2025年翻译技术洞察报告 Translation Technology Insights 2025 Helping you navigate change with clarity and confidence

Translation

Technology

Insights2025.

Helpingyounavigatechangewithclarityandconfidence

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TranslationTechnologyInsights2025

Contents.

Introduction 3

Keytrendstowatch 5

Shrinkingmarkets?Ortemporaryupheaval? 6

Alintranslationtoday 10

Alintranslationtomorrow 15

Thewayforwardlessonsfromthepast 18

Thewayforwardnewopportunities 25

Roundupofotherresults 3

Nextstepsfortheindustr- 43

TranslationTechnologyInsights2025

Welcometotheneweraoflocalization

InthisfourtheditionofourTranslationTechnologyInsights(TTI)report,weexplorehowtechnologyisreshapingthetranslationindustryandwhatthefuturemayhold.

OurpreviousreportwasbasedondatagatheredbeforethereleaseofChatGPTinlate2022-amomentthatmarkedthebeginningofaseismicshift.Atthattime,generativeAI(GenAl)andlargelanguagemodels(LLMs)weren'tpartoftheconversation.Now,theydominateit.

Thisyear'sTTIsurveyincludedquestionsaboutLLMsandusecasesforAlbeyond

machinetranslation(MT)forthefirsttime.Asaresult,thisreportfocuseslargelyonAl.ItmayonlybethreeyearssinceGenAl'sarrival,buttheimpacthasbeenlargeandrapid,makingthisacrucialmomenttoassesshowwelltheindustryisadapting.

Aswe'llsee,languageserviceproviders(LSPs)andfreelancersarefeelingtheimpact

-andnotinagoodway.Butwebelievethisdisruptionistemporaryandthatthereare

plentyofopportunitiesfortranslationprofessionalstothriveinanindustryreshapedbyAl.LessonslearnedfromMTstillremainrelevant,andforallthestrengthsofLLMs,wetrulybelievethatthefutureoftranslationliesinhuman-Alpartnerships.

Importantly,industrystakeholders-especiallyLSPs-arenotsimplyhidingtheirheadsinthesand.MTusageisatanall-timehighandaconsiderablenumberofearlyadoptersarealreadyexploringLLMs.Almostthree-quartersofrespondentsareconsideringinvestinginAlcapabilities.

Ifactedon,theseintentionscanbetransformative,

helpingprofessionalsestablishthemselvesastrustedauthoritiesonthebenefitsandrisksofAlinlocalization.Asexperts,theycan

advisecustomersandbecometheirpreferredpartnersforAl-poweredlanguageservices.

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TranslationTechnologyInsights2025

Meetoursurveyaudience

Justunder2,000translationindustryprofessionals,from109countries,completedanonlinesurveytoproducetheseresults.We’dliketothankeveryonewhotookthetimetodoso.

1,946respondents

Americas

15%

Europe

58%

APAC

22%

Restofworld

5%

Geographicdistributionofsurveyrespondents

Forthefirsttime,we’redividingtherespondentsintofourgroups(insteadofthree)basedon

whotheyworkfor.We’vealwaysdistinguished

freelancersfromLSPsandcorporates.Thistime,toreflectthespecificneedsofthoseworking

inthepublicsector,we’veseparatedthemoutfromthecorporategroup.Thefourgroupsare:

•Freelance:individualtranslatororcontractorwithatranslation/localization-relatedrole

•LSP:anyoneworkingatatranslation/localizationagency

•Publicsector:workinginagovernmentinstitutionorsimilar,inarolewithsomeresponsibilityfortranslation/localization

•Corporate:workinginanyotherbusiness,inarolewithsomeresponsibilityfor

translation/localization

Respondentgroups

Publicsector

5%

LSP

10%

Corporate

Freelance

67%

18%

TranslationTechnologyInsights2025

Everynumbertellsastory:

Keytrendstowatch

Herearesomekeystatisticsthatrevealhowthetranslationindustryisevolving.Thepaceisfast,theoutlookuncertain-butforthosereadytoadapt,theopportunitiesareclear.

offreelancersandLSPs

reportadropincustomer

demand-signalinga

majorshiftinhowwork

isbeingsourced

anddelivered.

