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1、As organizations rapidly deploy generative AI tools,survey respondents expect significant effects on their industries and workforces.The state of AI in 2023:Generative AIs breakout yearAugust 2023The state of AI in 2023:Generative AIs breakout yearThe latest annual McKinsey Global Survey on the curr

2、ent state of AI confirms the explosive growth of generative AI (gen AI)tools.Less than a year after many of these tools debuted,one-third of our survey respondents say their organizations are using gen AI regularly in at least one business function.Amid recent advances,AI has risen from a topic rele

3、gated to tech employees to a focus of company leaders:nearly one-quarter of surveyed C-suite executives say they are personally using gen AI tools for work,and more than one-quarter of respondents from companies using AI say gen AI is already on their boards agendas.Whats more,40 percent of responde

4、nts say their organizations will increase their investment in AI overall because of advances in gen AI.The findings show that these are still early days for managing gen AIrelated risks,with less than half of respondents saying their organizations are mitigating even the risk they consider most rele

5、vant:inaccuracy.The organizations that have already embedded AI capabilities have been the first to explore gen AIs potential,and those seeing the most value from more traditional AI capabilitiesa group we call AI high performersare already outpacing others in their adoption of gen AI tools.1The exp

6、ected business disruption from gen AI is significant,and respondents predict meaningful changes to their workforces.They anticipate workforce cuts in certain areas and large reskilling efforts to address shifting talent needs.Yet while the use of gen AI might spur the adoption of other AI tools,we s

7、ee few meaningful increases in organizations adoption of these technologies.The percent of organizations adopting any AI tools has held steady since 2022,and adoption remains concentrated within a small number of business functions.1 We define AI high performers as organizations that,according to re

8、spondents,attribute at least 20 percent of their EBIT to AI adoption.1The state of AI in 2023:Generative AIs breakout yearThe findings from the surveywhich was in the field in mid-April 2023show that,despite gen AIs nascent public availability,experimentation with the tools is already relatively com

9、mon,and respondents expect the new capabilities to transform their industries.Gen AI has captured interest across the business population:individuals across regions,industries,and seniority levels are using gen AI for work and outside of work.Seventy-nine percent of all respondents say theyve had at

10、 least some exposure to gen AI,either for work or outside of work,and 22percent say they are regularly using it in their own work.While reported use is quite similar across seniority levels,it is highest among respondents working in the technology sector and those in North America.Its early days sti

11、ll,but use of gen AI is already widespread2The state of AI in 2023:Generative AIs breakout yearRegularly usefor workRegularly use for workand outside of workRegularly useoutside of workHave tried atleast onceNoexposureDont knowAsiaPacifcDeveloping marketsEuropeGreater ChinaNorth AmericaAdvanced indu

12、striesBusiness,legal,and professional servicesConsumer goods/retailEnergy and materialsFinancial servicesHealthcare,pharma,and medical productsTechnology,media,and telecomC-suite executivesSenior managersMidlevel managersBorn in 1964 or earlierBorn 196580Born 198196MenWomen49109618111410221923151419

13、19201118133634454638336335776861452434734741405041443715212619141591116118161019161312151817178107161416181519234424235131620675171822181711933303736211824812194316637461615By ofce locationBy industryBy job titleBy ageBy gender identity18Reported exposure to generative AI tools,%of respondentsNote:F

14、igures may not sum to 100%,because of rounding.In AsiaPacifc,n=164;in Europe,n=515;in North America,n=392;in Greater China(includes Hong Kong and Taiwan),n=337;and in developing markets(includes India,Latin America,and Middle East and North Africa),n=276.For advanced industries(includes automotive a

15、nd assembly,aerospace and defense,advanced electronics,and semiconductors),n=96;for business,legal,and professional services,n=215;for consumer goods and retail,n=128;for energy and materials,n=96;for fnancial services,n=248;for healthcare,pharma,and medical products,n=130;and for technology,media,a

16、nd telecom,n=244.For C-suite respondents,n=541;for senior managers,n=437;and for middle managers,n=339.For respondents born in 1964 or earlier,n=143;for respondents born between 1965 and 1980,n=268;and for respondents born between 1981 and 1996,n=80.Age details were not available for all respondents

