【IPPR】2025英国人工智能创新方向报告基于新数据库的洞察与改革路线图

InstituteforPublicPolicyResearch

THEDIRECTION

OFAIINNOVATIONINTHEUK

INSIGHTSFROMANEWDATABASEANDAROADMAPFORREFORM

CarstenJungandBhargavSrinivasa

Desikan

April2025

ABOUTIPPR

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ThispaperwasfirstpublishedinApril2025.©IPPR2025

Thecontentsandopinionsexpressedinthispaperarethoseoftheauthorsonly.

Theprogressivepolicythinktank

CONTENTS

Summary 5

1.Introduction:AIdeploymentneedsnotjustacceleration,butdirection 8

Measuringthedirectionofinnovationandidentifying

‘deploymentgaps’ 9

2.Keyfindingsfromournewdatabase 10

AIbusinessesfocusmainlyongeneralprocessimprovements

ratherthanspecificproblemsolving 10

AIadoptionisfocussedontheknowledgeeconomyand

processimprovement 11

Theuseofoff-the-shelfmodels:AIadoptionintheUKcould

toalargeextentinvolvebusinessprocessinnovationrather

thanAIsoftwareinnovationperse 14

3.Deepdives:WhatarethevaluepropositionsofAIcompanies

andwherearethegaps? 17

Casestudy1:significantlyimprovingpublichealthwillrequire

morefocusonprevention 17

Casestudy2:TransportAIinnovationhasabigfocuson

autonomousvehiclesandlogisticsbutnotonimprovingaccess 20

4.Policyrecommendationsformission-drivenAIinnovation 23

Recommendation1:Thegovernmentneedstobettertrack

AIdeploymenttoinformpolicy 24

Recommendation2:Breakmissionsdowntospecific

problemstatements 25

Recommendation3:Aligninnovationpolicyclearlywith

missionstocreate‘technologypush’ 26

Recommendation4:Usesubsidies,procurementand

preferentialfinancingforAIadoptionandmarket

shaping,creating‘demandpull’ 30

References 34

Appendix:Methodology 37

IPPR|ThedirectionofAIinnovationintheUKInsightsfromanewdatabaseandaroadmapforreform3

4IPPR|ThedirectionofAIinnovationintheUKInsightsfromanewdatabaseandaroadmapforreform

ABOUTTHEAUTHORS

CarstenJungisheadofAIatIPPR.

BhargavSrinivasaDesikanwasaseniorresearchfellowatIPPRatthetimeofwriting.

ACKNOWLEDGEMENTS

WewouldliketothankAnnieWilliamsonandStephenFrostfortheirin-depth

adviceonthehealthandtransportsectorcasestudy.Wewouldalsoliketothank

AlexandraLowe,StuartThompson,KieranNeild-Ali,CharlesMcIvor,SamFreedman,KirNuthi,PeterHyman,Harry-QuilterPinner,GeorgeDibb,SimoneGasperin,RainerKattel,SebKrierandAndrewBennettforveryhelpfulconversationsandcomments.WewouldalsoliketothankSylviaMonkhouse,RichardMacleanandAbiHynesandforcopyeditingandproducingthereporttothehigheststandard.

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IPPR|ThedirectionofAIinnovationintheUKInsightsfromanewdatabaseandaroadmapforreform5

SUMMARY

Recentdevelopmentsinartificialintelligence(AI)couldhavetransformative

effectsontheeconomy.Withthelatestmodelsachievingtopscoresinscientificanddiagnosticreasoningtests,theycouldusherinaneweraofgrowth.InJungandSrinivasaDesikan(2024)weestimatedthatexistingmodels,ifwidely

implementedinthemediumterm,couldhelpraisegrowthby13percent.AdvancedAIcouldalsohelptacklebigsocietalchallengesrangingfromillhealthtoenvironmentaldegradation.