60%

machinetranslation(MT)-rising

to80%amongLSPs,making

itthemostwidelyadopted

translationtechnology

intheindustry.

ofrespondentsnowuse

areconsideringinvesting inAlcapabilities-withLSPsleadingthecharge.

plantoinvestinAlfor

qualityassurance,making

itthetoppriorityforfuture

Alinvestmentacrossall

respondentgroups.

citelackofbudgetasthe

topblockertoimproving

workflows,aclearsignthat

financialpressureisholding

backinnovation.

TranslationTechnologyInsights2025

Shrinkingmarket?Ortemporaryupheaval?

ThefirstthreeTTIreportsrevealedapatternofsustainedorincreasingpressureofworkwithintheindustry,especiallyintermsofnumbersofcustomers,projectsize(wordsperproject)andnumberoffilesperproject.EvenCOVID-19didn't

reversethisoverallpattern.Thistime,however,we'reseeingsomedramaticreversalsinthepressuresexperiencedbyrespondents.

DisruptionforfreelancersandLSPs

Moststrikingly,43%reportadecreaseinnumberofcustomersrequestingworkintheprevious12months,almostdoubletheproportionwhoreportedadecreaseincustomersin2023(22%)and2020(23%).

Importantly,thissharpbreakfrompreviousyearsisdrivenalmostentirelybytheexperienceoffreelancersandLSPs.Inboth2020and2023,70%ormoreofboththesegroupssawstableorincreasingcustomernumbers.In2025,

thishasdroppedtojust44%offreelancersand46%ofLSPs.Morethanhalfoffreelancers(51%)andalmosthalfofLSPs(46%)nowreportfewercustomers-morethandoubletheirratesin2023.

Noobviouschangeindemandfromthesource

InstarkcontrasttofreelancersandLSPs,aroundthree-quartersofcorporate

andpublic-sectorrespondents(74%and76%,respectively)arestillexperiencingstableorincreasingnumbersofcustomersrequestingwork,

withonlysmallproportionsseeingdecliningcustomer

numbers.Sowecansafelyassumethattheir

internalcustomers-thebusinessunits

wantingtranslation-stillhavethe

sameneeds.Butlessofthiswork

seemstobemakingitswaytoLSPsandfreelancers.

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TranslationTechnologyInsights2025

Numberofcustomersrequestingworkintheprioryear(%)

Don’tknowDecreasedStayedthesameIncreased

Freelance

2020

2023

2025

LSP

2020

2023

2025

70%

426

4327

70%

525

39

31

44%

28

16

51

5

70%

29

22

41

8

72%

622

38

34

46%

8

46

19

27

Corporate

2020

2023

2025

10104733

7124437

74%

719

30

44

Publicsector

2025

76%

915

40

36

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TranslationTechnologyInsights2025

Thewiderpicture

IndustryfiguresreportedintheSlator2025LanguageIndustryMarketReportareinlinewiththesefindings.Slatorreportsthatin2024,theoverallmarket

contractedby2%,drivenmainlybyadeclineinspendontraditionallanguageservicesthatmakeupthebulkoftheindustry.Breakingthisdownforlanguagesolutionintegrators(LSls)-whatwewouldcalltechnology-enabledLSPs-andlanguagetechnologyproviders(LTPs),weseeabigdifference:

·LSlssawa3%dropinrevenue

·LTPssawa12%growthinrevenue

Thesecontrastingfortunessuggestthatcustomersarereallocatingbudgetsawayfromhuman-deliveredservicesandtowardautomation,explainingtheriseinfreelancersandLSPsreportingfewercustomersrequestingwork.

'NotethatSlatorhasnowexpandeditsindustrydefinition,sothesefiguresareforitslegacyindustrydefinitioncoveringtraditionaltranslation,localizationandinterpretingservices,alongwithcoretechnologyplatformsusedtosupportthem.

