2026年值得关注与采纳的核心技术趋势研究报告 Top technology trends in 2026 to watch and adopt

EmpoweringVision.

DeliveringValue.

Toptechnologytrendsin2026towatchandadopt

2Toptechnologytrendsin2026towatchandadoptN-i

ByValentynKropov

ChiefTechnologyOfficeratN-iX

Thetechrevolutionyoucan’tignore

ThenextwaveoftechnologiespromisestochangehowbusinessesoperateinwaysthatgobeyondwhatIspossiblenow.Buttheseadvancescomewithasubstantial

infrastructurecost.Businessescannolongeraffordtoexperimentwitheveryemergingtrend,makingstrategic

technologyconsulting

morecriticalthanever.

LetIslookatthetrendsthatstandoutfortheirpotential,fromAIinfrastructureto

softwareengineering

practices.

2026technologytrendsadoption,innovation,interest,andinvestmentlevels

Source:Technologytrendsoutlook2025,McKinsey

w...●12345

50

25

Interest,2score(0=lower;1=higher)

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Key2026technologytrends:Investmentprioritiesfor

businessleaders

Thoughtfultechnologyselectionnowmattersmorethanbudgetsize.Companies

mustidentifywhichinnovationsamongrapidlygrowingmarketswilldelivera

competitiveadvantageintheirspecificcontext.We'vegroupedthetrendsintoclearcategories(AIcapabilities,infrastructureneeds,operationalimprovements,and

securityconcerns)tohelpyounavigatewhat'srelevanttoyouroperations.

AI&intelligentautomation

ArtificialIntelligence

isn'tonetechnology;it'sseveralrelatedcapabilitieschanginghowbusinesseswork.AIagentscancompletetasksindependently.AgenticAIisexpandingat44.6%annually.GovernancesystemshelpmanageAIrisks.Industry-specificAImodelsunderstandspecializedfields.

GenerativeAIcreatescontentandcodeandwillreach$442Bby2031.

Together,theserepresentthebiggestopportunitiesandchallengesforcompaniesadoptingnewtechnology.

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AgenticAI:Thenewworkforce

RecognizedonGartnerIstopstrategictechnologytrendsfor2026list,agenticAIisrapidlygainingenterpriseadoption.

TheagenticAImarketwillgrowfrom$7.06Bin2025to$93.2Bby2032.

Thisgrowthreflectsenterprisedemandforsystemsoperatingasvirtualcoworkersratherthansimpleautomationtools.

WhatsetsagenticAIapart:

Traditionalautomationrequireddeveloperstoprogrameverystepandexception.AgenticAIhandlesthelongtailofunpredictabletasksbyusingfoundationmodelsthatrespondappropriatelytosituationstheyIveneverencountered.Thesesystemsusedigitaltoolsdesignedforhumans(webbrowsers,forms,APIs),eliminating

theneedforcustomintegrations.Theyreceiveinstructionsinnaturallanguage,generateworkplansthathumanscanunderstandandmodify,andcommunicateamongthemselvestocoordinatecomplexworkflows.

Businessapplications:

OrganizationsaredeployingagenticAIacrossfunctionspreviouslyconsidered

toocomplexforautomation.Incustomersupport,AIagentsdonItjustanswer

questions-theyprocessorders,managereturns,andconnecttologisticssystems

autonomously.Softwaredevelopmentteamsuseagentsthatwrite,test,anddeploycodebasedonnaturallanguagedescriptions.Researchteamsdeploydeep-researchagentsthatdesignworkflows,executesearchesacrosshundredsofsources,and

synthesizecomprehensivereportsinhoursratherthanweeks.Earlyadoptersreportsignificantproductivitygains:creditanalystsatonebankachieved60%productivityincreasesandaround30%fasterdecision-makingbyusingAIagentstoautomate

memodrafting.

