2026年数据与智能赋能集体优势：终结全球供应链中的强迫劳动白皮书（英文版）-

Harnessing

Data

andIntelligenceforCollectiveAdvantage:

Ending

ForcedLabour

inGlobalSupply

ChainsW

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6Images:AdobeStockContentsForeword

3Executivesummary

41

The

problem:Theviciouscycleofforced

labouranddatafragmentation51.1Persistenceamid

progress:Theenduring

natureofforced

labour51.2Thestructuralrootsoffragmentation:

Data,incentives,trust6andgovernancegaps1.3Breakingthevicious

cycle92

Thesolution:TheGlobal

Data

PartnershipAgainst

Forced

Labour10asa

new

modelforcollective

impact2.1Asystem-level

responsetoasystemicchallenge102.2Thetheoryofchange112.3WhyfederateddataandagenticAIaregame

changers132.4Proofof

Concept

inThailand152.5Stakeholdervalueandcollectiveadvantage182.6Summaryofthesolution193

Thefuture:

From

prooftoglobal

impact203.1Minimumviableproduct:Scaling

beyondthe20ProofofConcept3.2Trust

bydesign:Governance,

risksandenabling21conditionsforscale3.3Buildingglobalmomentum

andvisionfor

203022Conclusion

23Contributors24Endnotes

26DisclaimerThisdocumentis

published

bytheWorld

Economic

Forumasacontributionto

a

project,

insight

area

or

interaction.Thefindings,interpretationsandconclusionsexpressedherein

are

a

resultofacollaborativeprocessfacilitated

andendorsedbytheWorld

Economic

Forumbutwhoseresultsdo

not

necessarilyrepresenttheviewsoftheWorld

EconomicForum,nor

the

entirety

of

its

Members,Partnersorother

stakeholders.©2026World

Economic

Forum.All

rightsreserved.

No

part

of

this

publication

maybereproducedortransmitted

in

anyformorbyany

means,

including

photocopyingandrecording,or

by

any

informationstorage

and

retrieval

system.Harnessing

Dataand

IntelligenceforCollectiveAdvantage:EndingForcedLabour

inGlobal

Supply

Chains2At

itscore,the

Partnership

usesafederateddata

modelandagenticAIand

provides

anintelligence

layerthatconnectsfragmenteddata

without

requiring

itto

be

movedorcentralized.Thisdesign

makescollaborationtechnicallyfeasible,ethicallysoundand

rights-based

by

design.Trust

is

builtthroughtransparency,accountabilityand

inclusion,ensuringthatdata

serves

prevention,

remedyandaccountability.Thiswhite

paper

presentstheearlyfindingsandlessonsfromthework.

It

highlightsthe

persistentbarriersthat

makeforced

labourdifficulttodetectand

measure,the

innovativeapproaches

beingdevelopedtoconnectdatasafelyand

effectively,

and

theopportunitiestoscalethis

modelglobally

inthe

yearsahead.TheThailand

ProofofConcept

(POC)

indicatesthatthis

modelcan

be

implementedsafely

andeffectively,andthat

participantsachievegreater

impactwhenworkingtogetherratherthanalone.Endingforced

labourwill

require

leadership,collaborationandcourageequaltothe

scale

ofthe

challenge.Asthe

Partnershipadvancestowards

its

2026development

phase,we

inviteallstakeholders

to

participate,

learnandact.

Byconnectinginsightssecurely,applyingshared

intelligenceand

demonstrating

measurable

progress,wecan

make

forced

laboura

preventable

riskratherthan

anenduring

reality.Forced

labour

remainsoneoftheworld’s

mostpersistentandsystemic

labour

rightschallengesembeddedacrossglobalsupply

chains

andsocieties.Governments,

businesses,trade

unions

andcivilsocietyorganizations

have

invested

heavily

inaddressing

it,yet

progress

hasstalled

because

ourcollective

response

has

notyet

beensystemic

enough.

