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1、Copyright 2024 Deloitte Development LLC.All rights reserved.Gen AI transforming Gen AI transforming transportationtransportationLessons from the frontier of an emerging technologyCopyright 2024 Deloitte Development LLC.All rights reserved.2Table ofcontents4 4Key findings5 5Wide(but shallow)adoption8

2、 8Value creation1212Clear challenges1717Overcoming barriers:Learning from leadersCopyright 2024 Deloitte Development LLC.All rights reserved.3Methodology Methodology This research relies on a July 2024 survey of 210 executives with strategic oversight(directors,vice presidents,and C-suite executives

3、)at transportation and supply chain companies.Most of the report focuses on perspectives of 186 executives working at companies with at least one generative AI(gen AI)use case in implementation.The questionnaire they completed was designed to better understand the extent and focus of gen AI adoption

4、 in the transportation industry,the value generated,challenges faced,and how gen AI leaders in the industry set themselves apart from the rest of the pack.Nearly one-third of the executives(30%)represent transportation companies with over$10 billion in revenue.Over half represent companies with$1 bi

5、llion to$10 billion in revenue(37%with$1 billion to$5 billion,and 15%with$5 billion to$10 billion)and 18%are from companies with revenues under$1 billion.Please refer to source lines for clarification on questions asked and sample sizes.17%14%23%40%Consumer product/retailtransportation and logistics

6、 Logistics providersOcean,rail,intermodal,inventory management,and wholesale and distributionTruckingThird-party logistics,freight forwarders,and brokeragesFirst-mile/middle-mileParcel/courier(4%)Digital freight(1%)Copyright 2024 Deloitte Development LLC.All rights reserved.4Key findingsKey findings

7、1.Many adopting,but few do so broadly1.Many adopting,but few do so broadlyFifty-four percent of respondents have at least one gen AI implementation,while another 21%have pilots only.Only one in fivecompanies have at least one broad implementation of gen AI in their supply chain or strategy and opera

8、tions.Even fewer have any broad implementation in supporting functions like finance,informationtechnology,human resources,or legal.2.Signals of acceleration 2.Signals of acceleration Adoption looks poised to accelerate in some key areas.Most companies surveyed have at least one limited implementatio

9、n or pilot in supply chain(73%)or strategy and operations(64%).3.Logistics providers lag other transportation players3.Logistics providers lag other transportation playersLogistics providers(third-party logistics,freight forwarders,and brokerages)are significantly less likely than other transportati

10、on players(trucking,first-and middle-mile providers,and retail and consumer product supply chain/logistics)to have at-scale gen AI implementations in all functions aside from strategy and operations.4.Early implementations seeing a wide range of economic value 4.Early implementations seeing a wide r

11、ange of economic value Route optimization,asset management,and warehouse operations are leading use cases,with relatively high adoption as well as economic impact.Demand planning,inventory management,and fleet management are also seeing high adoption but less economic value.Virtually no respondents

12、have applied gen AI to frontlineworkforce productivity or recruitment and retention.5.Finance is a missed opportunity5.Finance is a missed opportunityfor most for most Only 30%of respondents have a mature finance implementation.But among those that do,93%report high economic impactthe highest of any

13、 use case.6.High expectations,low success 6.High expectations,low success for big bottom-line outcomesfor big bottom-line outcomesMost respondents expect that gen AI can bring greater efficiency and higher revenue.However,few say they are achieving those aims.Among the 56%who hoped to increase reven

14、ue through gen AI,only 13%say theyve succeeded.In contrast,fewer are aiming gen AI at targetssuch as encouraging innovation,enhancing client relationships,and uncovering new insights.However,more than half with those ambitions say theyve succeeded.7.Generated insights focus on core transportation pr

15、ocesses;less so in7.Generated insights focus on core transportation processes;less so inkey enabling areaskey enabling areasAbout three in four respondents say gen AI is driving insights that help improve traceability or enable dynamic supply chain decisions.Two in three say insights help inventory

16、efficiency.Fewer than half say gen AI is generating helpful insights in customer relationship management,digital commerce and distribution,consumer insights,asset utilization,finance,and talent.8.Risk and governance and talent 8.Risk and governance and talent are transportations biggest barriers to

17、gen AI adoptioneven are transportations biggest barriers to gen AI adoptioneven among large companiesamong large companiesCompanies are moderately confident about their preparedness to adopt gen AI in strategy and operations.Confidence in tech varies with company size,but only half of companies with