ButrealisingthebenefitsofAIrequiresmorethanjustacceleratingdeployment.PolicyneedstoalsoprovidestrategicincentivesforaligningAIdeploymentwiththegovernment’smissions.Inthispaper,weanalysetheAIinnovationlandscapeintheUKtodeterminewhichtypeofAIdeploymentisandisnotcurrentlytakingplace.Weidentify‘AIdeploymentgaps’andmakerecommendationsforhowtheycanbefilled.

Todoso,webuiltafirst-of-its-kind(toourknowledge)databaseof3,256AIfirmsintheUK.IthasdetailedinformationonthetypeofAIapplications,sectorfocus,andspecificproblemstatementsthatAIapplicationsaresolving.Fromthis,we

developedmeasuresforthecurrentdirectionofAIinnovationandconsiderwhereAIdeploymentgapscouldlie.

RegardingthedirectionofUKAIinnovation,wefindthefollowing.

•TheUKisseeingrapidandfar-reachingAIinnovation.Wefindactivity

acrossallsectorsoftheeconomy,andacrossbusinesslines.ThisshowsinnovationdynamismintheUKandsuggeststhefirstwaveofdeploymentcouldsoonbefeltbyemployeesandconsumers.

•15percentofAIvaluepropositionsfocusonsolvingspecificproblemsinspecificsectors,while85percentarefocussedonmoregeneral

processimprovements.Thissuggestsmoregradualratherthanrapidtransformativeimpacts.

•70percentofAIfirmsareactiveinknowledgeeconomysectors.In

otherwords,adoptionisonlyslowlyreachingbeyondknowledgeintensive

industries–afirstsignofpotentialAIdeploymentgaps.Only15percentofapplicationsarefocussingonproductandR&Dinnovation–iegeneratingnewvaluepropositions–withtheremainderfocussedonmakingexistingbusinessprocessesmoreefficient.

•Wefindindicativeevidencethatmanybusinessesoftenuseoff-the-shelfmodels(proprietaryandopensource,suchasthosebyOpenAI,Anthropic,DeepSeekandMeta)ratherthantrainingtheirownin-housemodels.ValueaddfromAIadoptioncouldtherefore,toalargeextent,involvebusiness

processinnovation–AIdeploymentinotherwords–ratherthandevelopingnewAImodels.

ToillustratewhattypesofproblemsAIdeploymentisaimedat–andwhatthevaluepropositionsare–welookmorecloselyattwoAIinnovationareas:healthandtransportation.Wefindthefollowing.

•PublichealthisaburgeoningfieldofAIinnovation.HealthisthesecondlargestsectorforAIactivity–withmostspecialisedinnovationfocussedondiagnosis,drugimprovementandtreatmentimprovement.However,wehighlightthattobemoremission-aligned–asiswidelyrecognisedinthepublichealthspace–

6IPPR|ThedirectionofAIinnovationintheUKInsightsfromanewdatabaseandaroadmapforreform

therewillneedtoanincreasedfocusonprevention.However,wefindthatonly12percentofvaluepropositionsareinthepreventionspace.Moreinnovationactivityinthisareacouldhelpdeliverthegovernment’smission,andpolicy

canhelpgenerateit.

•AIinnovationinthetransportsectorhasabigfocusinautonomousvehiclesandoperationalefficiencies.Butfortechnologicalinnovationtobefully

mission-alignedthereisaneedtoincreaseaccesstotransportwhilealsoreducingcarbonemissions.Moreinnovationwouldbeneededintransformingthewaywetravel,includingbypersonalisingthetransportoffer,increasingon-demandtransitandencouragingmulti-modaltravel.Wefindthat,inthetransportsector,only9percentofAIinnovationsareinthisspace.

Wearguethat,tofillthesegaps,AIinnovationpolicyneedstobegenuinely

mission-driven,andcloselyalignedwiththegovernment’svariousobjectives.Wemakefourrecommendations.