TranslationTechnologyInsights2025

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Otherworkpressures

39%offreelancetranslatorshave

seenadecrease

inthenumberof

wordsperproject.

MostoftheotherdemandfactorsthattheTTIasksabouthavealsoseenasurprisingjumpinthosereportinga

decreaseover12months(aftersteadyfiguresbefore).

Butformostofthese,theoverallnumbersaregenerallysmall,soevenjumpsofdoubleormoredon’tamounttoaclearsignal.Curiously,thosereportingadecreasein

numberofwordsperprojectareupfrom20%to33%,

promptingustoask:isitplausiblethatprojectsizewouldbeaffectedbywhateveriscausingfewercustomersto

turntoLSPsandfreelancers?

Butfirstweneedtodigintothatcauseandaskwhetherit’stemporaryorpermanent.Almostwithoutexception,thereasongivenbyresearcherssuchasSlatorandby

themanydifferentindustrystakeholdersthatweengagewithis:GenAI.

No.ofcustomersrequestingwork

No.ofwordsperproject(projectsize)

Outsourcingneededtocompleteaproject

Variety/typesofsourcecontent

Varietyoffiletypes

50%

25%

5%

Thoseexperiencingadecreaseineachfactorintheprioryear(%)

22

20

11

9

10

6

43

33

23

22

16

15

12

7

6

202020232025

TranslationTechnologyInsights2025

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AIintranslationtoday

ManyoftheLSPswetalktotellusthey’reonthedefensive,havingtojustify

theirratesandvalueagainst‘AIshops’.ButsomealsohavetalesofcustomerswhoreplacedtheirserviceswithLLM-poweredtranslation,onlytoreturna

fewmonthslaterafterrealizingtheystillneedexpertlinguisticandproject

managementsupport.Whenwetalktocorporatetranslationteams,wehearthattheytooneedtojustifyhumaninvolvementintranslation.Theirinternalcustomerswanttoknowwhytheycan’tjustuseanLLMsuchasChatGPT

totranslateeverything.

Theoptimisticview–whichweourselvesholdandwillargueforlater–isthatthefighttoprovethevalueofhumaninputwillultimatelybewon,justasithasinthefaceofever-improvingmachinetranslation(MT).Butfirst,let’slookatAIadoptionandusewithintheindustry.

Oneofthethingswe’re

beingapproachedwithand

havingtodealwithistheidea

thatsomepeopleintheirminds

believethatLLMscandoeverything.

...There’snolongeraneedfora

translationteamandwecanbasically

geteverythingbackimmediately,right?

ScottCahoon

SolutionsArchitectatDellEMC

SpeakingatElevate2025

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TranslationTechnologyInsights2025

CurrentMTandLLMadoption

Across10yearsandfourTTIsurveys,useofMThasgrownfrom40%to60%,

withLSPsalwaysleadingtheway(50%to80%).Ofallthetechnologytypesweaskaboutinthesurvey,it'stheonlyonethathasseensustainedgrowth.CATusehasremainedprettyconstantandothertechusehasfluctuatedupanddown,butwithnocleartrends.

Wediscussedtheroleoftranslationtechnologyinour2023TTIreport,inthecontextofgrowingdemandinanunder-resourcedindustry.Thebigquestionnowis:whatdoesGenAlmeanforthispicture?Willittakealltheworkaway,wipingoutourindustryasthemeteordidthedinosaurs?Orisit(just)amajornewtoolthatwillchangetheindustryinwaysthatwecanperhapsanticipateandrespondto?

The2025TTIgivesusourfirstviewofLLMuseintheindustry.Oncemore,

LSPsareaheadofthecurve,with39%ofthemusingit(against22%overalluse).JustthreeyearsafterChatGPT'slaunch,thesearepromisingnumbersforearlyadoptersexploringthenewtechnology.80%oftheseearlyadoptersarealso

usersofMT.