18、 over$10 billion in revenue are confident in their technology infrastructure.9.Data concerns top gen AI risk factors9.Data concerns top gen AI risk factorsForty-one percent cited a data-related concern as their top risk(unauthorized use of organizational data:21%;misuse of client data:20%).One in fi

19、ve cited unintended outcomes as a key data-related concern of gen AIs rapid adoption.10.Transportation companies believe it will take more than three years for gen AI to transform their 10.Transportation companies believe it will take more than three years for gen AI to transform their industry.Othe

20、r sectors expect to industry.Other sectors expect to feel the impact much soonerfeel the impact much soonerSeven in 10 transportation companies expect it to take more than three years for gen AI to transform the transportation industry.Other sectors like financial services,energy,health care,and oth

21、ers think theyll feel the impact much sooner.Copyright 2024 Deloitte Development LLC.All rights reserved.Wide(but shallow)adoptionWide(but shallow)adoptionDespite strong early momentum,generative AI implementations in the transportation sector remain limited in scale,with most efforts still in the p

22、roof-of-concept stageCopyright 2024 Deloitte Development LLC.All rights reserved.6Gen AI implementations,although showing strong early momentum,remain limited in scale.Widespread pilots and early deployments indicate potential acceleration.Gen AI implementations,although showing strong early momentu

23、m,remain limited in scale.Widespread pilots and early deployments indicate potential acceleration.Most companies surveyed are running at least one gen AI pilot or limited implementation.But efforts are largely in the proof-of-concept realm(pilots or limited implementations).Transportation companies

24、seem to be struggling to scale,as just one in five surveyed have matured to broad implementations.Broad implementations focus primarily on core functions(strategy and operations;supply chain)rather than enabling functions like finance,IT,HR,and risk.With more than half of respondents reporting limit

25、ed implementations in strategy and operations and supply chain,adoption in these areas could accelerate quickly over the next few years.5%14%18%22%32%16%17%57%49%17%8%12%57%22%16%15%14%0%10%20%30%40%50%60%70%80%90%100%Legal,risk,and complianceHR IT and cyber Finance Supply chain Strategy and operati

26、onsMarketing and salesAt least one broad implementation At least one limited implementation PilotingEvaluatingQuestion:What is your organizations current adoption level of generative AI across the following functions?If the function does not apply to you,choose“N/A.”Notes:Marketing and sales impleme

27、ntation skews heavily toward retail and consumer products respondents.Three in five say their have broadly adopted gen AI in this area,versus one in 10 transportation companies.n=186 transportation and supply chain executives with at least one gen AI implementation within their organization.Percenta

28、ge of companies adopting gen AI across different functionsCopyright 2024 Deloitte Development LLC.All rights reserved.7The focus of broad gen AI adoption varies significantly by transportation subsector.The focus of broad gen AI adoption varies significantly by transportation subsector.Retail and co

29、nsumer product respondents are a major outlier in gen AI implementation for marketing and sales.For all other transportation subsectors,supply chain and strategy and operations are the functions with the highest adoption rates of broadly applied generative AI.First-and middle-mile players are leadin

30、g adopters in these areas.Trucking companies are relatively proactive in IT/cybersecurity and finance.Across all transportation sectors,legal,risk,and compliance,and human resources have the lowest adoption rates.0%10%20%30%40%50%60%70%Legal,risk,and complianceHR IT and cybersecurity Finance Supply

31、chain Strategy and operations Marketing and salesPercentage of respondents with at least one broad implementation Logistics providers TruckingOverallRetail/consumer product transportation and logisticsFirst-mile/middle-mileQuestion:What is your organizations current adoption level of generative AI a

32、cross the following functions?If the function does not apply to you,choose“N/A.”Notes:Logistics providers include third-party logistics,freight forwarding,and brokerages;first-mile/middle-mile includes ocean and rail freight,intermodal,inventory management,and wholesale and distribution.n=186 transp

33、ortation and supply chain executives with at least one gen AI implementation within their organization.Copyright 2024 Deloitte Development LLC.All rights reserved.Value creationValue creationAs transportation leaders move from possibilities to practicalities,choosing the right use cases,selecting ap