17、.For respondents identifying as men,n=1,025;for respondents identifying as women,n=156.The survey sample also included respondents who identifed as“nonbinary”or“other”but not a large enough number to be statistically meaningful.Source:McKinsey Global Survey on AI,1,684 participants at all levels of

18、the organization,April 1121,2023Respondents across regions,industries,and seniority levels say they are already using generative AI tools.McKinsey&CompanyOrganizations,too,are now commonly using gen AI.One-third of all respondents say their organizations are already regularly using generative AI in

19、at least one functionmeaning that 60percent of organizations with reported AI adoption are using gen AI.Whats more,40 percent of those reporting AI adoption at their organizations say their companies expect to invest more in AI overall thanks to generative AI,and 28 percent say generative AI use is

20、already on their boards agenda.The most commonly reported business functions using these newer tools are the same as those in which AI use is most common overall:marketing and sales,product and service development,and service operations,such as customer care and back-office support.This suggests tha

21、t organizations are pursuing these new tools where the most value is.In our previous research,these three areas,along with software engineering,showed the potential to deliver about 75 percent of the total annual value from generative AI use cases.3The state of AI in 2023:Generative AIs breakout yea

22、rIn these early days,expectations for gen AIs impact are high:three-quarters of all respondents expect gen AI to cause significant or disruptive change in the nature of their industrys competition in the next three years.Survey respondents working in the technology and financial-services industries

23、are the most likely to expect disruptive change from gen AI.Our previous research shows that,while all industries are indeed likely to see some degree of disruption,the level of impact is likely to vary.2 Industries relying most heavily on knowledge work are likely to see more disruptionand potentia

24、lly reap more value.While our estimates suggest that tech companies,unsurprisingly,are poised to see the highest impact from gen AIadding value equivalent to as much as 9 percent of global industry revenueknowledge-based industries such as banking(up to 5 percent),pharmaceuticals and medical product

25、s(also up to 5 percent),and education(up to 4 percent)could experience significant effects as well.By contrast,manufacturing-based industries,such as aerospace,automotives,and advanced electronics,could experience less disruptive effects.This stands in contrast to the impact of previous technology w

26、aves that affected manufacturing the most and is due to gen AIs strengths in language-based activities,as opposed to those requiring physical labor.Share of respondents reporting that their organization is regularly using generative AI in given function,%1Most regularly reported generative AI use ca

27、ses within function,%of respondents1Questions were asked of respondents who said their organizations have adopted AI in at least 1 business function.The data shown were rebased to represent all respondents.Source:McKinsey Global Survey on AI,1,684 participants at all levels of the organization,April

28、 1121,2023The most commonly reported uses of generative AI tools are in marketing and sales,product and service development,and service operations.McKinsey&CompanyMarketing and salesProduct and/or service developmentService operationsCrafting frst drafts of text documentsPersonalized marketingSummar

29、izing text documentsIdentifying trends in customer needsDrafting technical documentsCreating new product designsUse of chatbots(eg,for customer service)Forecasting service trends or anomalies Creating frst drafts of documents988754655Marketingand sales14Product and/or servicedevelopment13Serviceoper

30、ations10Risk4Strategy andcorporatefnance4HR3Supply chainmanagement3Manufacturing22“The economic potential of generative AI:The next productivity frontier,”McKinsey,June 14,2023.4The state of AI in 2023:Generative AIs breakout yearMcKinsey commentaryAlex Singla Senior partner and global leader of Qua

31、ntumBlack,AI by McKinseyIts amazing how quickly the conversation around generative AI has evolved.Just a few months ago,the conversation in the C-suite was pretty rudimentary,focused on trying to understand what it was and seeing what was hype versus what was reality.Now in just about six months,bus

32、iness leaders are having much more sophisticated conversations.As we can see from the survey results,almost a third of companies are using generative AI in at least one business function.This underscores the degree to which companies understand and accept that generative AI is viable in business.The

33、 next question will be how companies will take the next step,and whether generative AI will follow the same pattern we observed with AI more generally,where adoption has plateaued at around the 50 percent mark.We see from the data that the promise of generative AI is leading almost half of companies

34、 already using AI to plan on increasing their investments in AI,driven in part by the understanding that broader capabilities are needed to take full advantage of generative AI.Taking that next step,where generative AI can go from experiment to business engine,and ensuring a strong return on the inv