Despitevasteffortand

regulation,thedata

remainsfragmented,

incentives

misalignedandtrustscarce.Noneofthis

is

inevitable.Agrowingcommunityofpartners

has

begunworkingtogether

underthe

Global

Data

PartnershipAgainst

Forced

Labourtoaddressthischallengethrougha

new

model

of

collaboration.The

Partnership

representsatrusted,

precompetitive

infrastructureforcoordinatedglobal

action.

Itconnects

insightssecurelyacross

public,

privateandcivilsocietysystems

without

requiringanystakeholdertosurrendercontrol

oftheir

dataorsovereignty.

Partnerscollaboratesafely,

linkingexistingsystemsthroughsharedgovernanceandprivacy-preservingtechnologies

ratherthancreating

anothercentraldatabase.TheGlobal

Data

PartnershipAgainst

ForcedLabourseeksto

buildtheconditionsfortrust,interoperabilityandsharedaccountability,demonstratingthatsecuredatacollaboration

isbothtechnicallyfeasibleand

institutionally

possible.HarnessingDataandIntelligenceforCollectiveAdvantage:

Ending

Forced

Labour

inGlobalSupplyChainsForewordJohn

F.SchultzExecutive

Vice-President,

ChiefOperatingandLegalOfficer,

HewlettPackard

EnterpriseHarnessing

Dataand

IntelligenceforCollectiveAdvantage:EndingForcedLabour

inGlobal

Supply

Chains3Maroun

KairouzManaging

Director,World

Economic

ForumJanuary2026Forced

labour

isasystemicglobal

challengethatdemandssystemicaction.

Despitedecadesofreform,compliance

initiatives,advocacy

andcorporateduediligence,

nearly28

million

peopleremaintrapped

incoercivework,acrosssectorsand

borders.1

Thecausesarewell

known,yetprogress

hasstalled

becausetheecosystem

itselfis

fragmented:data

issiloed,

incentivesare

misaligned

andtrust

is

inshortsupply.Governments,businessesandcivilsocietyeach

collect

important

information,

butthesedatasets

rarelyconnect.Worker-generated

insights,whileamongthe

most

immediatesourcesofevidence,are

oftenthe

least

integrated

into

broadersystems.The

result

isaviciouscycle:

limitedvisibilityweakensaccountability,weakaccountabilityerodestrustand

mistrust

preventscollaboration.Understandingwhereandwhyexploitationoccurs

remainsdifficult

because

information

isscattered,

incentivestoshareare

unevenand

collaboration

oftencarries

risk.2

Withouttrustedmechanismstoconnectandverifydataacross

stakeholders,

visibilitystays

partialandcollectiveaction

limited.TheGlobal

Data

PartnershipAgainst

Forced

Labour

wascreatedto

breakthiscycle.

Launched

in2025,

it

providesatrusted,

precompetitive

infrastructurethatenablesgovernments,companies,

international

organizationsandcivilsocietygroupsto

collaborate

securelywithouttransferring,centralizingorgivingupthesovereigntyofunderlying

data.

Built

on

afederated

model,the

Partnership

linksexistingsystemsthroughsharedstandardsandgovernance

protocols,allowingparticipantstogeneratecollective

intelligencewhile

retainingcontroloftheir

owndata.

FederationandagenticAIsit

at

the

core

ofthisarchitecture,enablinganalysiswherethe

data

residesand

linkingsignalsfromvarioussources,suchasworkergrievances,

labour

inspections,recruitment

recordsand

migrationflows,touncover

riskpatterns

invisibletotraditionaltraceability.Startingwitha

ProofofConcept

(POC)

inThailand,

the

Partnership

illustrates

howfederatedsystemscan

revealactionable

insightswhile

maintainingdata

privacyandsovereignty,strengtheningcoordination

amonggovernments,

businessesandcivilsociety.