34、propriate tools,getting to scale,and accurately measuring progress will all be important steps.In this early phase of adoption,understanding where gen AI tools are beginning to create new value can offer critical insight.Copyright 2024 Deloitte Development LLC.All rights reserved.9As transportation

35、experiments with gen AI,core operational areas attract the most attention,and a few use cases show more early potential than others.Questions:What is your organizations current level of adoption of generative AI in the following areas?How much tangible economic value is generative AI currently creat

36、ing for your organization in the following areas?Note:n=186 transportation and supply chain executives with at least one gen AI implementation within their organization.High adoption,high impactLow adoption,high impactHigh adoption,low impactLow adoption,low impactNote:Both broad and limited impleme

37、ntations are included in analysis for this figure.No use case is No use case is being implemented being implemented broadly across more than broadly across more than 30%of respondents.30%of respondents.Customer serviceDemand planningWarehouse operations Route optimizationAsset managementFleet manage

38、mentInventory managementFinance and risk management Shipment tracking0%20%40%60%80%100%40%60%80%100%Percentage implementingEarly promiseRelatively high adoption;large majority of users already reaping benefitsInterest outstrips impactRelatively high adoption,but fewer users report high economic bene

39、fit Lagging use casesAreas with low adoption and low reported value generation(Among companies implementing each use case)(broad or limited implementation)Percentage reporting“extremely high”or“high”economic valueOverlooked opportunitiesFew implementing,but a majority report high value generationAdo

40、ption in frontline workforce productivity,recruitment,and retention is too low to measure impact.Copyright 2024 Deloitte Development LLC.All rights reserved.10Higher success is reported for qualitative goals,while more sought-after financial benefits remain elusive in realization or measurement.High

41、er success is reported for qualitative goals,while more sought-after financial benefits remain elusive in realization or measurement.Many may still be working out how to quantify gen AIs benefits or connect the technology to revenue and margin metrics.As they work toward rigorous accounting of finan

42、cial impact,organizations should also consider the value of nonfinancial outcomes that nonetheless can yield significant competitive advantage.More respondents are focused on efficiency,revenue,and cost reduction,but only a small percentage report achieving these goals.Over half of companies focused

43、 on innovation,improving client relationships,and uncovering insights report success in those areas.77%56%37%37%33%28%Improve efficiency Increase revenueReduce costsEncourageinnovation andgrowthEnhanceclients/customersrelationshipsUncover new ideasand insightsNonfinancial gen AI goalsPercentage achi

44、eving these(to very large or large extent)Lower success rate*Higher success rate*6868%13%13%56%56%5 58 8%13%13%3636%Bottom-line gen AI goalsPercentage of companies citing these as top 3 goalsQuestion:What are the top three overall benefits your organization hopes to achieve through generative AI eff

45、orts?To what extent are you achieving those benefits to date?Notes:n=186 transportation and supply chain executives with at least one gen AI implementation within their organization;*success rates among companies with each specific goal.Copyright 2024 Deloitte Development LLC.All rights reserved.11T

46、he focus of gen AIbacked insights varies by company type,and most focus on The focus of gen AIbacked insights varies by company type,and most focus on operations and assets over clients and consumers.operations and assets over clients and consumers.First-or middle-mile companies are the biggest user

47、s of insights around dynamic supply chain decisions and inventory efficiency.Trucking companies report the most use of traceability insights.Retail and consumer products organizations,not surprisingly,leverage customer-centric and digital-commerce insights more heavily than others.Broadening the bus

48、iness outcomes targeted for insights could be an opportunity for organizations to realize industry advantage.Insights driven by gen AI,by company category75%74%67%48%46%42%0%10%20%30%40%50%60%70%80%90%100%ImprovedtraceabilityEnabling dynamicsupply chaindecisionsImproved inventoryefficiencyCustomerre

49、lationshipmanagementDigital commerceand distributionstrategyConsumer insightsPercentage of companiesVery few respondents deriving insights related to:Asset utilization(25%)Financial settlement and payments(13%)Dynamic pricing(12%)Workforce(9%)Client-and consumer-relatedSupply chain,assets,and invent

50、oryLogistics providers Question:What types of business insights is generative AI helping to drive in your organization?Please select all that apply.(Note:First-and middle-mile includes ocean,rail freight,intermodal,inventory management,and wholesale.)Note:n=186 transportation and supply chain execut