TranslationTechnologyInsights2025

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Useoftechnologyinthetranslationindustrytoday

Machinetranslation(MT)

Terminologymanagement

Collaborationtoolsthatallow

userstosharetranslationassets

Translationmanagementsystem(TMS)

Largelanguagemodel(LLM)

Softwarelocalizationtools

Translationbusinessmanagement(incl.billing/invoicing)software

Integrationsandconnectorstocontentrepositories

Other

Computer-assistedtranslation(CAT)

Public

TotalFreelanceLSPCorporatesector

58%

80%

57%

53%

81%83%92%71%69%

60%

50%

70%

44%

50%

48%

48%

62%

38%

34%

42%

23%

55%

34%

21%

28%

39%

29%

18%

18%

22%

14%

31%

23%

12%

17%

8%

5%

38%

10%

11%

24%

3%

11%

6%

7%

0%

2%

1%

0%

Noneoftheabove

UseofMT(%)

75%

Total

FreelanceLSP

Corporate

Publicsector

50%

25%

2%

6%

7%

0%

4%

10%

54

50

80

68

60

58

57

65

53

51

49

43

41

40

39

39

2016202020232025

TranslationTechnologyInsights2025

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UsecasesforAIintranslationworkflows

Weaskedallrespondentsusingtranslationtechnologywhetherthey,ortheirorganization,areapplyingAItotasksthatweknowitcannowhandle.Unsurprisingly,thetopuseisforautomatingtranslations.Butonly35%saythey’reusingAIinthisway–surprisinglylow,

givenhowwidespreadmachinetranslationisacrosstheindustry.

Thislikelyreflectsabroaderissue:manyrespondentsmaynotrecognizeMTasaformofAI,eventhoughnearlyallmodernMTsystemsarepoweredbyAI.Ifthisistrue,thenit’slikelythatotherAI-drivenfeatures—suchasrefinement,qualityassurance,orterminologyextraction—arealsobeingoverlookedormisunderstood.

Thispointstoacriticalneedforbettereducationandclearercommunication—bothwithin

theindustryandfromtechnologyproviders—abouthowAIisalreadyembeddedinthetoolsprofessionalsuseeveryday,andhowitcanbeeffectivelyleveraged.

AIusecasestoday

Automatingtranslation

EnhancingQA(e.g.,errordetectionorconsistencychecks)

Refiningorimprovingtranslations

23%

10%

8%

10%

WedonotuseanyAI

availableinoursoftware

Managingterminology(e.g.,automatedtermextractionorsuggestions)

Findinghelporsupport

Optimizingworkflows(e.g.,automatedfilehandling,taskassignment)

Recommendingresources

(e.g.,TMs,glossariesorMTengines)

Generatinganalyticsorinsightsabouttranslationperformance

Categorizingortaggingcontent

Don’tknow

8%

OursoftwaredoesnotofferAIcapabilities

Public

TotalFreelanceLSPCorporatesector

35%

39%

38%

31%

34%

27%

33%

25%

20%

27%

25%

27%

25%

20%

22%

12%

10%

4%

30%

18%

13%

8%

23%

13%

11%

5%

16%

13%

10%

4%

23%

11%

8%

5%

22%

12%

13%

4%

16%

6%

9%

13%

25%

24%

23%

12%

8%

10%

6%

3%

13%

8%

7%

10%

11%

TranslationTechnologyInsights2025

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Asexpected,LSPsreporthigherlevelsofAIadoptionthantheothergroups,particularlyformanagingterminology,optimizingworkflows,generatinginsightsandcategorizing

content.However,onlythetopfewusecaseshavegreateradoptionthantheproportionofrespondentswhosaytheyaren’tusinganyAIcapabilitiesavailableintheirsoftware.

Thismaypartlybebecausemosttranslationsoftwaresimplydoesn’t(yet)supportmostoftheseadvancedAIusecases.Ifthefunctionalityisn’tavailable,userscan’tadoptit–nomatterhowinterestedtheyare.It’sareminderthatAIadoptiondependsnotjustonuserreadiness,butonplatformmaturity.Formostusecasesbeyondautomatedtranslation,

it’sstillearlydaysforbothtechnologydevelopersandtheirusers.

