpretvisualinputsfromimagesandvideos.3GenerativeAI:AtypeofAIthatinvolvesgeneratingnewdataorcontent,includingtext,imagesorvideos,basedonuserpromptsandbylearningfromexistingdatapatterns.Algorithm:Aprocessorsetofrulestobefollowedincalculations,especiallybyacomputer,tosolveaproblem.Machinelearning:AsubfieldofAI,broadlydefinedasthecapabilityofamachinetoimitateintelligenthumanbehaviourandlearnfromdatawithoutbeingArtificialintelligence:Artificialintelligence(AI)iscomprisedofwidelydifferenttechnologiesthatcanbebroadlydefinedas“self-learning,adaptiveexplicitlyprogrammed.4systems.”AIhasthecapabilitytounderstand1NLP:Afieldofmachinelearninginwhichmachineslearntounderstandnaturallanguageasspokenandwrittenbyhumans,insteadofthedataandnumbersnormallyusedtoprogramcomputers.language,solveproblems,recognisepicturesandlearnbyanalysingpatternsinlargesetsofdata.BigTech:Inthisreport,BigTechplayersrefertothelargetechcompaniesknownglobally,includingGoogle,Microsoft,IBM,Meta,andAmazon.Theterms'BigTech'and'largetechcompanies'areusedinterchangeablyinsomecontexts.PredictiveAI:AtypeofAIthatusesstatisticalanalysisandmachinelearningalgorithmstomakepredictionsaboutpotentialfutureoutcomes,identifycausationandassessrisks.5Compute:ComputereferstotheprocessofRemotesensing:Acquiringinformationfromadistanceviaremotesensorsonsatellites,aircraftsanddronesthatdetectandrecordreflectedoremittedenergy.AllobjectsonEarthreflect,absorbortransmitenergy,withtheamountvaryingbywavelength.ResearcherscanusethisinformationtoidentifydifferentEarthfeaturesaswellasdifferentperformingcalculationsorcomputationsrequiredforaspecifictask,suchastraininganAImodel.Italsoencompassesthehardwarecomponents,likechips,thatcarryoutthesecalculations,aswellastheintegratedsystemsofhardwareandsoftwareusedtoperformcomputingtasks.2rockandmineraltypes.61DefinitionbytheInternationalTelecommunicationUnion(ITU).23456AINowInstitute.(2023).ComputationalPowerandAI.DefinitiontakenfromMicrosoftAzure’sdictionaryoncloudcomputing.DefinitionbytheMITSloanSchoolofManagement,basedonthedefinitionbyAIpioneerArthurSamuel.DefinitionfromtheCarnegieCouncilforEthicsinInternationalAffairs.DefinitionbyNASAEarthdata.AIforAfrica:Usecasesdeliveringimpact3/76ExecutivesummaryThepotentialofAIinAfricaAIholdsimmensepotentialtoboostAfrica’seconomyandtosupporttheSustainableTheagritechsectorisseeingmostoftheAIinnovation,especiallyinKenyaandNigeriawhereDevelopmentGoals(SDGs)onthecontinent.WhileAIagriculturecontinuestoplayasignificantroleintheisalreadybeingdevelopedanddeployedtosupportarangeofusecasesacrossAfricancountries,littleresearchhasfocusedonbuildingabodyofevidenceofAIusecasesfordevelopmentonthecontinent.Thisreportisbasedontheanalysisofover90usecaseapplicationsidentifiedinKenya,Nigeria,andSouthAfrica–whichbenefitfromthrivingtechecosystems–acrossagricultureandfoodsecurity,energy,andclimate.WhilemanyAIusecasesarerelativelynascent,withsomebeingdeployedaspartofprojectsorpilotschemes,anumberofcommerciallyviablesolutionshavealsoemerged.Often,AIisbeingincorporatedintoexistingdigitalproductsandservices,actingasanenablertomakedigitalsolutionsmorerelevantandefficient,amplifytheirimpact,andfacilitatescaling.economy.AIisalreadybeingusedforagriculturaladvisory,withcompanieslikeTomorrowNowandThriveAgricprovidingfarm-levelinsightstofarmers,andforfinancialserviceswithcompanieslikeApolloAgriculturedevelopingalternativecreditassessmentmethods.AIisalsobeingdeployedintheenergysector,especiallyinNigeria,whereemergingtechnologieslikeInternetofThings(IoT)actasanentrypointforadvanceddataanalyticsinsmartenergymanagement.Usecasessuchasenergyaccessmonitoringandproductiveuseassetfinancing,developedbycompanieslikeNithio,remainatadevelopingornascentstagebutpresentsignificantpotentialtoreduceenergypoverty.AIisalsosupportingclimateusecasesespeciallyforbiodiversitymonitoringandwildlifeprotectioninKenyaandSouthAfrica,drivenbylargetechcompanieslikeMicrosoft’sAIforGoodLabandnon-profitorganisationssuchasRainforestConnection.AIforAfrica:Usecasesdeliveringimpact4/76AIfundamentalsandenablingenvironmentTheincreasingavailabilityofdatageneratedbyremotesensingtechnologies,suchason-the-groundsensors,droneswithhigh-resolutioncameras,andsatellites,hasledtothedevelopmentofmanyAI-drivenusecasesacrosssectors.Analysisofgeospatialandremotesensingdata,poweredbymachinelearning(ML),cansupportawiderangeofusecasesandactivitiessuchasmonitoringsoilconditionsforeffectivecropmanagement,mappingenergyaccessinoff-gridareastoinformenergyplanning,andmonitoringclimatechangeimpactsonecosystems.Despitetheseadvancements,theavailabilityoflocallyrelevantdataremainslimitedinAfricaandposesamajorobstacletodevelopinganddeployingtailoredsolutionsthataddresschallengesthatareuniquetothecontinent.Inadditiontobarriersinaccessinggovernmentanddomain-specificdata,oneofthemostsignificantgapsisinlanguagedata.ThescarcityoflocallanguagedatalimitstherelevanceofAI-enabledservicesandposesasignificantbarriertothedevelopmentofgenerativeAIsolutionsthatrelyonlanguagemodels.Acrosscountries,asignificantskillsgapstillunderminesthedevelopmentoftheAIecosystemandusecases.WhileuniversitiesofferAI-relatedcourses,theyoftenfailtokeeppacewithindustryneeds,andstudentshavelimitedopportunitiesforpracticallearningandhands-onexperiences.ThereisalsoadisproportionatefocusoncoreAIskills,suchasMLanddatascience,withlessemphasisonbuildingthemultidisciplinaryskillsetsneededtoleverageAItoaddresspressingsocioeconomicchallenges.Despitethesechallenges,organisationslikeDataScienceNigeria(DSN)offerupskillingandmentorshipprogrammestobuildapipelineofAItalent.Inparallel,endusersrequireafoundationallevelofdigitalliteracytoaccessAI-enabledservices,whichareprimarilyaccessiblethroughdigitalchannelslikemobiledevices.However,lackofknowledgeandskillsremainsoneofthegreatestbarrierstoadoptionanduseofdigitaltoolsandservices,especiallyforwomen,low-incomeandruralcommunities,andpersonswithdisabilities.WhileKenya,NigeriaandSouthAfricaareallregionaltechleadersandhavesoliddigitalfoundationsthatcanserveasthebuildingblocksforAIdevelopment,keychallengesremainintheecosystem.DespiteInfrastructureandcomputecapacityinAfricaisgrowing,andcountrieslikeSouthAfricahaveemergedasregionalleaders.IncreasinginvestmentsindatacentresfromlargetechcompaniesandMobilewideenthusiasmaboutthepotentialofAIforAfricaNetworkOperators(MNOs)inNigeriaandKenyaareforexample,privatesectorinvestorsremainrisk-alsodrivingmomentumintheregion,bringingcriticalaverseaboutinvestingindeeptech,andstartupsstorageandcomputingcapacitytothelocallevel.However,thehighcostsofhardwaresuchasGraphicProcessingUnits(GPUs)andcloudcomputingstillconstituteamajorbarriertoAIdeploymentandadoption,especiallyforlocalentrepreneursandresearcherswithlimitedfinancialresources.Aslocalcomputeecosystemscontinuetodevelop,thereisanopportunityforcountriesinAfricatotapintotheirmobile-firstmarketstobuildcapacityindistributed-edgecomputing.InKenyaforexample,deeptechhavetorelyongrantfundingfromdevelopmentpartnersanddevelopmentfinanceinstitutions(DFIs).Similarly,lowpublicandprivatesectorinvestmentinResearchandDevelopment(R&D)mayunderminethedevelopmentoflocalsolutions.WhilesomecountriesinAfricahavealreadydevelopednationalAIstrategies,Kenya,NigeriaandSouthAfricaarestillintheprocessofdraftingtheirown–buthaveadoptedinclusiveformulationprocesses.Mostframeworksacrossthecontinentremainintheirinfancy,companyFastaggerdevelopsMLcapabilitiesonedgehighlightingtheneedtoshiftfrompolicyformulationdevices,includingonlower-endsmartphones.toimplementationandtoensureethical,responsibleandsafeuseofAI.AIforAfrica:Usecasesdeliveringimpact5/76High-levelrecommendationsDifferentstakeholders–governments,developmentpartners,DFIs,NGOsandCivilSocietyOrganisations(CSOs),largetechcompaniesandstartups,andresearchandacademicinstitutions–cantakeanumberofactionsandcollaboratetoensurethatimpactfulinnovationsinAfricacanbedeployedandscaled.Thisinvolvesinvestingindomain-specificandlocallanguagedata,adoptingparticipatoryapproachestodatacollection,unlockingaccesstoexistingdatasources,andensuringdataprivacyandsecurity.Strengtheningbaselineinfrastructureandpromotingrenewableenergy,providinghardwareandcloudcredits,enhancingedgecomputingcapabilitiesandbuildinginstitutionalcapacitywillbeStakeholdersacrosssectorscanalsofocusonsupportingthewidertechandAIecosystemtofosteranenvironmentconducivetoinnovationandAIdeploymentacrossusecases.ThisinvolvesengaginginpartnershipstounlockaccesstocriticalresourcesforAIentrepreneursandresearchers,andtosupportthedevelopmentoftheAIecosystemthroughdata-sharingorinfrastructure-sharinginitiatives.Adoptingaconsortium-basedapproachhasthepotentialtohelpaddressthefinancinggap,whileadoptinginnovativefinancemechanismscande-riskinvestments.Combiningfundingwithtechnicalassistanceandgo-to-marketsupportcanalsohelpfoundersintheirscalingjourney.Increasedessentialtoboostlocalcomputecapacity.Inaddition,R&Dspendingwillbeessentialtosupportlocalfosteringacademic-industrycollaboration,raisingawarenessandbuildingcapacityinthepublicsectorwillbeessentialtocreateapipelineofAItalentwhileensuringinformedpolicymaking.TofosteradoptionandusageofAI-enabledservices,enhancingdigitalresearchcapacity,whilelocal-globalknowledgeexchangecandrivefurthermomentumandraiseawarenessaboutlocalinnovation.AscountriesworkondevelopingnationalAIstrategies,itwillbecriticaltoensureacollaborativeandinclusiveprocess,toskillsamongendusersandintegratingemergingskillsincludeprinciplesfortheethicalandsafeuseofAI,likeprompt-engineeringintoupskillingprogrammeswillbekey,especiallyasgenerativeAIsolutionsgraduallygrowinAfrica.andtoestablishaclearroadmapforimplementation.Policymakerscanalsoconsiderrollingoutregulationsinaphasedmannertoallowinnovationtoflourish.AIforAfrica:Usecasesdeliveringimpact6/761.IntroductionAIforAfrica:Usecasesdeliveringimpact7/76Overthepastyear,artificialintelligence(AI)anditstransformativepotentialhascapturedglobalattention.ThepotentialofAIinhelpingachievethe2030SustainableDevelopmentGoals(SDGs)iswellestablished.7,8AIapplicationscancreatesocialandeconomicimpact,especiallyinlow-andmiddle-incomecountrieswhereinnovativeapproachestoinclusiveandsustainabledevelopmentaremostneeded.Africarepresentsonly2.5%oftheglobalAImarket,yetrecentestimatessuggestthatAIcouldincreaseAfrica’seconomyby$2.9trillionby2030—theequivalentofincreasingannualGrossDomesticProduct(GDP)growthbythreepercent.Thisboost9ineconomicgrowthcouldtranslateintosignificantdevelopmentimpactsforthecontinent,providingemploymentopportunitiesandhelpingtoraisemillionsoutofpoverty.Figure1Figure2EstimatedannualvalueoftheAImarketinAfricarelativetotheglobalmarketPotentialvalueaddedbyAItotheAfricaneconomy($trillion,2024-2030)($trillion,2023)6WithAI5$2.9trillion4$16.5trillionWithoutAI3GlobalAIvalue$0.4trillionAfricanAIvalue2Approx2.5%oftheglobalAImarket2024202620282030GDPvaluewithAIGDPvaluewithoutAICumulativegainsinGDPaddedbyAI789Smith,M.&Neupane,S.(2018).Artificialintelligenceandhumandevelopment:Towardaresearchagenda.IDRC.Bankhwal,M.etal.(2024).AIforsocialgood:Improvinglivesandprotectingtheplanet.McKinseyDigital.AI4DAfrica.(2024).AIinAfrica:Thestateandneedsoftheecosystem.AIforAfrica:Usecasesdeliveringimpact8/76MobileconnectivityinSub-SaharanAfricacontinuestodrivedigitaltransformationandsocioeconomicadvancements.Agrowingproportionofthepopulationisconnectedtoandusingmobileinternet,andsmartphonepenetrationisexpectedtoreach88%by2030,creatingnewopportunitiesfordigitalinclusionandusageofAI-enabledservices.10CountriessuchasKenya,NigeriaandSouthAfricaalreadyhavesomeofthemostadvancedtechecosystemsintheregion.KenyaisparticularlyrenownedforpioneeringmobilemoneythroughM-Pesa,whileNigeriahasproducedseveralAfricanunicorns.Thesecountriesalsohavetech-relatedpoliciesthathavefosteredarelativelyconduciveenvironmentforinnovationandentrepreneurship.Theirsoliddigitalfoundationscanserveasbuildingblocksforthedevelopment,deploymentandadoptionofAI.regularpoweroutages.Inaddition,insufficientavailabilityofdataandlackofdataecosystems,lowlevelsofdigitalskillsandliteracy,fragmentedornon-enforcedpoliciesandnascentresearchcapacitiesconstitutekeybarriersforthedevelopmentoftheAIecosystem.AIalsobringssignificantrisksintermsofdataprivacy,biasanddiscriminationthatneedtobeaddressedtoensuresafeandresponsibleuseofthetechnology.WhiletherehasbeenanaccelerationoftechnologycompaniesleveragingAIandinitiativestodevelopandpromotetheuseofAIonthecontinent,thesehavenotnecessarilyfocusedonaddressingsocioeconomicordevelopmentchallenges.MostexistingusecasesaretypicallyfoundinsectorssuchasITservices,computersoftware,ormanagementconsulting.11Thereisalackoffocusonbuildinglocal,inclusive,andsustainableAIsolutions12thatcanhelpaddresstheSDGsinAfrica.Thereisapressingneedtoidentifyandtestmodelsandusecasesthatcanaddressdevelopmentchallenges,aretailoredtomeetthespecificneedsoflocalcommunities,andhavethepotentialtobescaledtoamplifytheirimpact.ConsideringthediversecontextsandculturesacrossAfrica,fosteringequitablepartnershipstobuildAIusecasesfordevelopmentandnurturethegrowthoflocalecosystemswillbecriticaltoharnessthepotentialofAItohelpachievetheSDGsontheHowever,unlockingthepotentialofAIwillrequireovercomingseveralchallenges.Whilethecoveragegaphassignificantlyreduced,theusagegapinSub-SaharanAfricastillstandsat59%,meaningthatmillionsofpeoplewholivewithinthefootprintofamobilebroadbandnetworkarenotusingmobileinternet.Significantdigitaldividesexistanddisproportionatelyaffectlow-incomegroups,thosewhoarelesseducated,ruralpopulationsandwomen,anddigitalisationandAIriskexacerbatingexistingsocioeconomicinequalities.Kenya,Nigeria,andSouthcontinent.Africahavecriticalinfrastructuregapsandundergo10GSMA.(2023).TheMobileEconomySub-SaharanAfrica2023.11TheAIMediaGroupSouthAfrica.StateofAIinAfricaReport2022.12Inthisreport,local,inclusiveandsustainableAIsolutionsreferstoAIapplicationsthataretailoredtolocalneedsandconstraintstofosterinclusivityandprioritiseaddressingdevelopmentchallengesinlinewiththeSDGs.AIforAfrica:Usecasesdeliveringimpact9/762.ResearchobjectivesandmethodologyAIforAfrica:Usecasesdeliveringimpact10/76ResearchobjectivesThisresearchseekstoidentifyAI-enabledusecasesandsolutionsthataddressdevelopmentchallengesrelatedtoagricultureandfoodsecurity,energyandclimateaction.ItfocusesonKenya,NigeriaandSouthAfrica,whoarealltechnologyleadersonthecontinentandintheirsub-region,andpresentsignificantpotentialtoleverageAIfordevelopment.Toaddresstheobjectivesoftheresearch,weinvestigatedthefollowingkeypillarsoftheAIecosystemtounderstandhowtheyimpactthedevelopmentandscalabilityofusecases:thedigitaleconomyfoundations,encompassingdigitalinfrastructure,humancapitalandskills,andpolicyandregulation;theAIfundamentals,includingdata,AI-specificskills,andcomputecapacity;andcross-cuttingenablers,suchaspartnerships,financingmechanisms,andresearchanddevelopment.Morespecifically,theresearchseeksto:1.IdentifyAI-enabledusecasesandsolutionsacrosstheselectedsectors,highlighttheirkeyrequirementsandassesstheirpotentialforimpact,scaleandconstraints.Whilewehaveseparatedtheenablersofeachmainpillarinourframework(Figure3)toshowthattheAIecosystemsitsontopofabroaderdigital/technologyecosystem,wehavegroupedtheminthereportascertainelementssuchasinfrastructure,skillsandpolicycanbeunderstoodaspartofaspectrum.2.ProvidealandscapeoverviewoftheAIecosystemineachcountrytoidentifygapsandopportunitiestoimprovetheenablingenvironmentanddevelopmentofAI-enabledusecases.3.Offerasetofrecommendationsforkeystakeholders,pinpointingwaystocatalysethedevelopmentoftheAIecosystemdeliveringimpactintheregion.Figure3TheAIecosystemframeworkiPartnershipsFinancingmechanismsResearchanddevelopmentDataAIfundamentalsComputeAIskillsDigitaleconomyfoundationsDigitalinfrastructureHumancapitalandskillsPolicyandregulationAIforAfrica:Usecasesdeliveringimpact11/76Thisreportreliesondesk-basedresearchandvalidationthroughdiversestakeholderengagement.ThemethodologyisoutlinedinTable1.Table1ResearchmethodologyDatasourceObjectiveDevelopanunderstandingoftheAIfordevelopmentDesk-basedresearchlandscapeinAfricaandinKenya,NigeriaandSouthAfrica,andexistinginitiativessupportingAIfordevelopmen