•First,AImakesitmoreimportantforgovernmentstobreakdowntheirmissionsintomorespecificunderlyingtargetsandproblemareas.AIinnovationcanbestbetargetedtowardssocialgoodifthereareclearlyidentifiedproblemsthatitcanhelpsolve.

•Second,tosteerprogress,innovationpolicyshouldbeexplicitlylinkedto

governmentmissionsandspecific‘problemareas’.ThisshouldbeembeddedinInnovateUK’sgrantmakingandsomeoftheBritishBusinessBank’sfinancialsupport.Itwillrequirecoordinationwithothergovernmentdepartments.

•Third,thegovernmentshoulduse‘technologypush’policies–suchasR&Dtaxcredits–toalignAIinnovationpolicieswithitsmissions.Thiswillmeanlinkingthemmoreexplicitlytosolvingproblemsrelatedtodeliveringmissionsthaniscurrentlythecase.

•Fourthandcrucially,itshouldalsouse‘demandpull’policies–thosethat

establishamarketfornewinnovationswherecurrentlynoneexists.Outcomes-basedprocurementcanbeakeytoolforthis,thatgivesbusinessescertaintytoinvestandinnovate.Butthiswillrequireasignificantshiftfromthecurrentriskaverseapproachtoprocurementcurrentlyprevalentingovernment.

WhiletheUKgovernmentdoesalreadyusealltheaboveleverstosomeextent–viaInnovateUKforexample–itdoessowithoutsufficientstrategicdirection.Wearguethatthesecouldbefurtherleveraged,alongsidebroaderprocurement,fiscalandregulatoryincentives,tosteerAIdevelopmentanddeployment.

TableS1summarisesourrecommendationsandhighlightshowtheyconnectto

thegovernment’sAIOpportunitiesActionPlan(Clifford2025).

IPPR|ThedirectionofAIinnovationintheUKInsightsfromanewdatabaseandaroadmapforreform7

TABLES1

Wemakefourrecommendationstoacceleratemission-alignedAIdeployment

Recommendation

ConnectiontoAIOpportunities

ActionPlan

1)In-depthtrackingofAI

deploymentandAIimpact

scenarios,bynewAItrackingunit

Needtoclearlytrackwhat

typeofAIdeploymentis

occurringandwherethegapsare.

Overtime,developin-

depthscenariosforjobandbusinessimpacts.

Plancallsfortechnical

horizonscanningandmarketintelligence.

Callsforassessmentofskills

gapsanddevisingof“sufficientopportunitiesforworkersto

reskill.”

2)Breakmissionsdowninto

specificproblemstatements,ascross-departmentaleffort,ledbymissioncouncils

Breakdownthegovernment’smissions(suchashealth)

intospecificproblemareasthatneedsolving.

CallsforAItobecoreto

deliveringthegovernment’s

missions,bothinpublicservicedeliveryandtheeconomymorewidely.

“AppointinganAIleadforeachmission.”

Cross-governmentworktoidentifyusecasesandincentivisedeployment.

3)Technologypush:align

innovationpolicyclearlywithmissionstocreate‘technologypush’,byInnovateUKandBBB

ClearlylinksomeofInnovateUKandBBB’sfundingto

solvingmission-relatedproblems.

Startwithareaswhereproblemsareclearlyestablished.

Preferentialcomputeanddataaccessformission-aligned

innovators.

Mission-focussednationalAItenders.

ConnectAIpoliciestonewindustrialstrategy.

4)Demandpull:Usesubsidies,procurementandpreferential

financingforAIadoptionand

marketshaping,bypublic

procurementbyalldepartments,InnovateUKandBBB

Graduallyincreasemoreoutcomes-focussedAI

procurement,backedbyacentralfund.

CreateBBBfundingstream

thatincentivisesAIadoption.

Agileprocurement,“two-way

partnershipwithAIvendorsandstartups”.

“DriveAIadoptionacrossthewholecountry”withfocusonSMEs.