51、ives with at least one gen AI implementation within their organization.TruckingOverallRetail/consumer product transportation and logisticsFirst-mile/middle-mileCopyright 2024 Deloitte Development LLC.All rights reserved.Clear challengesClear challengesNew technologies often need time to mature,and t

52、ransportation leaders are confronting some hard realities as they seek to deploy gen AI to gain advantage in a fast-changing industry.Transportation leaders assessment of their companies readiness for broad AI adoption reveals some key barriers that are likely slowing the progression from proof of c

53、oncept to large-scale deployment.By understanding and addressing the biggest hurdles,barriers,and risks,organizations can pave the way for smoother gen AI integration,unlocking its transformative potential and driving innovation in the industry.Copyright 2024 Deloitte Development LLC.All rights rese

54、rved.13Most transportation companies expect gen AIdriven industry transformation Most transportation companies expect gen AIdriven industry transformation to take over three years to occur,lagging other industries where the impact is to take over three years to occur,lagging other industries where t

55、he impact is expected sooner.expected sooner.Percentage of companies expecting gen AI to transform their industry*0%10%20%30%40%50%60%70%80%It already isIn less thanone yearIn one tothree yearsBeyondthree yearsNeverGPSERISeven in 10 transportation companies believe it will take gen AI more than thre

56、e years to transform their industry.Other sectors like financial services,energy,and health care expect to feel the impact much sooner.FSILSHCTMTTransportationQuestion:When is generative AI likely to substantially transform your organization and the broader industry,if at all?Notes:n=210 transportat

57、ion and supply chain executives;*industries are energy,resources,and industrials(ERI);financial services industry(FSI);life sciences and health care(LSHC);technology,media,and telecommunications(TMT);and government and public services(GPS).Source:Deloittes State of AI Quarterly Pulse survey;n=1,982.

58、Copyright 2024 Deloitte Development LLC.All rights reserved.14Large companies feel more prepared from strategy,operations and tech perspectives.Low confidence in risk and governance and talent is common across company sizes.Large companies feel more prepared from strategy,operations and tech perspec

59、tives.Low confidence in risk and governance and talent is common across company sizes.59%56%35%9%2%0%10%20%30%40%50%60%70%80%90%100%StrategyOperationsTechnologyinfrastructureRisk andgovernanceTalentPercentage of companiesPercentage of companies rating their organizations preparedness as“very high”or

60、“high”in each functionAnnual revenue$500M to$999M$1B to$9BOver$10BOnly half of respondents with annual revenues over$10 billion feel their technology infrastructure is ready for widespread gen AI adoption.But that is five times the share of companies that fall between$500 million and$999 million.Ove

61、rallQuestion:Consider the following areas.For each,rate your organizations level of preparedness with respect to broadly adopting generative AI tools/applications.Notes:See slide 19 for findings on how leaders in gen AI adoption in the transportation sector report levels of preparedness across funct

62、ions.n=210 transportation and supply chain executives.Copyright 2024 Deloitte Development LLC.All rights reserved.15Given low preparedness in risk management and governance,it is not surprising Given low preparedness in risk management and governance,it is not surprising that these are the most wide

63、ly reported barriers to gen AI deployment.that these are the most widely reported barriers to gen AI deployment.3%12%15%25%24%33%39%0%5%10%15%20%25%30%35%40%45%Nothing is holding our organization backLack of technical talent and skillsTech infrastructureMaturity of AI technologyExecutive commitmentG

64、overnanceRisk management%of respondentsBiggest barriers:Nearly all respondents report something holding them backOver$10B$1B to$9B$500M to$999MLarger companies especially cite risk management and governance as barriers,while tech infrastructure and tech talent garner less concern.For the smallest co

65、mpanies surveyed,executive commitment,maturity of AI technology,and tech infrastructure all stand out as bigger hurdles than for their peers whose revenue is over$1 billion.OverallQuestions:What,if anything,has most held your organization back in developing and deploying generative AI tools/applicat

66、ions?What challenges is your organization experiencing,or concerns do you foresee in using new types of data in generative AI initiatives?Please select all that apply.Note:n=210 transportation and supply chain executives.Copyright 2024 Deloitte Development LLC.All rights reserved.16Top gen AIassocia

67、ted risk(percentage of companies)21%20%19%13%24%3%Unauthorized use of organizational dataWhile there is no consensus on gen AIs biggest risk,four in 10 respondents say While there is no consensus on gen AIs biggest risk,four in 10 respondents say data-related concerns are primary.data-related concer

