波士顿咨询- 人工智能重塑 SaaS 格局企业需具备可灵活调整的定价策略 As AI Reshapes SaaS,Companies Need Pivot-Ready Pricing

TECHNOLOGYINDUSTRY

AsAIReshapesSaaS,CompaniesNeedPivot-

ReadyPricing

ByJohnPineda,AlexMcClure,andScottWoody

ARTICLEOCTOBER30,202615MINREAD

ThisarticleisacollaborationbetweenBCG,Stripe,andAWS.

AgenticAlisthebiggestplatformshiftsincecloud,representinga$3-trillion-plusrevenue

opportunityforthesoftwareindustry.ThisshouldbegoodnewsforSaaSproviders,butthemarketreactionhasbeensobering.Inearly2026,USsoftwarestockslostabout$2trillioninvalue,on

fearsthatagenticAlwouldfundamentallyunderminetheirbusinessmodel.Onetop-performingtechfundmanagertoldBloombergthatapplicationsoftwarefacesan“existentialthreat.”

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Althoughmuchofthatdeclinehassincereversedandrevenuegrowthinnon-AISaaScompaniesremainsstrong,accordingtoStripedata,therecoveryhasbeenunevenandmarketuncertainty

remainshigh.InourdiscussionswithSaaSCEOsandinvestors,thesamequestionscontinuetobeasked:Howdoweshiftour

pricingmodel

toridetheAIwaveratherthangetburiedbyit?Dowe

abandonsubscriptionsandseat-basedmodelsaltogether?Shouldwepricetotokencosts?

Answeringthesequestionsrequiresreimagininghowtoengagecustomers,structurepackaging

andpricing,plango-to-market,measurevalue,monetize,andorganizeoperations.TheresultwillbeaSaaSproviderbuilttokeeppacewithhowAIisreshapingbothcostsandwhatcustomers

value.

Tocreatethisstructure,however,providersshouldreengagetheirclientbasetofullyunderstandwhatdrivesvalueintheAIera.ThiswillinformanewstrategythatmapshowAIandagentic

economicswillevolveandhowpricing,packaging,andproviders’owncostbasecanshapethat

evolution.Thisstrategycaninformareshapingoftheorganizationtosupporttestingand

implementationofawiderangeofpossiblepricingmodels,includingusage-,outcome-,andcredit-basedmodels,allofwhicharerisinginprevalence.

Creatingthiskindoffutureflexibilityisvital.Successwillgotocompaniesthatrecognizeweareinanew,fast-movingeraandcaniterativelyexperiment,adapt,andimplementfreshapproachestomonetization.Wecallthiscapability“pivot-ready.”

WhyAIIsPuttingSaaSPricingModelsUnderPressure

SaaSprovidersthatuntilrecentlyhadawell-establishedandreliableplaybookformonetizationandbusinessgrowthnowfacemultiplechallenges,someofwhichpredatetheearly2026

meltdown:

Newcompetitorsareemerging.AI-nativeplayershavenewbusinessmodelsandpotentiallyloweroverheads.LLMprovidersaredevelopingproductsthatcoulddisplaceSaaSseats,suchasClaudeCoworkwithindustry-specificautomationpluginsforlawfirms.

BuyersmaytrytocutSaaSspendingtofundnewAIinitiatives.BCG’smostrecent

IT

SpendingPulsesurvey

showedthat66%ofNorthAmericanandEuropeanbuyersexpecttospendmoreonAI,includingGenAIandagents,buttoreducespendingandconsolidate

vendorsalmosteverywhereelse.

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Computecostsareunpredictable.SaaSprovidersneedtobuytokenstorunGenAI-poweredfeatures,makingusagecostsnotonlysignificantlyhigherbutalsodifficulttopredictatbothper-seatandaggregatelevels.

TheSaaS“moats”looklessdefensible.Forrivals,complexfeaturesthatwereexpensivetodevelopcanbecopiedquicklyusingAI-poweredcodingtools.Forcustomers,AIcanreduceswitchingcosts.

Morefundamentally,customerswerealreadyaskingtoughquestionsaboutvalue.AsSaaS

platformshaveproliferatedacrossenterprises,aggregatespendinghasbecomeincreasinglyvisible.Inevitably,CFOshavebeenwantingtoseeROI.