35、estment requires companies to tackle a broad array of issues.Those include identifying the specific opportunities for generative AI in the organization,what the governance and operating model should be,how to best manage third parties(such as cloud and large language model providers),what is needed

36、to manage the wide range of risks,understanding the implications on people and the tech stack,and being clear about how to find the balance between banking near-term gains and developing the long-term foundations needed to scale.These are complex issues,but they are the key to unlocking the really s

37、ignificant pools of value out there.5The state of AI in 2023:Generative AIs breakout yearGenerative AIrelated risks that organizations consider relevant and are working to mitigate,%of respondents11Asked only of respondents whose organizations have adopted Al in at least 1 function.For both risks co

38、nsidered relevant and risks mitigated,n=913.Source:McKinsey Global Survey on AI,1,684 participants at all levels of the organization,April 1121,2023Inaccuracy,cybersecurity,and intellectual-property infringement are the most-cited risks of generative AI adoption.McKinsey&CompanyInaccuracyCybersecuri

39、tyIntellectual-property infringement Regulatory complianceExplainabilityPersonal/individual privacyWorkforce/labor displacementEquity and fairness Organizational reputationNational securityPhysical safetyEnvironmental impact Political stabilityNone of the above56Organization considers risk relevantO

40、rganization working to mitigate risk534645393934312914111110132382528182013161646528Responses show many organizations not yet addressing potential risks from gen AIAccording to the survey,few companies seem fully prepared for the widespread use of gen AIor the business risks these tools may bring.Ju

41、st 21 percent of respondents reporting AI adoption say their organizations have established policies governing employees use of gen AI technologies in their work.And when we asked specifically about the risks of adopting gen AI,few respondents say their companies are mitigating the most commonly cit

42、ed risk with gen AI:inaccuracy.Respondents cite inaccuracy more frequently than both cybersecurity and regulatory compliance,which were the most common risks from AI overall in previous surveys.Just 32 percent say theyre mitigating inaccuracy,a smaller percentage than the 38percent who say they miti

43、gate cybersecurity risks.Interestingly,this figure is significantly lower than the percentage of respondents who reported mitigating AI-related cybersecurity last year(51 percent).Overall,much as weve seen in previous years,most respondents say their organizations are not addressing AI-related risks

44、.6The state of AI in 2023:Generative AIs breakout yearMcKinsey commentaryAlexander Sukharevsky Senior partner and global leader of QuantumBlack,AI by McKinseyThere is broad awareness about the risks associated with generative AI.But at the same time,the prevailing anxiety and fear is making it chall

45、enging for leaders to effectively address the risks.As our latest survey shows,just a little over 20 percent of companies have risk policies in place for generative AI.Those policies tend to focus on protecting a companys proprietary information,such as data,knowledge,and other intellectual property

46、.Those are critical,but weve found that many of these risks can be addressed by making changes in the businesss technology architecture that reflect established policies.The real trap,however,is that companies look at the risk too narrowly.There is a significant range of riskssocial,humanitarian,sus

47、tainabilitythat companies need to pay attention to as well.In fact,the unintended consequences of generative AI are more likely to create issues for the world than the doomsday scenarios that some people espouse.Companies that are approaching generative AI most constructively are experimenting with

48、and using it while having a structured process in place to identify and address these broader risks.They are putting in place beta users and specific teams that think about how generative AI applications can go off the rails to better anticipate some of those consequences.They are also working with

49、the best and most creative people in the business to define the best outcomes for both the organization and for society more generally.Being deliberate,structured,and holistic about understanding the nature of the new risksand opportunitiesemerging is crucial to the responsible and productive growth

50、 of generative AI.7The state of AI in 2023:Generative AIs breakout yearThe survey results show that AI high performersthat is,organizations where respondents say at least 20 percent of EBIT in 2022 was attributable to AI useare going all in on artificial intelligence,both with gen AI and more tradit

51、ional AI capabilities.These organizations that achieve significant value from AI are already using gen AI in more business functions than other organizations do,especially in product and service development and risk and supply chain management.When looking at all AI capabilitiesincluding more tradit

52、ional machine learning capabilities,robotic process automation,and chatbotsAI high performers also are much more likely than others to use AI in product and service development,for uses such as product-development-cycle optimization,adding new features to existing products,and creating new AI-based