68、ns are primary.Misuse of client or customer data Rapid adoption causing unanticipated outcomes Intellectual property issues Other risks No concerns about potential gen AI risksOther risks Lack of confidence in results7%Noncompliance with regulations6%Lack of explainability and transparency6%Eliminat

69、ion of jobs due to automation3%Use of prohibited gen AI tools2%Question:Which of the following risks related to generative AI tools/applications is your organization most concerned about?Note:n=210 transportation and supply chain executives.Copyright 2024 Deloitte Development LLC.All rights reserved

70、.Overcoming challenges:Learning from leadersOvercoming challenges:Learning from leadersDespite the many challenges transportation companies facefrom risk and governance to tech and talentsome transportation companies are finding early success around generative AI.Leaders are not luminaries.They repo

71、rt some of the same gaps in functional readiness as everyone else and cite some of the same challenges and risks.But given their early success,there are lessons to learn from how they navigate.Copyright 2024 Deloitte Development LLC.All rights reserved.18Despite barriers,some are finding success wit

72、h gen AI already.Transportation and logistics functions in retail and consumer products companies see much Despite barriers,some are finding success with gen AI already.Transportation and logistics functions in retail and consumer products companies see much more success than traditional transportat

73、ion players.more success than traditional transportation players.Defining leadersGen AI leaders were defined as transportation companies with 11 or more generative AI implementations,reporting high economic value in at least three use case areas.74%of gen AI leaders fell within retail,consumer produ

74、cts,or wholesale transportation and logistics.Only 26%are traditional transportation companies(that is,logistics providers,trucking,first-/middle-mile providers)11 or more at-scale implementations3 or moreuse case areas with“extremely high”economic value17%17%Note:n=210 transportation and supply cha

75、in executives.Copyright 2024 Deloitte Development LLC.All rights reserved.1959%56%35%9%2%0%10%20%30%40%50%60%70%80%90%100%StrategyOperationsTechnologyinfrastructureRisk andgovernanceTalentPercentage of companiesPercentage of companies rate their organizations preparedness as very high or high in eac

76、h functionLeadersPackOverallFunctional preparedness for broad gen AI adoption:Leaders separate from the pack on strategy,operations,and tech infrastructure.In talent,risk,and Functional preparedness for broad gen AI adoption:Leaders separate from the pack on strategy,operations,and tech infrastructu

77、re.In talent,risk,and governance,they report similar gaps as everyone else.governance,they report similar gaps as everyone else.More than nine in 10 gen AI leaders feel their strategy and operations are ready for broad adoption of gen AI tools and applications.They may feel less confident about tech

78、nology infrastructure,but still rate their preparedness significantly higher than the rest of the pack.However,in risk and governance,only one in 10 leaders say their companies are prepared.Almost nobody reports high preparedness for gen AI implementation from a talent perspective.Question:Consider

79、the following areas.For each,rate your organizations level of preparedness with respect to broadly adopting generative AI tools/applications.Note:n=210 transportation and supply chain executives.Copyright 2024 Deloitte Development LLC.All rights reserved.20With talent being a universal challenge,lea

80、ders intend to address it sooner.With talent being a universal challenge,leaders intend to address it sooner.18%26%15%9%17%91%69%IncreaseNo changeDecreasePackLeadersLeaders also are significantly more likely to say they expect to increase head count because of gen AI.How do you expect your organizat

81、ions head count to change in the next 12 months because of gen AI?PackLeadersMost recognize the need for a new talent strategy due to gen AI,and one in four leaders expect that shift within a yearShare of respondents expecting to shift their talent strategy within the next year due to gen AIQuestion

82、s:When do you expect to make changes to your talent strategies because of generative AI?Which of the following best describes the full-time employee head count change you anticipate will result over the next 12 months due to the implementation of your organizations generative AI strategy?Notes:n=210

83、 transportation and supply chain executives;n=186 transportation and supply chain executives with at least one gen AI implementation within their organization.Copyright 2024 Deloitte Development LLC.All rights reserved.210%10%20%30%40%50%GovernanceframeworksPractitionertrainingGen AI advisoryboardMo

84、nitorregulatorycomplianceHuman validationof gen-AI-createdcontentDelegate anexecutiveInternal auditsExternal auditsPercentage of companiesRisk mitigation tacticsAudits are table stakes:Internal and external audits are used to similar extent across respondent types.Create conditions for sustained suc