ThatdoesnotmeanSaaSplayersshouldabandontraditionalpricingmodelsandstartcharging

onlyforusageoroutcomes.Acompleteresetcarriessignificantrisk.SaaSrevenuegrowth

appearsresilient,accordingto

Stripedata

.FormostSaaSproviders,thedownsideofanabrupt

shifttousage-oroutcome-basedpricingisevengreaterthantheworst-casescenariowithexistingpricingmodels—evenforprovidersthatfacestrongcompetitionfromdisruptersandwhose

clientsareaggressivelycuttinglicenses(“seatcompression”).Inaddition,mostSaaScompanieslacktheorganizationalcapacitytoimplementusage-oroutcome-basedpricing.

Nevertheless,SaaSproviders(andothersoftwarefirms)shouldstillurgentlybecomepivot-ready.Theyshould:

Reengagecustomersonwhattrulydrivesvalue.

Definehowthepricingandmonetizationgameischangingforprovidersandthebroaderecosystem.

Buildtheoperationalcapabilitiestoexperimentwithandsupportusage-based—and

possiblyoutcome-based—models,evenifashiftisnotatthetopoftoday’sagenda.

Underneathallthisisanotherissue:costs.Traditionally,inat-scaleSaaSbusinesses,thesewereabackgroundissue.IntheAIera,costsvaryunpredictablybetweencustomersandwiththepricingplansofthird-partyLLMproviders.TheyarealsoaweakpointagainstAI-nativerivals—and,

perhapsmostimportant,theyarewatchedcloselybyinvestors.

ReengageCustomersonWhatTrulyDrivesValue

ManySaaSproviderscannotmeterhowtheirsoftwareisused,letalonethevaluetheydelivertocustomers.SomeAlfeaturestheyhaveintroducedareconvenienttimesaversforindividualusersbutfailtodelivertheenterprise-levelvaluethatwouldmakecustomershappytoincreasetheirspending.(SeeExhibit1.)

EXHIBIT1

HowtoDistinguishFeaturesThatGenerateRevenuefromThoseThat

AreCommoditized

Logistics

End-to-endjobbooking

(e.g.,fulltruckloadbookingand

confirmationofdelivery)

Auto-emailquoterequests

CustomerSuccess

Issueresolution

(e.g.,fullresolutionof

customerinteraction,withguardrails)

Financials

Smart

categorization

andreconciliation

oftransactions

(e.g.,autonomousgeneralledger)

Auto-categorizing

ofexpenses;

simpleinvoiceautomation

SupplyChain

Differentiated

Customerswillingtopay

Respondingto

disruption

(e.g.,detectinglate

deliveriesandsuggesting

alternativesuppliers)

Chatbots

Commoditized

Tablestakes

Monitoringstocklevels

Sources:Expertinterviews;BCGresearchandexperience.

Thisneedstochange.TocapturetheopportunityprovidedbyagenticAI,SaaSprovidersneedtounderstandandthenwintheircustomersalloveragain.Inparticular,theyshould:

·Renewthedialogueonwhattrulydrivescustomervalue.ManySaaSleaderstellusthat

customerswantagenticcapabilitiestodrivedownoperatingcosts.Thatmaybetrueforsomeusecases,butitiscriticaltounderstandthebroadercontextinwhichcustomersoperatetofinddeepersourcesofvaluethattheSaaSplatformcandeliver.

·Buildthe“taxonomyofvalue”foragenticcapabilities.WeseeSaaSprovidersbuildingavastnumberofagenticAlfeatures,butthoseproviderslackdifferentiation.ProvidersshouldcreateahierarchythatdistinguishesAI“tablestakes”fromfunctionalitythatmakestheirsoftwarestandoutversusrivals.(SeeExhibit2.)

·Createapaththatconnectsvaluetoattribution.SaaSprovidersshoulddrivedeeper

engagementwithcustomersonhowvaluecanbemeasuredandthenattributed.Thisisa

commonfailing;inaninformalsurveyofSaaSprovidersthatBCGconducted,thetopreasonscitedfornotshiftingtooutcome-basedpricingwere,first,thatoutcomeswerenotmeasuredand,second,thatoutcomeswerenotattributedtotheplatform.Evenifoutcome-based

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pricingisnottherightanswertoday,SaaSprovidersandtheircustomersneedclarityonhowtheplatformprovidesvalue.