53、products.These organizations also are using AI more often than other organizations in risk modeling and for uses within HR such as performance management and organization design and workforce deployment optimization.Another difference from their peers:high performers gen AI efforts are less oriented

54、 toward cost reduction,which is a top priority at other organizations.Respondents from AI high performers are twice as likely as others to say their organizations top objective for gen AI is to create entirely new businesses or sources of revenueand theyre most likely to cite the increase in the val

55、ue of existing offerings through new AI-based features.Leading companies are already ahead with gen AI8The state of AI in 2023:Generative AIs breakout yearAs weve seen in previous years,these high-performing organizations invest much more than others in AI:respondents from AI high performers are mor

56、e than five times more likely than others to say they spend more than 20 percent of their digital budgets on AI.They also use AI capabilities more broadly throughout the organization.Respondents from high performers are much more likely than others to say that their organizations have adopted AI in

57、four or more business functions and that they have embedded a higher number of AI capabilities.For example,respondents from high performers more often report embedding knowledge graphs in at least one product or business function process,in addition to gen AI and related natural-language capabilitie

58、s.While AI high performers are not immune to the challenges of capturing value from AI,the results suggest that the difficulties they face reflect their relative AI maturity,while others struggle with the more foundational,strategic elements of AI adoption.Respondents at AI high performers most ofte

59、n point to models and tools,such as monitoring model performance in production and retraining models as needed over time,as their top challenge.By comparison,other respondents cite strategy issues,such as setting a clearly defined AI vision that is linked with business value or finding sufficient re

60、sources.Top objective for organizations planned generative AI activities,%of respondents1Note:Figures do not sum to 100%,because of rounding.1Asked only of respondents whose organizations have adopted Al in at least 1 function.2Respondents who said that at least 20 percent of their organizations EBI

61、T in 2022 was attributable to their use of AI.For respondents at AI high performers,n=45;for all other respondents,n=712.Source:McKinsey Global Survey on AI,1,684 participants at all levels of the organization,April 1121,2023Smaller shares of AI high performers see cost reductions as their top objec

62、tive for generative AI eforts.McKinsey&CompanyIncrease value of oferingsby integrating AI-basedfeatures or insightsIncrease revenuefrom core businessCreate new businessesand/or sources of revenueReduce costs incore businessRespondents atAI high performers2All otherrespondents30332721100%231219339The

63、 state of AI in 2023:Generative AIs breakout yearThe findings offer further evidence that even high performers havent mastered best practices regarding AI adoption,such as machine-learning-operations(MLOps)approaches,though they are much more likely than others to do so.For example,just 35 percent o

64、f respondents at AI high performers report that where possible,their organizations assemble existing components,rather than reinvent them,but thats a much larger share than the 19 percent of respondents from other organizations who report that practice.Many specialized MLOps technologies and practic

65、es may be needed to adopt some of the more transformative uses cases that gen AI applications can deliverand do so as safely as possible.Live-model operations is one such area,where monitoring systems and setting up instant alerts to enable rapid issue resolution can keep gen AI systems in check.Hig

66、h performers stand out in this respect but have room to grow:one-quarter of respondents from these organizations say their entire system is monitored and equipped with instant alerts,compared with just 12 percent of other respondents.Element that poses the biggest challenge in capturing value from A

67、I,%of respondents1Note:Figures do not sum to 100%,because of rounding.1Asked only of respondents whose organizations have adopted Al in at least 1 function.2Respondents who said that at least 20 percent of their organizations EBIT in 2022 was attributable to their use of AI.For respondents at AI hig

68、h performers,n=49;for all other respondents,n=792.Source:McKinsey Global Survey on AI,1,684 participants at all levels of the organization,April 1121,2023Models and tools pose the biggest AI-related challenge for high performers,while strategy is a common stumbling block for others.McKinsey&CompanyS

69、trategyOtherDataTechnologyAdoption and scalingTalentModels and toolsRespondents atAI high performers2All otherrespondents100%242011621242191311115131810The state of AI in 2023:Generative AIs breakout yearMcKinsey commentaryBryce HallAssociate partnerOver the past six years as weve conducted our annu

70、al global AI research,one consistent finding is that high performers take a broad view of whats needed to be successful.They are particularly strong in staying focused on value,and then rewiring their organization to capture that value.This pattern is clear when looking at how high performers are wo