Yourmove:

●

Find3-5processeswhereemployeesspendconsiderabletimeontasksthatfollowpatternsbutneeddecision-making.Lookforworkthatcrossesmultiplesoftwaresystemsandinvolvesseveralsteps.Starttestinginlow-riskareaswheremistakeswon'tcausesignificantproblemsandwhereyoucaneasilymeasureresults.Beforeyoubegin,decidehowyou'lltrackprogress:howmuchfasterworkgetsdone,

howmanyerrorsoccur,andwhetheremployeesfindthesystemhelpful.Thesemeasurementstellyouwhethertheinvestmentisworking.

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2

AIgovernance:From

optionaltomandatory

AIgovernanceusedtobeoptional.Nowit'slegallyrequired.TheEUAIActfinescompaniesupto€35Mforviolations.

RegulatorsandcustomersincreasinglydemandthatcompaniesexplainhowtheirAIsystemsmakedecisions,provethatthosesystemstreatpeoplefairly,andshowwhoIsaccountablewhen

thingsgowrong.

Businessimpact:

Goodgovernancesavesmoneybypreventingproblems.Companiesthatskip

governancefacefines,damagetheirreputationwhenAImakesbiasedorwrongdecisions,andwastetimefixingsystemsthatshouldneverhavebeendeployed.Companieswithstronggovernancebuildcustomertrust,getemployeestouseAItools,andwincontractsasbuyersrequireproofofresponsibleAIpractices.

Yourmove:

FormanAIoversightteamthatincludespeoplefromlegal,IT,operations,andriskmanagement.ListeveryAIsystemyourcompanyuses,bothmachinelearningandgenerativeAItools.WriteclearpoliciescoveringwhocanuseAI,howtohandledata,howtoverifyAIoutputsareaccurate,andwhattodowhenproblemsarise.This

preparationletsyouexpandAIuseconfidently.

VerticalAI:Industry-specificintelligence

Amongtechnologytrendsin2026,industry-specificAItrainedonspecialized

dataanddomainknowledgestandsoutforcreatingcompetitiveadvantagesthatgeneral-purposeAImodelscannotreplicate.GeneralAImodelsknowalittleabouteverythingbutaren'texpertsinanything.VerticalAImodelsaretrainedspecificallyforoneindustry:healthcare,legal,logistics,ormanufacturing,sotheyunderstandtheterminology,regulations,andworkflowsthatmatterinthatfield.Industry-

specificAItrainedonspecializeddataanddomainknowledgecreatescompetitiveadvantagesthatgeneral-purposeAImodelscannotreplicate.

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Businessvalue:

VerticalAIeliminatestheneedtowriteelaboratepromptsexplainingcontext.

Thesystemalreadyunderstandsyourindustry.Yougetmoreaccurateresults

becausetheAIistrainedonrealscenariosfromyourfield,notgeneralinternetcontent.IntegrationiseasierbecauseverticalAIvendorsbuilddirectconnectionstothesoftwareyourindustryuses:medicalrecordssystems,legaldatabases,ormanufacturingplatforms.

Yourmove:

Research

verticalAI

vendorsinyourindustrynow:whatdatatheyuse,howtheyconnecttoyoursoftware,andwhatresultstheydeliver.Ifnogoodoptionsexist,checkwhetheryourcompanyhasproprietarydatathatcouldsupportbuildingacustomAImodel.DevelopingspecializedAIrequiresdedicatedengineeringskillsandcomputingresources,sopartneringwithanexperiencedtechnologyprovidercanhelpyoumovefasterandcapturethe2-3yearadvantagethatearlyadopterstypicallygain.

4

GenerativeAI:

Scalingcreative

andtechnicalwork

GenerativeAI

hasbecomestandardinfrastructureforcreatingcontent,writingsoftware,andconducting

research.

ThemarketwillgrowataCAGRof37%,drivenbymoreuse

casesandfallingcosts.

Someoperationscost50timeslessthanayearago,makinggenerativeAIaffordableformorebusiness

applications.Smallerspecialized

modelscanrundirectlyondevices,reducingrelianceoncloudservicesandimprovingresponsetimes.