EXHIBIT2

ATaxonomyofValueforAgenticCapabilities

0

Noagenticcapabilities

None

None

1

Al-augmentedassistance

(e.g.,draftingemails,leadscoring);someincrementalefficiencybenefit

Foundational—humanintheloop

Limited;incrementalrevenueonce

valueisdemonstratedviapilots

②

Taskagentscompletingmultiplesteps

Structured—clearactionboundaries,

Moresubstantialefficiencyand

withinasimpletask(e.g.,resolving

toolpermissions,QAandaudit

effectivenessbenefit;monetizedon

level1supportticketsend-to-end)

processes

taskscompleted

Workflowagentscompletingmore

complexjobs(e.g.,managingaActiveoversightandescalationpoliciescontractlifecycle)

Monetizedonjobscompletedor

operationaloutcomes

④

Automatedknowledgeworkers

executingabroadrangeofjobswithinadomain(e.g.legal,customersupport)

Advanced,continuousgovernance

Monetizedonoperationalorfinancialoutcomes

Source:BCGanalysis,

Note:Ilustrativeexample—thetaxonomyandthresholdswillneedtobeadjustedforeachprovider.

DefineHowthePricingand

MonetizationGameIsChanging

ExecutivesatSaaSprovidersintuitivelyknowthattherulesofpricinghavechanged.The

challengeisinthespecifics:understandingwhichruleshavealreadychangedandhowquicklytheyneedtorespondtochangesthatarestillahead.Theycangetclaritybyaskingthree

questions.

Howmuchisthemarketlandscapeandstrategicpricinggamechanging?Discussionswithcustomersprovidekeyintelligencehere.It'simportanttounderstandwherecustomersarespendingtheir“Alwallet”—thebudgetsetasideforAlinitiatives—andhowworkflowsareevolving.

FormanySaaSplayers,thecoreplatformwillnotbeeroded,butgrowthwillslowascustomer

spendingshiftstootherplatformsandincumbentsstruggletokeepupwithgrowingcomplexity.ManySaaScompanieshavehistoricallythrivedinwhatBCGcalls“thechoicegame”(typically

good-better-bestsubscriptiontiers).Themarketisevolving,however,andthecomplexityofAl

deploymentsmeanspotentiallyshiftingtootherpricingstrategies,suchasthecost,custom,and

dynamicgames

.ThesepricinggamesrequirebetterawarenessofhowcostsscalewithAIusage,andgreaterflexibilityandresponsiveness.

Whatshouldbemonetized?Historically,thiswasclear.HumanbeingssatinfrontofadeviceandaccessedtheSaaSplatformtodotheirjob.ButSaaSprovidersthatarepivot-readycanconsider

threerapidshifts:

Monetize“headless”access.Asagentsproliferate,theywillincreasinglyneedaccesstoSaaSdatabases,whichmanyenterprisesuseassystemsofrecord.SaaSplayersneedtothinknotonlyaboutaccessauthenticationviaAPIsandtheModelContextProtocol

(preferredforGenAIaccess)butalsoaboutfairuseandhowtochargeforthisaccess.

CreatenewtypesofAI-enabledproductsandservices.ThestrongestSaaSproviderscandefinenewproprietarydatasets,orchestration,andanalyticscapabilitiesbasedonuniquedifferentiation.Providersthatcoordinatemultipleecosystempartnerscanserveas

transactionplatformsandprovidepaymentsandembeddedfinancecapabilities.Thekeyhereistobeintentionalaboutwhichopportunitiestounlock.

Monetizeservicesdifferently.Traditionaldeploymentservicesshouldbefocusedonshortertimetovalue,rewardingagentictools,speed,andqualityevenifdoingsomeans

cannibalizingrevenue.Agenticmanagedservicesbecomemorevaluabletocustomersandhighermargintovendorsthantraditionalmanagedservices.

Howmuchchangedoesthepricingmodelneed—andwhen?Seasonedexecutivesandinvestorshavelivedthroughturbulencebefore;afterall,theSaaSbusinessmodelitselfwasahighly

disruptiveforceintheearly2000satatimewhensoftwarewasa“buyonce”purchase.Traditionalsoftwarecompaniesthatwerenotpivot-readyfacedacrisis.

Lookingattoday’sSaaSlandscape,itisprematuretodeclarethatseat-basedpricingisdead.Butcuttingseatshaslongbeenagoalofcost-consciousITdepartments,andagenticAIgivesthem

newwaystodothis.Threealternativesallowdepartmentstoavoidthesqueeze:adoptinga

subscriptionmodelmorealignedwithvalue(suchasanenterprisefootprintmodel),pricingon

thebasisoftasksorjobscompleted,andchargingonthebasisofoperationalorfinancial

outcomes.Token-basedpricingorinfrastructuremeasurescouldbeusedassecondarymetricsifcost-to-servebecomesapressingissue,butwerecommendavoidingthemasprimarymetrics.AItokencostcurvesarelikearollercoasterwithunpredictabletwistsandturns;wegenerallyavoidlinkingrevenuetoafairgroundride.