71、rking with generative AI as well.For example,on strategy,leaders from our analysis are mapping out where the high-value opportunities are from AI across their business domains.Tellingly,theyre not doing this for only generative AI.As excited as we all are about the dazzling new gen AI applications,s

72、ignificantly more than half of the potential value for companies comes from AI applications that dont use gen AI.They are maintaining discipline in viewing the full range of AI opportunities based on potential value.That approach extends to all capability areas.In technology and data,for example,hig

73、h performers are laser focused on capabilities needed to capture the value theyve identified.This includes capabilities to enable large language models to train on company and industry-specific data.Theyre evaluating and testing the efficiencies and speed enabled by consuming existing AI services(wh

74、at we call the“taker”approach)and developing capabilities to create competitive advantagefor example,by tuning models and training them to use their own proprietary data(what we call the“shaper”approach).11The state of AI in 2023:Generative AIs breakout yearOur latest survey results show changes in

75、the roles that organizations are filling to support their AI ambitions.In the past year,organizations using AI most often hired data engineers,machine learning engineers,and Al data scientistsall roles that respondents commonly reported hiring in the previous survey.But a much smaller share of respo

76、ndents report hiring AI-related-software engineersthe most-hired role last yearthan in the previous survey(28 percent in the latest survey,down from 39 percent).Roles in prompt engineering have recently emerged,as the need for that skill set rises alongside gen AI adoption,with 7 percent of responde

77、nts whose organizations have adopted AI reporting those hires in the past year.AI-related talent needs shift,and AIs workforce effects are expected to be substantial12The state of AI in 2023:Generative AIs breakout yearThe findings suggest that hiring for AI-related roles remains a challenge but has

78、 become somewhat easier over the past year,which could reflect the spate of layoffs at technology companies from late 2022 through the first half of 2023.Smaller shares of respondents than in the previous survey report difficulty hiring for roles such as AI data scientists,data engineers,and data-vi

79、sualization specialists,though responses suggest that hiring machine learning engineers and AI product owners remains as much of a challenge as in the previous year.Share of respondents reporting difculty in organizations hiring of AI-related roles,1%1Asked only of respondents whose organizations ha

80、ve adopted Al in at least 1 function and who said their organization hired the given role in the past12 months.Respondents who said“easy,”“neither difcult nor easy,”or“dont know”are not shown.2Not asked of respondents in 2022.Source:McKinsey Global Survey on AI,1,684 participants at all levels of th

81、e organization,April 1121,2023Hiring for AI-related roles remains a challenge,though reported difculty has decreased since 2022 for many roles.McKinsey&CompanyMachine learning engineersAI data scientistsTranslatorsAI product owners/managersData architectsPrompt engineers2Software engineersData engin

82、eersDesign specialistsData-visualization specialists0LESS DIFFICULTMORE DIFFICULT204060801002022202313The state of AI in 2023:Generative AIs breakout yearLooking ahead to the next three years,respondents predict that the adoption of AI will reshape many roles in the workforce.Generally,they expect m

83、ore employees to be reskilled than to be separated.Nearly four in ten respondents reporting AI adoption expect more than 20 percent of their companies workforces will be reskilled,whereas 8 percent of respondents say the size of their workforces will decrease by more than 20 percent.Expectations abo

84、ut the impact of AI adoption on organizations workforces,next 3 years,%of respondents1Note:Figures may not sum to 100%,because of rounding.1Asked only of respondents whose organizations have adopted Al in at least 1 function;n=913.Source:McKinsey Global Survey on AI,1,684 participants at all levels

85、of the organization,April 1121,2023Survey respondents expect AI to meaningfully change their organizations workforces.McKinsey&CompanyChange in number of employeesShare of employees expected to be reskilledDecrease by 20%Increase by 20%Decrease by 1120%Increase by 1120%Decrease by 310%Dont knowIncre

86、ase by 310%Little or no change(decrease or increase by 2%)85%20610%171120%1820%38Dont know83104251283014The state of AI in 2023:Generative AIs breakout yearLooking specifically at gen AIs predicted impact,service operations is the only function in which most respondents expect to see a decrease in w