Source:Authors'analysis

8IPPR|ThedirectionofAIinnovationintheUKInsightsfromanewdatabaseandaroadmapforreform

1.

INTRODUCTION:AI

DEPLOYMENTNEEDS

NOTJUSTACCELERATION,BUTDIRECTION

Artificialintelligence(AI)technologiesareadvancingatarapidpace,andtheUK

governmenthasidentifiedAIasacrucialtoolfordrivingeconomicgrowth,enhancingpublicservices,andhelpingitdeliveritsmissions–suchasimprovingpublichealth.Thisagendaisreflectedinthegovernment’sAIOpportunitiesActionPlan(Clifford

2025).ItfocussesonremovingbarrierstoAIadoptionacrosstheeconomy–includingfosteringwidespreadadoptionbybusinesses–andithintsataligningAIinnovationwiththegovernment’smissions.

GenerativeAI,inparticular,hasthepotentialtohugelyimpacteconomyandsociety.Inawiderangeofcognitivetasks,leadingmodelshaveachievedundergraduateandPhDlevelreasoningskills(Jung2025).Inourpreviousstudy,wemodelledthat59percentoftasksintheeconomycouldbeimpactedbyexistinggenerativeAItechnology,ifcompaniesandpublicsectororganisationsweretobuildtheirprocessesaroundit(JungandSrinivasaDesikan2024).

Wethereforeseeenormouspotentialincutting-edgeAI,butsteeringthedirectionofitsapplicationwillbecrucial.ThereisariskthatmerelyacceleratingAIdeploymentwithoutsufficientdirectionmightfailtoimprovelivingstandardsanddeliverthe

government’smissions.

In2024,AIventurecapital(VC)investmentintheUKwascloseto$4billion.WhilethisisstillfarbehindtheUS–whichsawalmost20timesmoreVCinvestment–

theUKranksthird,afterChina(Dealroom.co2025).TheUKisalsoleadingEurope’sgenerativeAIpatents(thoughagainitisfarbehindChinaandtheUS,andbehindsomeEuropeancountriesonwiderR&Dmetrics)(CIIP2024)1UKscientistSirDemisHassabiswontheNobelPrizeinchemistryin2024forbreakthroughworkinAI.TheUKrankshighlyingenerativeAIresearchpublicationsanditsrenownedcomputerscienceuniversitydepartmentsalsoindicatehighpotential.Allthispointstothe

UK’sroleasanimportantAIinnovationhub.

Inthisreportwearguethat,buildingonthesefoundations,theUKcouldbecomeagloballeaderinpublicvaluecreatingAI.TheAIOpportunitiesActionPlan(Clifford2025),togetherwiththenewgovernment’sbroad-rangingvisiononmission-basedgovernment,couldboostgrowthanddeliverpublicvalue.Thisincludespriorityareassuchasimprovingpublichealthandhelpingdeliverabettertransportsystem.

However,currentlymuchofthepolicyfocusison‘accelerationism’–meaningmakingAIbetter,cheaperandwidelydeployed.‘AIsafety-ism’focussesonavoidingclearlydefinedrisks,nomatterhowadvancedorwhattypeofAIapplication.

1See:

/news/uk-tops-europe-ai-patents-un-study

IPPR|ThedirectionofAIinnovationintheUKInsightsfromanewdatabaseandaroadmapforreform9

WearguethattoachieveAIforpublicvaluecreation,athirdstrandofpolicyisneeded:‘directionism’.ThisistheideathatpolicycansteerthedirectionofAI

deploymentactively,usingpolicyincentives–suchastargetedfunding,publicprocurementorpublicinfrastructureaccess–forbuildingproductsandservicesthatcreatepublicvalue,expressedthoughgovernmentmissions(Jung2025;Blili-Hamelinetal2025).