AsplatformsevolveandembedmoreAI-drivenfeatures,weexpectadoptiontorise

–butonlyifvendorsclearlycommunicatethesecapabilitiesandusersunderstandhowtoapplythemeffectively.

Isbudgetpressureaffectingprojectsize?

Earlierinthisreport,wequestionedwhatmightbedrivingthetrendtoward

smallerprojectsizes.Oneclearfactorisfinancialpressure.Ourdatashowsthatcorporatebudgetsareflatyear-on-year,and23%ofpublic-sectorrespondentsreporthavingnodedicatedlocalizationbudgetatall.Atthesametime,the

volumeofcontentbeingproducedcontinuestogrow,whilethedemandforcontentinlocallanguagesremainsstrong.

Thiscreatesachallengingdynamic:organizationsareexpectedtodomorewiththesame,orevenfewer,resources.Fromourconversationswithcustomers,it’sclearthatmanyareincreasinglyrelyingonautomationtomaketheirbudgetsgofurther.Ratherthanoutsourcingentireprojects,manyareusinginternaltoolstohandleasmuchofthetranslationprocessaspossibleandonlysendingthemostcomplexorhigh-riskcontenttoLSPsorfreelancers.

Increasingly,thisapproachissupportedbyAItoolsthatcanevaluatethequalityofmachine-generatedtranslationsandapplyautomaticpost-editingtoimprovethem.Thesetoolshelporganizationstriagecontent,identifyingwhichsegmentstrulyrequirehumaninputandrefiningtherestautomatically.Theresultisamoreselectiveoutsourcingmodel,whereonlythecontentthatAIcan’tconfidently

handleispassedonforhumanreview—potentiallycontributingtosmallerprojectsizes.

Whilethedatadoesn’tconfirmthisdirectly,itreflectsaplausibleandgrowingtrend.We’llbewatchingcloselytoseehowthisevolvesinfuturewavesoftheresearchandinindustryconversations.

TranslationTechnologyInsights2025

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AIintranslationtomorrow

ItmaystillbeveryearlydaysforAI(withtheexceptionofMT),butthefocusonitis

intenseandalmostthree-quarters(72%)oftherespondentsareconsideringinvestinginAIcapabilities.

Plansfornextinvestments

WhenaskedtoselectuptothreeusecasesforfutureAIinvestment,46%ofrespondentschoseenhancingqualityassurance,makingitthetoppriority.Otherpopularchoices

includedmanagingterminology(36%),refiningtranslations(35%),andautomating

translation(34%).Meanwhile,28%saidtheycurrentlyhavenoplanstoinvestinAIatall.

Buttheseoverallfiguresareheavilyshapedbyfreelancers,thelargestgroupand

generallytheslowesttoadoptnewtechnologies.InvestmentisfarmorelikelyforLSPs,corporatesandpublic-sectorrespondents–especiallyLSPs(only10%ofthemhave

noplanstoinvestinAI).

PrioritiesforinvestinginAI

EnhancingQA(e.g.,errordetectionorconsistencychecks)

Managingterminology(e.g.,automatedtermextractionorsuggestions)

RefiningorimprovingtranslationsAutomatingtranslation

28%

I/wedonotplantoinvestinAIcapabilities

Optimizingworkflows(e.g.,automatedfilehandling,taskassignment)

Recommendingresources(e.g.,TMs,glossariesorMTengines)

Generatinganalyticsorinsightsabouttranslationperformance

Findinghelporsupport

Categorizingortaggingcontent

Other

Public

TotalFreelanceLSPCorporatesector

46%

60%

51%

48%

42%

36%

37%

46%

46%

34%

35%

35%

45%

35%

33%

34%

48%

39%

46%

10%

17%

14%

28%

34%

25%

24%

16%

24%

11%

12%

12%

9%

22%

12%

10%

11%

15%

10%

8%

7%

5%

4%

7%

8%

4%

3%

4%

5%

3%

1%

1%

1%

0%

1%

TranslationTechnologyInsights2025

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Comingatfutureinvestmentfromanotherangle,The

TTIsurveyaskedrespondentstochooseuptothree

categoriesoftranslationsoftwarethey’renotcurrently

using–identifyingthenextstepintheirmaturityjourney.

