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1、In collaboration withNovember 2024Learning to Manage Uncertainty,With AIby Sam Ransbotham,David Kiron,Shervin Khodabandeh,Michael Chu,and Leonid ZhukhovAUTHORSSam Ransbotham is a professor of analytics at the Carroll School of Management at Boston College,as well as guest editor for MIT Sloan Manage

2、ment Reviews Artificial Intelligence and Business Strategy Big Ideas initiative.David Kiron is the editorial director,research,of MIT Sloan Management Review and program lead for its Big Ideas research initiatives.Shervin Khodabandeh is a senior partner and managing director at Boston Consulting Gro

3、up(BCG)and the coleader of its AI business in North America.He is a leader in BCG X and has over 20 years of experience driving business impact from AI and digital.He can be contacted at .Michael Chu is a vice president of data science at BCG,where he focuses on applying AI and machine learning to b

4、usiness problems in commercial functions,including optimizing pricing,promotions,sales,and marketing.He can be reached at .Leonid Zhukhov is a vice president of data science at BCG and leads the Tech&Biz Lab at the BCG Henderson Institute.He leads the design and build of AI and machine learning solu

5、tions for BCG clients across a range of sectors.He can be reached at .CONTRIBUTORSFranois Candelon,Todd Fitz,Kevin Foley,Sarah Johnson,Michele Lee DeFilippo,Meenal Pore,Namrata Rajagopal,Allison Ryder,Barbara Spindel,and David Zuluaga MartnezThe research and analysis for this report was conducted un

6、der the direction of the authors as part of an MIT Sloan Management Review research initiative in collaboration with and sponsored by Boston Consulting Group.To cite this report,please use:S.Ransbotham,D.Kiron,S.Khodabandeh,M.Chu,and L.Zhukov,“Learning to Manage Uncertainty,With AI,”MIT Sloan Manage

7、ment Review and Boston Consulting Group,November 2024.REPRINT#:66262Copyright Massachusetts Institute of Technology,2024.All rights reserved.SUPPORTING SPONSORSCONTENTS1 Uncertainty Abounds 2 Combining Organizational Learning and AI-specific Learning Leads to Augmented Learning4 Augmented Learners A

8、re Better Prepared for Many Types of Uncertainty 8 Three Ways to Enhance Organizational Learning With AI 11 Developing Augmented Learning Capabilities 13 Learning With AI Is Key to Navigating Uncertainty14 Appendix:The State of AI in Business Uncertainty AboundsUncertainty is all about the unknown.T

9、he less an organi-zation knows,the greater its uncertainty and the less able it is to manage resources effectively.Managing uncertainty,therefore,requires learning.Companies need to learn more,and more quickly,to manage uncertainty.Addressing uncertainty constitutes a pressing challenge for leadersh

10、ip,especially today,when geopolitical tensions,fast-moving consumer preferences,talent disruptions,shifting regulations,and rapidly evolving technologies complicate the business environment.Companies need better tools and perspectives for learning to manage uncertainty arising from these and other b

11、usiness disrup-tions.Our research finds that a major source of uncertainty,artificial intelligence,is also critical to meeting this chal-lenge.Specifically:Companies that boost their learning capabilities with AI are significantly better equipped to handle uncertainty from technological,regulatory,a

12、nd talent-related dis-ruptions compared with companies that have limited learning capabilities.The Este Lauder Companies(ELC)offers a case in point.The cosmetics company has a strategic need to anticipate consumer trends ahead of its competitors.In earlier times,consumer preferences might have shift

13、ed seasonally.Now,preferences are less certain;shifts happen more quickly due to social media and digital influencers.Fashion trends can change by the week.If the color peach suddenly captures the publics interest,the company needs to discern that trend as quickly as possible.It uses AI to detect an

14、d rap-idly respond to consumer trends.Sowmya Gottipati,vice president of global supply chain technology at ELC,reports that the company,which carries products across more than 20 brands and“hundreds of different shades,”uses fuzzy matching to figure out which products can meet the demand and delight

15、 consumers.“We are looking to AI to discover consumer trends and then match up our existing products to the trends so that we can repackage them and position them in the market for that trend,”Gottipati explains.ELC uses AI to detect sudden changes and have a market response ready so it can redeploy

16、 inventory and supply chain pro-cesses to meet demand efficiently.Companies cant control the changes but can use AI to manage their responses.ELC is not alone:The company is among the 15%of orga-nizations that integrate AI into their learning capabilities.These organizations what we refer to as Augm