TABLE1.1

PolicyshouldfocusmoreonshapingthedirectionofAIinnovation,aswellasaccelerationandriskmitigation

Goal

Policytools

Examples

Accelerationism

IncreaseAIdeploymentbymakingitbetter,

easierandcheapertouse

Givebusinessesand

peopleaccesstocapital,digitalinfrastructure

andtalent

UKAIOpportunitiesPlan,investments

inpublicsector

supercomputing

capabilities(UKDayOne2024)

Safety-ism

Avoidclearly

identifiedrisks

Safetytesting,privacysafeguards,anti-biasassurance

EUAIAct,AIsafety

institutes(egUK,US,Singapore)

Directionism

'Steer'innovationtowardssolving

importantsocietalproblems

Provideincentives

tobuildservicesand

researchthatexplicitlysolvessocietalproblems

Outlinespecificmissionsandmilestonesegin

preventativehealthorclimate

Source:authors

MEASURINGTHEDIRECTIONOFINNOVATIONANDIDENTIFYING‘DEPLOYMENTGAPS’

Inthisreport,weshowempiricallythatthereisacaseforpolicytosteerAI

deploymentmoreproactively.Wehighlightthatthereareinnovationareasthatcouldhavehighsocialreturnsbutthatcurrentlyreceiverelativelylittleattention.These‘AIdeploymentgaps’highlightthatpolicycanplayaroleinincentivisingmission-alignedinnovation.

Weanalysethelandscapeof‘AIorganisations’intheUK–3,200organisationsthathaveAIaspartoftheirvalueproposition.Todoso,wedevelopedafirst-of-its-kinddatabaseofAIfirmsoperatingintheUK,whichhasdetailedinformationonthe

typeofAIapplications,thesectorfocus,andthespecificvaluepropositionsofAIfirms.WedevelopedthisdatasetbybuildingonUKRIdataandaugmentingitwithlargescaleAI-enabledwebscraping(seeappendixforourmethodology).ThisisafirststeptomeasurethecurrentdirectionofUKAIinnovationandconsiderwhereAIdeploymentgapslie.

Inthenextsection,wepresentourkeyfindingsfromtheanalysisofthisdataset.Wethenconducttwodeepdivesintothehealthandtransportationsectors

andshowwhereAIinnovationmightcurrentlybefallingshortofhelpingthegovernment’smissions.Inourrecommendationsection,wehighlighthowUKinnovationpolicycouldbecomemoremissionaligned.

10IPPR|ThedirectionofAIinnovationintheUKInsightsfromanewdatabaseandaroadmapforreform

2.

KEYFINDINGSFROMOURNEWDATABASE

AIBUSINESSESFOCUSMAINLYONGENERALPROCESSIMPROVEMENTSRATHERTHANSPECIFICPROBLEMSOLVING

Inthissection,weinvestigatehownarrowlyfocussedfirms’valuepropositionsare.The‘mostspecific’applicationsarethosethatsolveaspecificprobleminaspecificsector(“usingAIfordampdetectioninhomes”,forexample).Theleastspecificonesarethosethatsolveageneralproblem(suchas“improvingbusinessprocesseswithAIanalytics”)andmarketthemselvestoawiderangeofsectors.

Wefindthat85percentofAIfirmsprovide‘general’AIsolutions.Theseare

valuepropositionsaimedatgeneralprocessimprovement–likeimproving

analytics,bettercustomerengagementorbetterproductdesign.Ontheone

hand,thiscanbeagoodthing,asAIisa“generalpurposetechnology”thatcan

haveamultitudeofapplications.Ontheotherhand,manyoftheapplicationsinourdatasetdescribefairlyabstractprocessimprovements,whichmaynotfullyrealisethetransformativepotentialofAIinsolvinghithertointractableproblems.Only15percentoforganisationsdevelopspecificsolutionsinspecificsectors,articulatinganarrowlydefinedvalueproposition.