This

model

buildsafoundationforcollectiveadvantage,witheachstakeholder

benefitingfrom

greatervisibility,efficiencyandaccountabilitywhile

theecosystemasawhole

becomes

morecapable

of

prevention:–Governmentsgainclearervisibility

to

target

enforcementanddesign

responsive

policy.–Businesses

reduceduplicationand

strengthen

compliancewhile

improving

riskmanagement,

supplychain

resilienceand

brandtrust.Asregulatoryscrutiny,

investorexpectationsand

due-diligenceobligations

intensify,collaboration

offersa

practical

pathto

meetstandards

more

efficientlyand

credibly.–Civilsocietyandworker

organizations

amplify

workervoiceandshapesystemicsolutions.–Investorsanddonors

access

reliable

data

toassess

impactanddirect

resourceswherethey

are

most

needed.Thesolution

isscalable

bydesign.

Itsfederatedarchitecturecanexpandacrosssectors,

regionsand

institutionswithoutcentralizingauthorityorcompromisingsovereignty.Asparticipationgrows,each

newdatasetenhancesanalytical

power;stronger

insights

increase

incentivestocollaborate;

and

broaderengagementaccelerates

prevention,

thuscreatingavirtuouscycle

ofshared

intelligence

andcollaborativeaction.The

nextstep

iscollective.

Endingforced

labourwilldemand

leadership,collaborationandcourage

equaltothescaleofthechallenge.Through

shared

evidence,aligned

incentivesand

responsibleinnovation,stakeholderscan

movefrom

isolated

initiativestocoordinated

impact.

Byconnectinginsightssecurelyandactingon

shared

intelligence,

governments,

businessesandcivilsocietycanmakeforced

laboura

preventable

riskratherthan

anenduring

reality.Asthe

Partnership

movestowards

its2026development,allstakeholdersare

invitedtoparticipate,

learnandact,connecting

insights,

applyingshared

intelligenceanddemonstrating

measurable

progresstogether.ExecutivesummaryTheGlobal

Data

PartnershipAgainst

Forced

Labour

usesfederationandagenticAItotransformfragmenteddata

intosharedintelligence–drivingcoordinated,

privacy-preservingglobalactionagainstforced

labour.Harnessing

Dataand

IntelligenceforCollectiveAdvantage:EndingForcedLabour

inGlobal

Supply

Chains4The

problem:The

vicious

cycleofforcedlabourand

datafragmentationEvenasglobalefforts

expand,forced

labour

persistsamidfragmenteddata,

misaligned

incentivesanddisconnectedsystemsofaccountability.performedwithoutthe

person’sfreeand

informed

consent,

includingwheretheycannot

leavethejob

whentheywish.6Theterm

“modernslavery”is

broader.7

It

includes

forced

labour

butalsoencompasses

humantraffickingand

practices

resemblingslavery,such

asforced

marriageorthesale

of

children.Accordingto

ILOestimatesfrom2022,

nearly28

million

peoplearetrapped

inforced

labourworldwide,

includingabout

17

million

in

private-sectorsupplychains.8

This

representsan

increase

ofaround2.7

millionsince2016,

underscoringthe

needtoaddress

rootcauses,close

datavisibility

spotsandtostrengthenvictim

protection.9The

ILO

Forced

LabourConvention,

1930(No.29)definesforced

labouras“allwork

or

service

which

isexactedfromany

person

underthemenaceofany

penaltyandforwhichthe

person

has

notoffered

himselfor

herselfvoluntarily”.5

It

isasevereformof

labour

exploitation

that

canoccur

inanysector,countryor

supply

chain,

from

manufacturingandagriculturetoconstruction,domesticworkandtheinformal

economy.Forced

labourdependsontwocore

elements:(1)acrediblethreator

actual

penalty

(which

may

includeviolence,withholding

identitydocuments,

retainingwages,chargingor

indebtingworkers

through

recruitmentfees,threatsofdeportation

ordismissal,ordebt

bondage);

and

(2)

workOverthepasttwodecades,

companies,governments,

internationalorganizationsandcivilsocietygroups

have

launched

hundredsofprogrammestotackleforced

labour.Socialaudits,

worker

hotlines,traceabilitytools,socialcompliance

programmesand

nationalenforcementof

labourlaws

haveeachactedas

important

mechanisms

inthefightagainstforced

labour.10

Governments

havecomplementedtheseeffortsthroughtrademeasures,

import

bans,country

ratingsandresearch,allofwhichstrengthen

regulatory

andmarketaccountability.