Thecurrentleadingapproach,basedonexperienceacrossBCG,AWS,andStripe,isthehybridmodel,whichmixesconventionalsubscription-basedpricingwithoneofthealternativemodelslistedabove.Stripe

surveyedmorethan2,000

globalbusinessesandfoundthat49%ofhigh-

growthand57%ofhypergrowthcompanieshaveadoptedhybridmodels.Andcustomersare

prepared:BCG’sITSpendingPulsesurveyandmarketresearchacrossenterprisebuyershave

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confirmedmostbuyersalsopreferthepredictabilityofhybridandcommitted-spendingmodelsfornow.

BuildingtheInfrastructureforPivot-ReadyPricing

Thegrowthpotentialofmodelsthatincorporateusageisclear,buttheshiftisharderthanmanySaaSleadersanticipate.InStripesurveydata,

67%ofhypergrowthcompanies

reportedthattheychangedtheirpricingthreeormoretimesinthelasttwoyears;forlow-growthcompanies,thiswasjust22%.Thetop100AIcompaniesonStripereach

$1millioninannualizedrevenue

inamedianof11.5months,about4monthsfasterthanthefastest-growingSaaScompanies.Aligning

internallyonthepricingmodelandmetricsisanessentialfirststep.Thecompaniesmakingthefastestprogresstreatmonetizationascoreinfrastructure,notsomethingtosolveinone

engineeringsprint.

Oncealigned,theworkbeginsbydefiningwhatthecustomerispayingforandhowtomeasure

thatactivity,oftenbybuildingtelemetry—collectingthedatathatwillpowerthenewusage-

basedpricingelement.WithmanynewAIcapabilities,youcan’tmonetizewhatyoucan’tmeter,andthefastest-movingcompaniescaptureusageattheeventlevel,decoupledfromproduct

code,sopricinginquiriesorchangesdon’trequireengineeringintervention.Thepricingdesign

shouldalsodeterminewhetherthenewmetricisaddedtoanexistingsubscriptionorreplacesit,andwhatthecompanywilltracktoevaluatethemodel.Theinvestmentinbillingisvital,and

withoutthatalignment,confusioncanarisewithfieldteamsandcustomers.Aninvoicethecustomercannotunderstanderodestrust,risksretention,andcreatesanonpaymentrisk.

Legacysystems,designedforamuchsimplerworld,typicallybreakwhenfacedwithcomplexitiesinmetering(suchasturningagivenvolumeofAPIcallsintoadollarfigureonaninvoice)or

portfolioandpricingmodelmanagement(whereproducts,tiers,discounts,andrateshave

proliferated).Acentralizedproductcatalogwithapplicableratesreducesengineeringoverheadandmakespricingexperimentationviable.

Withoutimprovedpricingarchitecture,downstreamteamsthatrelyonbillinginformationquicklyfeelthestrain.Salesrepsareforcedtoimproviseonpricing—anddealsslowdown—whenpricesheetsandbillingtoolsaredisconnected.Infinance,theinherentvariabilityofusage-based

pricingexposesthelimitsoftraditionalfinancial-planningtools;ashifttoprocessingdata

continuouslywillbeneeded.Withoutwell-constructedmonetizationinfrastructure,teamslikethesewillwastetimewithmanualworkarounds.

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Ahigh-qualitybillingarchitecturecanprovideadditionalbenefits;forinstance,itsurfacesinsightsfortheSaaSprovider’smarketingandfinanceteams,aswellasinsightsforcustomers.

It’snosurprise,then,thatleadersoftenunderestimatetheupfrontresourcesneeded,theroadmaptradeoffs,andtheongoingcostofengineering,infrastructure,andmonitoring.

Leaderscanreturntocorequestions:Canweingestandmeterhighvolumesofdata,update

pricingquickly,calculateinvoicesaccuratelyacrosseveryproductandcustomer,maintainGTMflexibility,andverifythatnewproductsaredeliveringontheR&Dthesis?Thatisnotabilling

question.It’saninfrastructurequestion.

Tomakeitwork,threeshiftsareneeded:

Pricingmustbecomeacoreproductcapability.Itshouldenableexperimentation,successmetrics,andacentralizedsourceoftruthforvalueanalysis.

ProductandGTMcollaborationshouldbetightened.Thereshouldbetransparentchannelstodiscusscustomerimpact,shiftsintheidealcustomerprofile,valuemessaging,andfield

adaptability.