87、orkforce size at their organizations.This finding generally aligns with what our recent research suggests:while the emergence of gen AI increased our estimate of the percentage of worker activities that could be automated(60 to 70percent,up from 50 percent),this doesnt necessarily translate into the

88、 automation of an entire role.Efect of generative AI adoption on number of employees,by business function,next 3 years,%of respondents1Note:Figures may not sum to 100%,because of rounding.1Respondents were asked about only the business functions in which they said their organizations have adopted Al

89、.Source:McKinsey Global Survey on AI,1,684 participants at all levels of the organization,April 1121,2023Service operations is the only function in which most respondents expect to see a decrease in workforce size because of generative AI.McKinsey&CompanyProduct and/or service developmentDecreaseInc

90、reaseDont knowLittle or no changeRiskStrategy and corporate fnanceMarketing and salesSupply chain managementService operations30313739455435372833322320202517141215121012HR41301711910Manufacturing4033121515The state of AI in 2023:Generative AIs breakout yearShare of employees at respondents organiza

91、tion expected to bereskilled over the next 3 years as a result of AI adoption,%of respondents11Asked only of respondents whose organizations have adopted Al in at least 1 function.2Respondents who said that at least 20 percent of their organizations EBIT in 2022 was attributable to their use of AI.F

92、or respondents at AI high performers,n=50;for all other respondents,n=863.Source:McKinsey Global Survey on AI,1,684 participants at all levels of the organization,April 1121,2023Respondents at AI high performers expect their organizations to reskill larger portions of the workforce than other respon

93、dents do.McKinsey&Company1120%2130%30%Dontknow10%Respondents atAI high performers2All otherrespondents739108938211814AI high performers are expected to conduct much higher levels of reskilling than other companies are.Respondents at these organizations are over three times more likely than others to

94、 say their organizations will reskill more than 30 percent of their workforces over the next three years as a result of AI adoption.16The state of AI in 2023:Generative AIs breakout yearMcKinsey commentaryLareina YeeSenior partner,McKinsey;chair,McKinsey Technology CouncilWe are in the early innings

95、 of generative AI,and companies already anticipate a meaningful impact on talentfrom opening up new work opportunities and transforming how work gets done to introducing whole new job categories such as prompt engineering.One of the benefits of generative AI is that it can help nearly everyone with

96、their jobs,and this is also its greatest challenge.This scale differs from traditional AI,which affected a fairly smallthough no less importantportion of the workforce who had deep skills in technical areas like machine learning,data science,or robotics.Given the highly specialized capabilities requ

97、ired,AI talent always seemed in short supply.Our survey highlights that hiring for these roles is still a challenge.Generative AI,in contrast,will still need highly skilled people to build large language models and train generative models,but users can be nearly anyone,and they wont need data scienc

98、e degrees or machine learning expertise to be effective.The analogy is similar to the move from mainframe computerslarge machines operated by highly technical expertsto the personal computer,which anyone could use.Its a revolutionary shift in terms of how people can use technology as a power tool.Th

99、is view of generative AI as a tool is reflected in our survey.In most instances companies see generative AI as a tool to augment human activities,not necessarily replace them.So far,were mainly seeing companies that are leaning forward with generative AI,focusing on pragmatic areas where the routes

100、to improvements in top-line growth or productivity are clearest.Examples include using generative AI tools to help modernize legacy code or speed up research and discovery time in the sciences.Were still just scratching the surface of these augmentation capabilities,and we can anticipate that their

101、use will accelerate.17The state of AI in 2023:Generative AIs breakout yearWhile the use of gen AI tools is spreading rapidly,the survey data doesnt show that these newer tools are propelling organizations overall AI adoption.The share of organizations that have adopted AI overall remains steady,at l

102、east for the moment,with 55 percent of respondents reporting that their organizations have adopted AI.Less than a third of respondents continue to say that their organizations have adopted AI in more than one business function,suggesting that AI use remains limited in scope.Product and service devel

103、opment and service operations continue to be the two business functions in which respondents most often report AI adoption,as was true in the previous four surveys.And overall,just 23 percent of respondents say at least 5 percent of their organizations EBIT last year was attributable to their use of

104、 AIessentially flat with the previous surveysuggesting there is much more room to capture value.With all eyes on gen AI,AI adoption and impact remain steady18The state of AI in 2023:Generative AIs breakout yearNumber of business functions at respondents organizations that have adopted AI,%of respond