Inthe

privatesector,due-diligencesystems,ethical

recruitment

initiativesand

responsiblesourcing

programmes

have

maturedrapidlyamongagrowing

numberof

companies;

however,too

manycompaniesstill

do

notmeaningfully

investigateforced

labour

prevalence

intheirsupply

chains.Atthesametime,

modernslaveryand

supply

chain

laws

inthe

United

Kingdom,AustraliaandCanada,

import

restrictions

inthe

USand

European

UnionPersistence

amid

progress:The

enduring

natureofforcedlabourAccordingtothemostrecent

InternationalLabourOrganization(ILO)estimates,almost28

million

people

aresubjectedtoforcedlabourworldwide,acrossbothformalandinformalsectors.3

Despitedecades

ofprogressinpolicy,

advances

in

local

action,corporateduediligenceandcivilsocietyadvocacy,overallprevalencehas

notdeclined

but

has

infactincreased,pointingtoadeeper,

system-level

weaknessindetecting,preventingand

addressing

forcedlabour.

Itpersistsnot

because

its

causes

are

unknown,butbecausethedata,accountabilityand

coordinatedactionremaindisjointed.41.1BOX

1Harnessing

Dataand

IntelligenceforCollectiveAdvantage:EndingForcedLabour

inGlobal

Supply

Chains5Understandingforcedlabour1–Corporateaction:

Many

leadingcompanies

haveembedded

human

rightsduediligence,

suppliercodesofconductand

responsible

recruitment

policiesacrosstheirglobaloperationsandsupply

chains.–Industrycollaboration:

Sector

alliances

(e.g.apparel,electronics,agriculture)are

developing

sharedtoolsforaudits,workervoiceamplificationandgrievance

management.–Governmentframeworks:

National

lawsand

trade

policies

increasingly

requiresupplychain

transparencyandforced

labour

riskreporting.–Internationalcooperation:

The

ILO,InternationalOrganizationfor

Migration

(IOM)

andother

United

Nations(UN)

partnerscoordinatetechnicalassistance,global

estimatesandstandardsalignment.Why

itstill

matters:

Despitetheseadvances,most

systems

rely

on

disconnected

datasources,creating

duplication

and

informationgaps.A

trusted

and

interoperable

model

ofcollaboration

is

needed

to

connect

existingefforts,transforming

parallel

initiatives

intosharedvisibility.Theseadvances

have

builtessential

momentuminaddressingforced

labour,yet

progressremains

insufficient.

Mostsystemsstill

operateindependently,

limitingtheabilityto

see

risksacrosssupplychainsor

act

on

them

collectively.Evenwherestrongcommitment

exists,

theinformationandtools

neededfor

coordinated,system-levelaction

remaindispersed

acrossstakeholders,whooftendo

not

(or,

in

some

cases,cannot)collaborateopenly

dueto

commercial,politicalor

reputationalsensitivities.(EU),anddue-diligence

legislation

inGermany,France,

NorwayandSwitzerlandare

strongexternaldriversof

change.11,12

Legislative

progress

across

EastAsia,South-EastAsiaandtheGulfCooperationCouncilhasaddedfurthermomentum,

whilehundredsofglobalbrands

invest

inworkervoiceplatformsandtraceabilitytechnologies.13,14Eachoftheseeffortsgeneratesvastamountsofdata,

onsuppliers,recruitment,enforcementandworkerconditions,butmostof

it

remains

lockedwithin

institutionalboundariesorincompatiblesystems.Globalsupplychainsconnect

millionsof

enterprises

and

hundredsofmillionsofworkers,

but

dataand

informationabout

labourconditionswithin

them

is

uneven,siloedandoften

inaccessible.Governmentscollect

inspectionand

migrationdata;