TheGTMoperatingmodelshouldberethoughtholistically.Recalibrateroles,customerengagement,andcompensationsocontinuousadoptionbecomesatop-downobjective.

SaaSLessonsfromAINatives

AIstartupsareshowingremarkablerevenuegrowth.StriperesearchshowsthatAIstartups

foundedinthepreviousthreeyearshavereached$5millioninannualizedrevenueinamedianofjust9months.Incontrast,earlierresearchshowedthetop100SaaScompaniesreachedthislevelinamedianof37months.(SeeExhibit3.)

EXHIBIT3

AIIsPoweringaNewWaveofSoftwareGrowth

Techstartups'timeto$5millioninannualizedrevenue

37months

$4M

$3M

$2M

$1M

$OM

30

24months

9months

$5M

20

10

0

MONTHSSINCEFIRSTREVENUE

—SaaS100:Historicrevenuegrowthpatternofthe100top-performingSaaScompanies

—Al100:Growthpatternforthetop100Alcompaniesmeasuredin2024

—NewAl:Mostrecenthypergrowthtrend

Source:Stripe.

Thesefast-growingAlcompaniesincludenotonlyhouseholdnamessuchasOpenAland

Anthropicbutalsospecialistsinverticalssuchaslegalorhealthcare.Examiningthesenewplayersyieldslessonsabouthowgrowthmodelscanalignwiththewaysinwhichaproductdeliversvalue.Commonpatterns:

·Monetizationisacoreproductdecision.Fromdayone,manyofthesebusinessesbuiltcommercialmodelsthattieusagetovalue,alow-riskstrategyforthemgiventheyhavenoexistingrevenuestreamstocannibalize.

·Customersexperiencelowbarrierstorealizingvalue.Usersexperiencethevaluebeforetheypay,meaningincentivesarealignedonbothsides.ThisinvertstheSaaSlegacymodel,wherecustomersstartreceivinginvoicesbeforevalueisproven.

·Customersincreaseglobalreachquickly.Lowentrybarrierscombinewithcloud

infrastructure,allowingthesebusinessestotestnewmarketsquicklyandtoexpandwithoutfriction.

·Customerscombinedomainspecializationwithdeepworkflowintegration.Applicationsthatpairverticalexpertisewithend-to-endworkflowautomationarebecomingmore

common.

·Internaleconomicsdriveadditionaladvantages.Becausethesecompanieshaveturnedtheircommercialstructuresintoanacceleratedcustomeracquisitionfunnel,they

canoperatelean,oftendeployingAltoincreaseproductivityinnewforms.

Together,thesecreateasystemicchallengetotheeconomicsthatmostSaaSproviders

experience:toincreaserevenue,theywillalsoneedtoincreasetheirheadcount.Alnativesdidn't

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havetobecomepivot-ready—theywerebuiltthatwayfromdayone;incumbentsnowhavetomatch.

TheurgencyisalsoevidentinhowquicklyyoungSaaSbusinessesarenowscaling:platformsonStripethatwentliveinJanuary2026arereaching$1millioninpaymentvolumeatahigherratethananypreviouscohortovertheequivalentperiod.

BuildingforWhatComesNext:

WhenMachinesBecomeBuyers

Thereisoneotherkeychange.Itstartswithafoundationalquestion:Whydoespricingexist?

ThetraditionalSaaSplaybookisrootedinhowthehumanbrainprocessesinformationand

weighscostsagainstvalue.Pricingschemesreflectthis;forinstance,good-better-bestisgroundedinthehumantendencytoselectthemostbalanced,“better”tier.Otherpricingschemesusepriceanchoring,creatingapremium-priceddeluxepackagethatmakesallothertiersappearmore

affordabletopotentialcustomers.

Removethehuman,however,andthesedynamicsloserelevance.AIagentswillincreasinglyhaveaseatatthetablewhenorganizationsarechoosingSaaSproviders.Althoughtheyareunlikelytohavethefinalsayonthevendorinthenearterm,theycanevaluateandfine-tunethousandsofpurchasecombinationstorecommendwhichvendorortiercombinationsgeneratethemost

valueforthelowestprice.Inthemediumterm,theymaychooseavendor,managecontracting,andrebalancesubscriptionandusageoptionswithruthlessefficiencyeverymonth.TheseshiftswouldfurthererodethecostandrevenuepredictabilitythathasmadetheSaaSbusinessmodelsodurable.

AnearlyexampleofthispurchaseflowiswithPostHog,asoftwareproductdevelopmentand

analyticsplatform.ThroughStripeProjects,developersa