105、ents11In 2021,n=1,843;in 2022,n=1,492;in 2023,n=1,684.Source:McKinsey Global Survey on AI,1,684 participants at all levels of the organization,April 1121,2023Less than one-third of respondents say their organizations use AI in more than one functiona share largely unchanged since 2021.McKinsey&Compa

106、ny1 or more functions2 or more functions3 or more functions4 or more functions5 or more functions56505520212022202331273120212022202314171620212022202369620212022202324320212022202319The state of AI in 2023:Generative AIs breakout yearMore than two-thirds of respondents expect their organizations to

107、 increase their AI investment over the next three years.Cost decreases from AI adoption in 2022,%of respondents1Revenue increases from AI adoption in 2022,%of respondents21Question was asked only of respondents who said their organizations have adopted AI in a given function.Respondents who said“cos

108、t increase,”“no change,”“not applicable,”or“dont know”are not shown.2Question was asked only of respondents who said their organizations have adopted AI in a given function.Respondents who said“revenue decrease,”“no change,”“not applicable,”or“dont know”are not shown.Source:McKinsey Global Survey on

109、 AI,1,684 participants at all levels of the organization,April 1121,2023Organizations continue to see benefts from AI adoption in the functions using AI capabilities.McKinsey&CompanyHuman resourcesManufacturingMarketing and salesR&D/product and/or service developmentRiskService operationsStrategy an

110、d corporate fnanceSupply chain managementAverage across all functionsHuman resourcesManufacturingMarketing and salesR&D/product and/or service developmentRiskService operationsStrategy and corporate fnanceSupply chain managementAverage across all functions20%1019%10%610%5%410264014415541126414918315

111、132644812345475193192433410284293417601616346681938651225246113163564101433571016325823330566183559Organizations continue to see returns in the business areas in which they are using AI,and they plan to increase investment in the years ahead.We see a majority of respondents reporting AI-related reve

112、nue increases within each business function using AI.And looking ahead,more than two-thirds expect their organizations to increase their AI investment over the next three years.20The state of AI in 2023:Generative AIs breakout yearAbout the researchThe online survey was in the field April 11 to 21,2

113、023,and garnered responses from 1,684 participants representing the full range of regions,industries,company sizes,functional specialties,and tenures.Of those respondents,913 said their organizations had adopted AI in at least one function and were asked questions about their organizations AI use.To

114、 adjust for differences in response rates,the data are weighted by the contribution of each respondents nation to global GDP.The survey content and analysis were developed by Michael Chui,a partner at the McKinsey Global Institute and a partner in McKinseys Bay Area office,where Lareina Yee is a sen

115、ior partner;Bryce Hall,an associate partner in the Washington,DC,office;and senior partners Alex Singla and Alexander Sukharevsky,global leaders of QuantumBlack,AI by McKinsey,based in the Chicago and London offices,respectively.They wish to thank Shivani Gupta,Abhisek Jena,Begum Ortaoglu,Barr Seitz

116、,and Li Zhang for their contributions to this work.McKinsey commentaryMichael ChuiPartner,McKinsey Global InstituteWeve been emphasizing the importance of generative AIand for good reason,given its revolutionizing potentialbut this survey is a good reminder that theres a lot of value out there in th

117、e broader AI world.In fact,some of our other research indicates that nongenerative AI has even more value potential than generative AI.Use cases in areas such as improvements in forecasting accuracy,optimizing logistics networks,and providing next-product-to-buy recommendations can all generate valu

118、e for companies that can take advantage of the broader AI promise.While reported overall AI adoption remains steady at around 55 percent,more than two-thirds of respondents say their companies plan on increasing their investments in AI.And we continue to see a set of AI high performers that are buil

119、ding out the foundations and capabilities that allow them to generate value.One way to interpret this is that“the rich are getting richer”when it comes to extracting value from AI.Well be interested in seeing whether the great interest in generative AI opens the door to higher overall adoption of AI going forward.21The state of AI in 2023:Generative AIs breakout yearQuantumBlack AI,by McKinsey August 2023 Copyright McKinsey&Company Designed by McKinsey Global PublishingMcK McKinsey McKinseyScan Download PersonalizeFind more content like this on the McKinsey Insights App