businessesgatherauditandsupplier

information;non-governmentalorganizations(NGOs)andtrade

unionsdocumentworkerexperiencesandgrievances.Globalestimates,statisticalguidelines,academic

research,grievance

mechanismsanddigital

platforms

haveexpandedtheoveralldatalandscape.15

Eachsource

offers

greatvalue

onitsown,yet

rarely

interactswithothers.16

Thisfragmentation

makes

itdifficulttoconsistentlyand

reliably

identify

patternsofrisk,target

prevention

effortsor

measure

progresseffectively.17

The

result

isan

incomplete

pictureofthe

issueat

hand

and

limitedcollectivecapacityto

prevent

it.Thestructuralrootsoffragmentation:Data,incentives,trustandgovernancegapsHarnessing

Dataand

IntelligenceforCollectiveAdvantage:EndingForcedLabour

inGlobal

Supply

Chains6What’salreadyhappeninginbusiness

and

policy1.2BOX

2Atthesametime,

incentivestoshareor

even

collect

dataare,

in

manycases,weak.Whenthe

benefits

oftransparencyare

uncertain,the

risks

highorexposure

uncomfortable,stakeholders

hesitatetodisclose

information.

Uneven

incentivesand

limited

capacityfordisclosureallow

informationgapsto

persistacrossthesystem,

particularlywherecommercialconfidentiality,

legal

mandatesor

limited

technical

infrastructureconstrainengagement.Compoundingthese

barriersare

persistentdeficitsoftrustandgovernance.

Privacy,

sovereigntyand

reputationalconcernsdeter

collaboration,while

longstanding

mistrust

betweensectorsreinforcessilosand

limits

data

exchange,

evenwhereobjectivesalign.

No

shared

governanceframeworkexiststoalign

accountability

ormeasurecollective

impact,and

informationtendstoflowverticallywithinsectors

rather

thanhorizontallyacrossthem.Thisfragmentation

is

reinforced

bydeeperstructural

barriersthatshape

howdata,

incentives,trustand

governance

interact.

Informationaboutforcedlabour

isabundant

insomeareasyet

absent

inothers,especially

inthe“first

mile”ofproductionor

informalwork,whereconditions

remain

largelyinvisibleand

under-documented.

Eachactorgathers

datawithintheirown

mandate,

usingdifferenttools,standardsand

incentives.Assuch,existing

sourcesvarywidely

inqualityand

rarely

align

onstandardsor

interoperability,whileworkersoftenunder-reportexploitationduetofearof

retaliation

or

lackofaccessto

reliable

mechanisms.18

It

isworth

notingthatdifferences

incollection

methods,

verificationstandardsand

reporting

incentivescan

produce

misleadingor

incomplete

information.Somedatasets

may

reflectcommercial,

politicalor

methodological

bias,

underscoringthe

importance

ofvalidationandtriangulationacross

multiplesources

beforedrawingconclusions.Examplesofdatatypes:Workersurveys,hotlinedata,

union

reports,

NGOcasefiles,

survivortestimoniesTypicalsources:

NGOs,unions,worker

voice

platformsRelevanceto

impact:

Revealslivedexperience,

riskpatternsand

hidden

coercionUniverse:

PublicsectorExamplesofdatatypes:Socialaudit

reports,suppliercompliancedata,

recruitmentagency

records,grievance

dataTypicalsources:Companies,auditors,supplychain

platformsRelevancetoimpact:Offersoperationalvisibility

andcomplianceevidenceExamples

of

data

types:

Labour

inspections,

prosecutions,

migrationand

borderdata,humanitarianassessmentsTypicalsources:Governmentministries,

enforcementagenciesRelevancetoimpact:Anchorsprevalencedataandsupports

policydesignForced

labourdatatodayspansthree

broad

universes(corporate,civilsociety

and

public-

sectorsystems)asdescribed

byTechAgainst

Trafficking’sThree

Universesof

Data.Thechallenge

is

notscarcity

butfragmentation:connectingthese

universessecurely

iswhat

the

Partnershipseekstoachieve.Universe:CorporatesectorSource:Tech

Against

Trafficking.(2024).The

current

landscape

of

data

sharing.Building

an

effective

data

ecosystem

toaddress

forced

labor

in

global

supply

chains,pp.24–32.The

diversity

of

forced

labour

data(Tech

Against

Trafficking’s

Three

Universes

of

Data)Harnessing

Dataand

IntelligenceforCollectiveAdvantage:EndingForcedLabour

inGlobal

Supply

Chains7Universe:Civil

societyBOX3Source:World

Economic

Forum1Data

and

measurement

challenge–Information

is

collected

in

differentformats,

languagesandlevelsofdetail

depending

on

theactorsinvolved,leadingtofragmentation

andinconsistency.–Limited

interoperability

is

caused

by

a

lackofcommondatastandardsortaxonomies

tolinkauditresults,

inspectionfindings

and

workerfeedback.–Stakeholderslackconsensus

onwhichindicatorsdefineprogressor

howtomeasureprevalenceconsistently,resultinginmeasurement

uncertainty.–Eachactor

sees

only

afragment

ofthe

supply

chain,limiting

the

ability

to

identify

risks

or

verifyconditionsbeyondtheirimmediate

reach.2Incentive

challenge–Sharingdatacan

appear

riskywithoutclearcollective

benefit,creating

hesitation

todisclose

informationthat

mightexpose

weaknessesor

invitescrutiny.–Businessesfacecommercialconfidentiality

and

reputationalconcerns;governments

prioritizesovereigntyand

legal

mandates;and

manyactors–

includingcivilsocietyorganizations,

smallenterprisesand

localauthorities

–operatewith

limited

resourcesor

infrastructure

forsecuredata

management.–Privacyobligationsand

ethical

considerations

regardingsensitiveworkeroroperational

data

furtherdiscourageopen

sharing.3

Trust

challenge–Privacyandsecurity

concerns

limit

collaboration.–Historical

mistrustamongsectors

discourages

openexchange.–Withoutassurancethatdatawill

be

used

responsiblyand

reciprocally,evenwell-

intentionedactorsstay

siloed.4Governancechallenge–Existing

initiatives

lackan

overarchingframework

to

align

accountability

andmeasurecollective

impact.–Informationflowsverticallywithinsectors

but

rarely

horizontallyacrossthem.LackoftrverifiabgovernaunlandmeChallengeasuWeakicollnabBOX

4FIGURE

1Thevicious

cycleofFoursystemicchallenges:Data,incentives,trustandgovernanceHarnessing

Dataand

IntelligenceforCollectiveAdvantage:EndingForcedLabour

inGlobal

Supply

Chains8fragmentationTheviciouscycleoffragmentation>ethicalestandswithdstedofandsafegardcentoratckuardatfrementiicooeve<snasLasrThestructuralbarriersoutlinedabovedo

not

operate

in

isolation.Together,they

reinforce

one

anothertocreateaself-perpetuatingcycleinwhich

limitedvisibilityconstrainsaccountability,weakaccountability

dampensincentivesandalack

oftrust

preventscollaboration.Thisdynamicexplainswhyprogressremainsslowevenasawarenessand

regulationincrease:informationgrows,butintelligence

does

not.In

practice,thisviciouscycle

manifests

inthree

interlinkedways:1Fragmented

visibility:Data

from

audits,inspections,

regulatorsandsupplychaininformation

isoftenscatteredacross

multiple

organizationsandstakeholders,

makingitchallengingtocombine

and

analyse

it

effectivelyto

identify

patternsofrisk

or

rootcauses.2Duplicated

effort:Stakeholders

oftenassessthesame

limitedsetofworkplaces

or

suppliers,

ratherthan

buildingononeanother’s

findingstoexpandvisibilitytothosecurrently

unseen.

Intheabsenceof

interoperableframeworks,the