Becausethequestionfocusesontoolsrespondents

aren’talreadyusing,foundationaltechnologiesoftenrankhighly.Forexample,whileonly19%ofrespondentsdon’tcurrentlyuseCATtools,it’sanaturalstartingpointfor

thatgroup—soit’sfrequentlyselected.

Inthe2023TTIreport,themostcommonchoiceswereCAT,terminologymanagementandcollaborationtools(withsomedifferencesinrankingforfreelancers,LSPsandcorporates).Thistime,however,theemergenceofLLMsasanewoptionforallgroups(exceptfreelancers),andtherisinginterestinmachinetranslation,highlight

justhowcentralAIhasbecometotheindustry’sfuture.

Businessfactorsdrivingtechnologyinvestment

Thesurveyalsoasksaboutanumberofbusinessfactorsthatmightdrivetherespondentsortheirorganizations

towardstheadoptionoftranslationsoftwareinthe

next12months.Inpreviousyears,thetopthreeoverall(withsomevariationbygroup),haveconsistentlybeentomaintain/improvequality,improveprocessesand

manageincreasingdemand.

Butthistime,anewfactorhasemerged-‘newtypes

ofsoftware’nowranksthirdoverallandisamongthe

topthreeforeverygroup.AmongLSPs,iteventakesthetopspot.ThisshiftlikelyreflectsthegrowinginfluenceofgenerativeAI,whichhasintroducedawaveofnewtoolsandcapabilitiesacrosstheindustry.AsGenAIcontinuestoreshapeexpectationsaroundwhattranslation

technologycando,it’snosurprisethatrespondentsareincreasinglycitingtheavailabilityofnewsoftwareasakeydriverforinvestment.

Meanwhile,managingincreasingdemandhasslippedoutofthetopthreeoverall–fallingtofifthforboth

freelancersandLSPs.Itremainsapriorityinthepublicsectorandhasjustdroppedtofourthforcorporates.ThisfitswithourearlierfindingthatmorefreelancersandLSPsareseeingdecreasingcustomernumbers,whilecorporateandpublic-sectorrespondentsaren’t.

Topthreechoicesfornextstepintranslationmaturityjourney

Freelance

•CAT(38%)

•Terminologymanagement(32%)

•Machinetranslation(27%)

LSP

•LLM(58%)

•Machinetranslation(45%)

•CAT(41%)

Corporate

•Machinetranslation(43%)

•LLM(39%)

•Terminologymanagement(39%)

Publicsector

•LLM(51%)

•Machinetranslation(50%)

•CAT(45%)

TranslationTechnologyInsights2025

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Factorsdrivingtheadoptionoftranslationsoftwareinthenext12months(%)

TotalFreelanceLSPCorporatePublicsector

Maintain/improvetranslationquality

4142344539

Improvetranslationandbusinessprocesses

3633454132

Newtypesofsoftwareavailableonthemarket(e.g.AIcapabilities,cloud-basedCATtools)

3432493537

Bettermanageincreasingdemandfortranslations

2724273439

Improvecustomersatisfaction

2828272526

Budgetconstraints–needingtoswitchtolowercostalternativesinthemarket

2220342218

Bettermanageagrowingtranslationworkforce

109131313

Don’tknow

16

18

10

13

19

Other

44335

TranslationTechnologyInsights2025

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Thewayforward:lessonsfromthepast

CurrentAIadoptionandplansforinvestment

tellusclearlythatAIisabigfocus,butnotwhy.Areindustrystakeholdersfeelingpressurefromtheircustomerstouseit?Dotheyseeinherentadvantageinaddingthesecapabilitiestotheirtoolkit?Aretheysimplyexploringitbecause

that’swhatyoudowhensomethingnewand

potentiallyuseful(orthreatening)comesalong?