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Businessapplications:

PharmaceuticalcompaniesusegenerativeAItopredicthowmoleculeswillbehave,cuttingdrugdevelopmenttimeandcosts.71%ofsoftwaredevelopersreport

productivitygainsbetween10%-25%whenpairinggenerativeAIwithstrong

qualitychecks.Marketingteamscreatepersonalizedcontentfordifferentaudiencesegmentswithouthiringproportionallymorewritersordesigners.ThebestreturnscomefromembeddinggenerativeAIintoexistingworkflows,notusingitasa

separatetool.

Yourmove:

PartnerwithanexperiencedtechprovidertobuildgenerativeAIintoR&Dand

creativework.DefinewhenAIoutputsneedexpertreviewbeforeuse.Trackspeedmetrics(howfastworkgetsdone)andqualitymetrics(accuracy,howoftenwork

needsrevision)tounderstandrealvalue.Trainteamstowriteeffectivepromptsandcriticallyverifyoutputs;theseskillsdeterminewhethergenerativeAIsavestimeorcreatesmorework.

Infrastructureandcomputing

Theinfrastructurelayer(datacenters,edgecomputingnodes,andthenetworks

connectingthem)facessignificantnewstrain.AIworkloadsrequireexponentially

morecomputingpower,specializedhardware,andenergythanprevioustechnologywaves.Thissectioncovershowinfrastructureevolvestomeetthesedemandsandwherebusinessesmustinvesttoremaincompetitive.

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AI-nativeinfrastructure:Rethinkingthestack

TraditionaldatacentersdesignedforwebapplicationsanddatabasescannothandleAIworkloadsefficiently.AI-nativeinfrastructurerepresentsaredesignofcomputingsystemsaroundthespecificrequirementsoftrainingandrunningAImodels.Power-intensiveAIinfrastructureismakingelectricitysupplytheprimaryconstraintonAIexpansion.

Businessimpact:

Infrastructuredecisionsmadenowdeterminewhat'spossiblein2027-2028.

CompaniestreatingAIinfrastructureasanITexpenseratherthanastrategic

capabilitywillbeconstrainedwhendeployingAIatscale.Competitorswithpurpose-builtAIinfrastructuregainadvantagesinmodeltrainingspeed,inferencecost,

andabilitytorunlargermodels.ThistranslatesdirectlytobetterAIapplications,

fasteriterationcycles,andloweroperationalcostsperAIinteraction.AI-native

infrastructurerequiressignificantupfrontinvestmentbutdeliversbettercontrolandlowerlong-termcoststhancloudservicesforhigh-volumeproductionworkloads.

Yourmove:

AudityourinfrastructureIsreadinessforAIworkloadsnow.Assesspowercapacity,coolingsystems,andnetworkbandwidth.IfplanningsignificantAIdeployment,

engagewithfacilitymanagersandutilitiesearly-leadtimesforpowerupgradescanexceedsoftwaredevelopmenttimelines.Fororganizationsnotreadyforcapital

investmentinAIinfrastructure,understandcloudoptionsthoroughly,includingcostsatproductionscaleandvendorlock-inrisks.

Edgecomputing:processingatthesource

Cloudcomputingcentralizesdataandprocessinginmassivedatacenters.Edgecomputingreversesthis,movingcomputationclosertowheredataoriginates:

factories,retailstores,hospitals,andvehicles-oftendirectlyonInternetofThingssensorsandembeddeddevices.Thisshiftaddresseslatency,bandwidthcosts,anddatasovereigntyrequirementsthatthecloudalonecannotsolve.

Theedgecomputingmarketwillgrowfrom$564.56Bin2025toover$5Tby2034,representing28%annualgrowth.

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Businessimpact:

Edgecomputingprocessesdatainstantlyatitssourceratherthansendingittodistantcloudservers,enablingreal-timeresponsesinmanufacturing,retail,andhealthcare.Thisapproachalsokeepssensitivedatalocalforeasiercomplianceandcutscostsbysendingonlyimportantinsightsinsteadofmassiveamountsofrawdata.

Thetradeoffisincreasedcomplexity.Insteadofmanagingeverythinginonecentrallocation,companiesmustnowhandlesoftwareupdates,security,andmonitoringacrosshundredsorthousandsofseparateedgedevices.Makingthisworkrequiresnewskillsandoftenspecializedmanagementsoftwaredesignedspecificallyfor

distributedsystems.