Withregardstodeployment,wehypothesisethatsuchproblem-focussedAI

applicationscanhavemoretransformativepotential.Forinstance,DeepMind’s

AlphaFoldisahighlyspecialisedAIapplication,andisconsideredtohavea

transformativepotential.TheycreatedanAIsystemthatcanaccuratelypredict

aprotein’s3Dstructurefromjustitsaminoacidsequence,solvinga50-year

scientificchallenge.Itcouldbetransformativebecausebeingabletopredicta

protein’sstructureiscrucialforunderstandingdiseaseanddevelopingnewdrugs.

AIapplicationsthatarefocussedonsuch‘bottleneckproblems’canthereforehavehighpotentialtobetransformativeintheshortterm.SuchaproblemsolvingfocusalsoallowsustomoreclearlyassesswhattypeofprogressAIisdeliveringor,in

otherwords,whatthedirectionofAIinnovationis.ThedirectionofAIinnovationcanbesummarisedbytheproblemitisdeployedtosolve.

However,lessnarrowlyfocussedAIapplicationsthatleadtogradualprocess

improvementscanalsohavelargecumulativeimpactsovertime.Forinstance,

electricity’simpactonmanufacturingoccurredthroughgradualimprovementsthatultimatelyyieldeddramaticchange.Initially,factoriesmerelysubstitutedelectricmotorsforsteamengineswithminimalgain.Astechnologyevolved,machines

receiveddedicatedmotorsratherthanrelyingoncentralpowerdistribution.The

realbreakthroughcamewhenfactoriescompletelyredesignedtheirlayoutsaroundworkflowratherthanpowerrequirements,boostingproductivity(David1990).Suchinitialgradualchangemightbeginwiththe‘AIconsulting’companies–about18percentinourdataset–whichhelpbusinessesadoptAIintheirexistingprocesses.

IPPR|ThedirectionofAIinnovationintheUKInsightsfromanewdatabaseandaroadmapforreform11

FIGURE2.1

Eighty-fivepercentoffirmsareworkingongeneralapplications

Numberoffirms

3’500

3’000

NumberofAIfirms

2’500

2’000

1’500

1’000

500

0

AIconsulting

GeneralAIsolutions

GeneralAIsolutionsinspecificsectors

Specificsolutionsinspecificsectors

Count

Source:IPPRanalysisofUKRI(2024)augmentedviaRAGwebscraping

AIADOPTIONISFOCUSSEDONTHEKNOWLEDGEECONOMYANDPROCESSIMPROVEMENT

Wefinddeploymentactivityacrossallsectorsoftheeconomy,andacrossbusinesslines.Thissuggeststherecouldbewide-reachingapplicationofAIacrossthe

economyinthenearterm.ItalsoshowsthatthereissignificantinnovationdynamismintheUKandthattheadoptionphaseisclearlyunderway.

Ourfindingsinfigure2.2suggestthat70percentofAIinnovationisconcentratedin‘knowledgeeconomy’sectors.Thisincludesprofessionalservices,financial

services,andinformationandcommunication,aswellashealthandlifesciences.Thisisinlinewithourfindingfromourpreviousreport,wherewehighlighted

that‘backoffice’knowledgejobsaresignificantlymorelikelytobeimpactedbygenerativeAIthan‘frontoffice’,customerfacingandmanualjobs(JungandSrinivasaDesikan2024).

Nexttotheknowledgesectors,wholesaleandretailtradealsoseeasignificantamountofAIactivity.ButapplicationsherearenotprimarilyputtingAIinbrick-and-mortarshops.Instead,activitymainlyinvolvesconsultancyservicessuchasanalysingcustomerdataandprovidingsalesinsights.