ThetruthisthatallofthesearedrivingadoptionofAI,althoughit’sslightlydifferentforMTand

LLMsbecausetheformerisamuchbetterunderstoodtoolacrosstheindustry.

Ultimately,thedevelopmentofNMThascreatedthejobofpost-editing,expandedtheproportionofcontentthatbusinessescantranslateandthenumberoflanguagestheytarget,andallowed

adaptableprofessionalstofocusonaspects

oftranslationthatdemandhumaninsightand

creativity.EvenbeforeLLMsenteredthepicture,automatedtranslationhadn’treducedhuman

involvementintranslation.

Unlessthere’ssomethingfundamentally

differentaboutGenAI,it’splausiblethatLLMs

willultimatelyhaveasimilareffectontheindustry.

LessonsfromMT

Let’snotforgetthat,whileadaptingtoMThasattimes(especiallyinitsearlydays)beenpainful

forsomeintheindustry,ultimatelygrowthhas

continuedevenasMThasbecomeevermore

capable.Ratherthankillingofftheindustry,the

developmentofneuralmachinetranslation(NMT)

-themostrecentandwidelyadoptedform-

hashelpedfreeuptimeandbudget,enablingabroaderscopeforbusinesstranslation.

Importantly,MThasalsobecomeeasiertouse,thankstolanguagetechnologyproviderswhohaveintegrateditseamlesslyintotranslation

platformsandworkflows,allowingusersto

orchestratetheirAIusagewithgreatercontrolandefficiency.

Asadoptionhasincreased,theindustryhas

cometounderstandthatnotallcontentis

suitableforMTalone.Organizations,along

withtheirLSPs,havelearnedtodistinguish

whatcanbefullyhandledbyNMT–especiallywhenusingadaptablemodelsincombination

withtranslationmemoriesandtermbases–andwhatstillrequirespost-editingorotherforms

ofhumaninput.

Everybody

thathasbeen

involvedinmachine

translation–starting

fromstatisticalto

neuralnetworksand

thenmovingtolarge

languagemodels–

hasactuallyacquired

alotofexpertiseinhowtodeployAIsolutions

atscale.Let’snotforgetthat.

LoïcDufresnedeVirel

HeadoflocalizationatIntel

FromtheGloballySpeakingpodcast,episode145

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TranslationTechnologyInsights2025

AreLLMssodifferent?

There'sdefinitelysomethingaboutanLLM's

conversationalfluencyand'breadthof

knowledge'-spanningcodingtopoetry-

thatmakesGenAlfeeldifferentfromearlier

Almodels.Somethingaboutitscreativitythat

givesnewlifetothebeliefthatanydaynowAl

translationwillroutinelymatchthebestofhumanefforts,andthetranslationindustrywillbedone.

Isit,then,asignofdoomthatfreelancersandLSPsarelosingcustomerstoAlsolutions?Orjustthepainthatweknowwehaveto

gothroughbeforetheindustrysettlesintoanewequilibrium?

Remember,too,howrapidlyhumanlanguage

andcultureevolve.Thiswillalwayslimithow

quickly(ifatall)continuingAldevelopmentcanmatchhumantranslation.Withoutnewhumansourcesofcontentandcontinualfine-tuningtokeeppacewithchange,Aloutputwillrapidlylosetouchwithreality.Thisisoneofthereasonswhywebelievethatthefutureoftranslationprobablyremainsoneofhuman-Alpartnership.

Thefactthatwe’realreadyhearingabout

customersreturningafterunsatisfactoryAl-onlyexperiencessuggeststhatit'sthelatter.We're

alsospeakingtomanybusinessesthatsee

clearlythat,foralltheirstrengths,LLMsaren't

reliableenoughtoreplacehumansentirelywhentranslatingmanytypesofcontent.Andthey

generallybelievethat,despitethepaceofAldevelopment,that'su