Yourmove:

Identifywhichoperationsneedinstantresponses,generatelargeamountsofdata,ormustkeepinformationinspecificlocations.Goodexamplesincludefactory

qualitychecksthatneedimmediateadjustments,storesthatpersonalizedisplaysforshoppers,orhospitalsmonitoringpatientvitalsigns.

Figureoutifthebenefits(fasterdecisions,lowerdatatransmissioncosts,andmeetingregulatoryrequirements)areworththeextraworkofmanagingmanyseparatesystems.Testedgecomputingatoneortwositesbeforeexpandingitacrossyourorganization.

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7

Quantumcomputing:Fromlaboratorytolimitedproduction

Quantumcomputinghasgeneratedexcitementandskepticisminequalmeasure.In2026,thetechnologyremainsexperimentalmainly,butrecentbreakthroughsaremovingitfrompureresearchtowardlimitedpracticalapplications.

Thequantumcomputingmarketwillgrowfrom$1.79Bin2025to$7.08Bby2030ata31.6%CAGR.

Thisrepresentsprogressbutremainssmallcomparedtoothercomputingmarkets,reflectingquantum'searlystageandnarrowapplicability.

Real-worldapplications:

Oneofthepromisingtechnologytrendsin2026,quantumcomputingwonItreplaceconventionalcomputersformosttasks.Itsvalueliesinspecificproblemtypeswherequantummechanicsprovidesadvantages.Financialinstitutionsexplorequantum

algorithmsforportfoliooptimizationandriskmodelingthatconsidermorevariablesthanclassicalcomputerscanprocessefficiently.Pharmaceuticalcompanies

investigateusingquantumsystemstosimulatemolecularinteractionsfordrug

discovery,potentiallyidentifyingcandidatesthatconventionalsystemswouldmiss.Logisticscompaniestestquantumapproachestorouteoptimizationproblemswithmassivesolutionspaces.In2026,organizationsaremovingfrompureresearch

totestingquantumsystemsonrealbusinessproblems,butmostapplicationsremainexperimental.

Yourmove:

Mostorganizationsshouldmonitorquantumdevelopmentsandbuildrelationshipswithquantumcomputingprovidersratherthancommittingresourcesimmediately.Forlargefinance,pharmaceuticals,orlogisticsenterprises,considersmallpilot

projectstobuildquantumexpertisebeforethetechnologymatures.

Learnmore:7AItrendsto

watchin2026

11Toptechnologytrendsin2026towatchandadopt

Operationalexcellence:

Automatingforscale

AsbusinessesscaleAIanddigital

capabilities,operationalcomplexity

growsexponentially.Manualprocessesthatworkedfordozensofapplicationsbreakdownwithhundreds.ITteams

struggletomanageinfrastructuresprawl.Developmentcyclesslowascoordinationoverheadincreases.

Thissectioncoverstwotechnology

trendsin2026thathelporganizationsmaintainvelocityastheyscale:

hyperautomationforend-to-end

workflows,AIOpsforautonomousIToperations,andplatformengineeringfordeveloperproductivity.

Hyperautomation:Beyondtaskautomation

Traditionalautomationtargetsindividualtasks:processinganinvoice,sendinganemail,updatingadatabaserecord.Hyperautomationconnectsthesetasksintocompleteworkflowsthatrunend-to-endwithouthumanhandoffs.

Thehyperautomationmarketwillexpandfrom$46.4Bin2024to$270.63Bby2034at17%annualgrowth.

Thisreflectsbusinessesmovingfromautomatingindividualstepstoautomatingentireprocesses.

Businessapplication:

Hyperautomationcombines

roboticprocessautomation

(RPA),AI,andanalyticstohandlecompleteworkflows.Aninsuranceclaimdoesn'tjustgetautomaticallyenteredintoasystem;itgetsvalidated,routed,assessed,approved,orescalated,andpaidwithouthumantouchexceptforexceptions.Hyperautomationrequiresthinkinginworkflows,nottasks.AccordingtoaMcKinseystudy,rule-basedtaskautomationdrives30-200%ROIinoneyear.