85、cess:Leaders are more likely to have companywide frameworks and empower practitioners to succeed within them.Delegate and form committees:Leaders are less likely to assign gen AI risk management to a select few champions including delegated executives,advisory boards,and appointed humans to validate

86、 content.LeadersPackLeaders approach risks by setting up larger training and governing programs,while others are more likely to concentrate responsibility among a select few.Leaders approach risks by setting up larger training and governing programs,while others are more likely to concentrate respon

87、sibility among a select few.Question:What is your organization currently doing to actively manage the risks around your generative AI implementations?Note:n=186 transportation and supply chain executives with at least one gen AI implementation within their organization.Copyright 2024 Deloitte Develo

88、pment LLC.All rights reserved.22Charting a powerful path forward Charting a powerful path forward While the transportation industry has embraced gen AI technology,adoption remains shallow,with most efforts still in the proof-of-concept stage.Gen AI can be a powerful tool for leaders navigating a fas

89、t-changing industry environment marked by shifting trade flows,margin pressures,and increasing demand from shippers and regulators.As the technology matures across and beyond transportation,stakeholders will increasingly demand return on investment.Our research indicates three key approaches that co

90、uld help place a transportation company on the path to gen AI industry advantage:1Coordinate data and talent around clear objectivesAlign gen AI capabilities and use cases with clear business outcomes.Broadly and rigorously establish practices that ensure appropriate access to corresponding data.Emp

91、ower your workforce to adopt and engage as your organization transforms.2Implement a more holistic approach to value expectations and measurement Bottom-line goals like increased revenue may be within grasp,but measuring them requires rigor and new frameworks.Leaders should also consider gen AIs ben

92、efits in areas such as encouraging innovation and enhancing client relationships.3Ensure risk-proofing is process-driven and decentralized instead of putting a few in charge When it comes to risk,build the scaffolding that will support sustained success,rather than delegating boards and individuals

93、to make ad hoc decisions.Note:n=186 transportation and supply chain executives with at least one gen AI implementation within their organization.Copyright 2024 Deloitte Development LLC.All rights reserved.23AuthorsAuthorsLets talk.Larry HitchcockUS Transportation sector leaderDeloitte&Touche LLPEile

94、en CrowleyVice chair and US Transportation,Hospitality&Services attest leader Deloitte&Touche LLPMaggie RauchTransportation,Hospitality&Services research leaderDeloitte Services LPMauricio Garza BenavidesManaging director in Consulting Deloitte Consulting LLPKate FerraraRelationship national sector

95、leader for Transportation,Hospitality&ServicesDeloitte&Touche LLPThank youThank youThe authors would like to thank Yasir Mehboob,Josh Skwarczyk,Anand Kumar,and Upasana Naik for their contributions to this report.Deloitte Consumer Industry CenterThe Deloitte Consumer Industry Center provides premiere

96、 insights based on primary research on the most prevalent issues facing the consumer industry to help our clients run effectively and achieve superior business results.The center is your trusted source for information on leading trends and research that connect insights,issues,and solutions for Delo

97、ittes four consumer sectors:automotive;consumer products;retail,wholesale,and distribution;and transportation,hospitality,and services.About the Deloitte Transportation,Hospitality&Services practiceThe travel industry is undergoing a dramatic transition,all while juggling rising costs and labor shor

98、tages with understanding where and how to invest in technology.Todays consumers are buying into better and looking for brands that share their values around purpose,inclusion,trust,transparency,and innovation.Leaders in this rapidly shifting industry should have better insight,better innovation,and

99、a better connection to their customers.Thats why they turn to Deloitte.Driven by a relentless pursuit of innovation and the pulse of the consumer,Deloitte helps many of the worlds leading brands in the Transportation,Hospitality&Services sector align with their customers values,create lasting compet

100、itive advantages,build enduring customer relationships,and shape the future of the DeloitteDeloitte refers to one or more of Deloitte Touche Tohmatsu Limited,a UK private company limited by guarantee(“DTTL”),its network of member firms,and their related entities.DTTL and each of its member firms are

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102、ective affiliates.Certain services may not be available to attest clients under the rules and regulations of public accounting.Please see to learn more about our global network of member firms.This presentation contains general information only and Deloitte is not,by means of this presentation,rende

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