Lookingatapplicationsacrossbusinessunits,wefindthatsoftwareengineeringseesthebiggestuseofAIinnovation.Inotherwords,AIisbeingusedasacodingassistant.ProductandR&Dapplicationsmightdeliverthemostvisibleshort-termtransformativechangesbyimprovingproducts–buttheyseeonly15percentofactivity.Thisisfollowedbycustomeroperations,marketingandsales.Insum,

thissuggestsAIinnovationislargelyfocussedonprocessimprovement:technical

12IPPR|ThedirectionofAIinnovationintheUKInsightsfromanewdatabaseandaroadmapforreform

efficiency(softwareengineeringandthesupplychain)andcustomerfocusedefficiency(marketingandsales,customeroperations,andthesupplychain).2

AnexampleofacompanyusingAIforsuchefficiency-focussedinnovationis

Synthesia,basedintheUK,whichaidscompanieswithtext-to-videocreation

andcommunication.ItisusedbymanyFortune100companiesforlearningand

development,marketing,andsalesenablement,amongothers(Benaich2024).Inourclassification,thisfallsunderboth‘marketingandsales’and‘customeroperations’.

FIGURE2.2

Nearly70percentoffirmsareintheknowledgeeconomyandhealthsectorsandonly18percentofapplicationsarein“productdevelopmentandR&D”

Numberoffirmsactiveinsectorandbusinessarea(firmscanbeactiveinmultiplefields)

Professional,scientificandtechnicalactivitiesHumanhealth,medicine,pharmaceuticalsFinancialandinsuranceactivities

InformationandcommunicationCommercialactivities,wholesaleandretailtrade

Government,publicadministration,socialwork

Marketsectors

andcompulsorysocialsecurityManufacturing

Education

Transportandstorage Arts,entertainmentandrecreationAdministrativeandsupportserviceactivities

Electricity,gas,steamandairconditioningsupply

Renewableenergy,environmentalprotectionandmitigatingclimateimpacts

Accommodationandfoodservices

Agriculture,forestryandfishing

Construction

Realestateactivities

Watersupply,sewerage,wastemanagementandremediationactivities

Marketingandsales

Customeroperations

MiningandquarryingDefense,policingandarmsmanufacturing

718

932

1,248

1,523

159

452

612

264

385

402

744

933

1,021

230

355

497

248

251

458

769

622

894

200

641

712

313

193

592

632

688

857

61

261

712

313

193

483

614

367

536

261

230

293

162

77

227

405

473

545

75

215

232

152

171

149

256

336

356

186

87

127

76

78

122

182

329

359

12

55

78

40

154

105

198

230

282

101

52

90

40

58

164

150

198

239

13

40

66

27

62

99

160

68

135

17

45

42

42

71

43

110

135

161

34

29

62

25

33

65

81

126

126

23

26

79

25

56

87

104

56

104

27

15

32

13

16

33

59

114

111

35

17

33

9

20

39

69

84

108

21

24

41

14

25

54

85

69

102

9

36

46

18

16

12

37

43

52

12

6

10

8

7

16

29

41

47

13

7

12

8

9

4

14

45

45

6

4

5

3

2

ProductandR&D

Softwareengineering

Supplychain

Riskandlegal

Strategyandfinance

CorporateIT

Talentandorganisation

1,400

1,200

1,000

800

600

400

200

Business

Source:IPPRanalysisofUKRI(2024)augmentedviaRAGwebscraping

2InJungandSrinivasaDesikan(2024)wefoundthatthemajorityoftasksinthesejobscouldbe

significantlyaidedbygenerativeAI.Thisisthereforeanareawherefurthergrowthmightbeexpected.

IPPR|ThedirectionofAIinnovationintheUKInsightsfromanewdatabaseandaroadmapforreform13

AIfirmsinourdatasetareprimarilyfocussedonprovidingservicesoverresearch(90percentservicesversus10percentresearchfocus).Thehealthcareand

educationsectorshavethehighestproportionofresearch-focussedfirms.Intermsofcustomers,mostAIfirmsselltheirproducttootherbusinesses:about

59percentoffirmsaretargetingbusinesses,aboutaquarterareaimedatgovernmentcustomers,andconsumer-focussedapplicationsmakeupabout

15percent.

Intheoverallsample,22percentofthefirmsreceivedsometypeofpublicfunds