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Yourmove:

Identifythreeend-to-endprocesseswhereworkflowsthroughmultiplesystemsandpeoplespendtimeoncoordinationratherthanjudgment.Mapcurrent

workflows,includingallhandoffs,decisionpoints,andexceptioncases.Calculatethetimeandcostspentoneachprocess.PilothyperautomationontheprocesswiththeclearestROIandleastexceptioncomplexity,thenexpandbasedon

results.OrganizationslackingautomationexpertiseshouldpartnerwithprovidersexperiencedinprocessredesignandRPAimplementationratherthanattemptingtobuildcapabilitiesfromscratch.

AIOps:AutonomousIToperations

IToperationsteamsdrowninalerts,logs,andincidents.Asinfrastructurescales,human-onlymonitoringbecomesimpossible.AIOpsappliesAItodetectissues,

identifyrootcauses,andremediateproblemsautomatically.By2029,agentic

AIwillautonomouslyresolvemostofthecustomerserviceissues,according

toGartnertechnologytrends2026.ThisincludesITservicedeskoperationswhereAIOpshandlesincidentdetection,diagnosis,andresolutionwithminimalhumanintervention.

WhatAIOpsdelivers:

Predictivemaintenancethatidentifiesfailingcomponentsbeforetheycause

outages.Automatedremediationthatfixescommonproblemswithouthuman

intervention.Rootcauseanalysisthattracesissuesacrosscomplexdistributed

systemsfasterthanmanualinvestigation.Capacityplanningthatpredictsresourceneedsbasedonusagepatternsandbusinessgrowth.

Businessimpact:

Meantimetoresolution(MTTR)dropssignificantlywhensystemscandetectandfixproblemsautonomously.Organizationsreportmovingfromreactivefirefightingtoproactivesystemmanagement,freeingITstaffforstrategic

projectsratherthanincidentresponse.AIOpsrequirescleandata:logs,

metrics,andtraces,structuredforAIanalysis.OrganizationswithfragmentedmonitoringorinconsistentloggingstruggletodeployAIOpseffectively.

Itrequiresinvestinginobservabilityinfrastructurebeforeexpectingautonomousoperations.

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Yourmove:

EvaluateAIOpsplatformsforIToperations,startingwithanassessmentofcurrentobservabilitymaturity.Ifmonitoringdataisfragmentedacrosstoolsorlacksa

consistentstructure,consolidateandstandardizebeforepursuingAIOps.ConsiderpartneringwithatechnologyproviderthathasexperienceintegratingAIOpsintoexistingenvironmentsandcanhelpnavigatetheimplementationcomplexity.

MeasureimprovementsinMTTR,alertnoisereduction,andstafftimefreedforstrategicwork.

Continuereading:AIOpsstrategy:

Keycomponentsandbestpractices

Securityandtrust:Buildingresilientsystems

Traditionalperimeter-basedsecurityfailsasorganizationsmoveworkloadsto

cloudenvironments,connectthousandsofIoTdevices,andsupportdistributedworkforces.Theassumptionthatanythinginsideyournetworkistrustworthynolongerholds.Amongthemosttransformativetechnologytrendsin2026aretwoapproachestobuildingsecurityandtrustindistributed,digital-firstoperations:

zero-trustarchitectureforcontinuousverificationandblockchainfortransparent,tamper-proofrecords.

10Zero-trustarchitecture:Verifyeverything,always

Traditionalcybersecuritymodelsassumenetworkperimeters,whicharefirewallsprotectingtrustedinternalnetworksfromuntrustedexternalthreats.Zero-trustrejectsthisassumption.Everyaccessrequestrequiresverification,regardless

ofsource.

Thezero-trustsecuritymarketwillexpandfrom$42.28Bin2025to$124.5Bby2032at16.7%annualgrowth.

Thisreflectsorganizationsrecognizingthatperimetersecuritycannotprotectmoderndistributedoperations.

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Whynow:

Threeforcesdrivezero-trustadoption.

Remoteworkeliminatedthenetwork

perimeter:employeesaccesssystemsfromhomenetworks,coffeeshops,andairports.Cloudadoptionmovedapplicationsand

dataoutsideorganizationalcontrolto

third-partyinfrastructure.IoTproliferationconnectedthousandsofdevices:security

cameras,sensors,andbuildingsystemsthatlacktraditionalsecuritycontrols.Traditionalperimeterdefensecannotprotectthis

distributedenvironment.

Businessimpact:

Zero-trustpreventscostlybreachesaveraging$4.45Minremediationexpensespluslost

businessandreputationdamage.Aproperlydeployedzero-truststrategycanpreventupto31%ofinsuredcyberlossesannually.Zero-trustenablesbusinessagility,supporting

remoteworkforces,adoptingcloudservices,andconnectingpartnerswithoutexpandingtheattacksurface.ContinuousverificationandaccessloggingforregulatedindustriessimplifySOC2,HIPAA,andPCI-DSS

compliance.Implementationcostsrange

fromhundredsofthousandstolowmillions,whilepreventingasinglemajorbreachsavesmultiplesofthatinvestment.

Yourmove:

Starttransitioningfromperimeter-based

securitytozerotrustbyprotectingyour

criticalsystemsthroughcontrolledand

continuouslyverifiedaccess.When

choosingacybersecuritypartnertohelp

implementtheseprotections,lookforfirmsthatunderstandyourbusinesscontext.

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11

Blockchainforenterprise:transparent,tamper-proofrecords

Blockchaingainedattentionthroughcryptocurrencybutoffersvaluebeyonddigitalcurrency.Itscorecapabilityismaintainingtransparent,tamper-proofrecords

acrossdistributedsystems,whichsolvesrealbusinessproblemsaroundtrust,transparency,andverification.

By2029,theglobalblockchainmarketisexpectedtoreach$248.9B,aCAGRof65.5%.

Thisrapidgrowthismainlybecausemoreventurecapitalfirmsareinvesting

heavilyinblockchainstartups.Atthesametime,industrieslikeretail,supplychainmanagement,andbankingareadoptingblockchain.

Whatblockchainprovides:

Distributedledgersrecordtransactionsacrossmultiplepartieswithoutacentralauthority.Oncerecorded,entriescannotbealteredwithoutconsensus,creatingatamper-proofhistory.Allparticipantsseethesamerecords,eliminating

discrepancies.Smartcontractsexecuteautomaticallywhenconditionsaremet,reducingcoordinationoverhead.Cryptographicverificationensuresauthenticitywithoutrequiringtrustinintermediaries.

Businessimpact:

Blockchainhelpstrackproductsfromorigintocustomer,makingverifying

authenticityeasier,ensuringethicalsourcing,andquicklypinpointingaffected

batchesifproblemsarise.Italsogivespeoplecontrolovertheirpersonal

information,lettingthemshareverifiedcredentialssafelywhilereducingtheriskofidentityfraud.Infinance,blockchainenablesfaster,cheaper,andmoretransparentcross-borderpayments,helpingbanksandcompaniescutcostsandspeedup

internationaltransactions.

Yourmove:

ItIsmorepracticalformostenterprisestopartnerwithexistingblockchainplatformsratherthanbuildingfromscratch,unlessyourprojectrequiresafullycustom

solution.Focusonareaswhereblockchainaddsclearbusinessvalue,suchassupplychaintransparency,securedigitalidentities,orcross-borderpayments.

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Sustainabilityandconnectivity:Enablingthefutureresponsibly

Oneofthekeytechnologytrendsin2026impactingbusinessesisthegrowing

challengeofbalancingincreasingenergyconsumptionagainsttheneedforrobust,always-onconnectivity.Datacenters,whichpowerserviceslikeAIandcloud

computing,usealotofenergy,makingenergyefficiencyatoppriority.Atthesametime,5Gand6Gnetworksenablefaster,morereal-timebusinessoperationsand

connecteddevices,helpingbusinessesbecomemoreefficientwhilecuttingdownonphysicalinfrastructure.

Data-centerenergyconsumptiongrowth

Source:S