17、ented Learners are 1.6 times more likely than those with lim-ited learning capabilities to manage various environmental and company-specific uncertainties,including unexpected technological,regulatory,and workforce changes.These companies are twice as likely to be prepared to manage talent-related d

18、isruptions compared with organizations that have limited learning capabilities.Whats more,these organizations are 60%-80%more likely to be effective at managing uncertainties in their external environments than Limited Learners companies with limited learning capabilities.By doing so,they reap advan

19、tages with AI well beyond direct financial benefits.Based on a global survey of 3,467 respondents and inter-views with nine executives,our research quantitatively and qualitatively establishes a relationship between organiza-tional learning,learning with AI,and the ability to manage rapidly changing

20、 business environments.Organizational learning itself has long been associated with improved per-formance.Integrating AI with an organizations learning capabilities significantly improves corporate responses to uncertainties from talent mobility,new technology,and related regulations.This report def

21、ines an AI-enhanced organizational learning capability(augmented learning),explains its use in reducing the considerable uncertainty managers face today,and offers key takeaways for exploit-ing these new abilities.Companies need to learn more,and more quickly,to manage uncertainty.Learning to Manage

22、 Uncertainty,With AI1Combining Organizational Learning and AI-specific Learning Leads to Augmented LearningOrganizational learning is an organizations capability to change its knowledge through experience.1 Organizations that learn from mistakes,tolerate failure,capture best practices,and support ne

23、w ideas have an advantage over organizations that dont:They learn to get better.Those that struggle to learn will struggle to navigate increasing uncertainties.Extensive past research demonstrates the benefits of general organizational learning.General organizational learning capabilities dont neces

24、-sarily depend on AI;organizations can have strong organi-zational learning capabilities without using the technology.Conversely,organizations can use AI to learn even if they dont otherwise have strong organizational learning capa-bilities.Managers can learn from generative AI tools,use AI to deepe

25、n their understanding of performance,and iter-ate with AI to develop new insights and processes.These individual learning experiences create value from AI but may not constitute an organizational learning capability.Our research finds that organizations that combine organi-zational learning with AI-

26、specific learning Augmented Learners outperform organizations that employ either approach in isolation.As businesses adopt AI and embrace successively more powerful AI tools in various contexts,they have new opportunities to strengthen their learning capa-bilities for both human workers and their ma

27、chines.Our prior research,“Expanding AIs Impact With Organizational Learning,”found that organizations with superior learning capabilities are more likely to obtain significant financial ben-efits from their AI use.2 In our latest research,we find that the reverse is also true:Using AI can improve o

28、rganizational learning capabilities,and these learning improvements are tied to not only enhanced financial results but also the ability to manage strategy-related uncertainties.Assessing Learning CapabilitiesOur survey instrument measured each enterprises orga-nizational learning capability using f

29、ive questions.We also assessed how individuals and systems learn with AI through a different set of four questions.Together,these questions probe several aspects of organizational learning and AI-specific learning:knowledge capture,synthesis,and dissemination.(see figure 1,page 3.)ABOUT THE RESEARCH

30、This report presents findings from the eighth annual global research study on artificial intelligence and busi-ness strategy by MIT Sloan Management Review and Boston Consulting Group.In spring 2024,we fielded a global survey and subsequently analyzed records from 3,467 respondents representing more

31、 than 21 industries and 136 countries.We also interviewed nine executives leading AI initiatives in a broad range of companies and industries,including financial services,technology,retail,travel and transportation,and health care.Our research connects organizational learning,learning with AI,and th

32、e ability to manage rapidly changing environ-ments.This report defines an AI-enhanced organizational learning capability,explains its use in reducing several types of uncertainty managers face today,and offers key leader-ship takeaways for exploiting these new abilities.To assess whether organizatio

33、ns have“high”or“low”organizational and AI-specific learning capabilities,we analyzed survey responses to these statements using an agree-disagree Likert scale:My organization learns through experiments.(organi-zational learning)My organization tolerates failures in experiments.(organizational learni

34、ng)My organization learns from postmortems on both successful and failed projects.(organizational learning)My organization codifies its learning from initiatives.(organizational learning)My organization gathers and shares information that employees learn.(organizational learning)My organizations use

35、 of AI leads to new learning.(AI-specific learning)My organization uses AI to learn from performance.(AI-specific learning)My organization builds AI solutions with human feed-back loops.(AI-specific learning)Employees in my organization learn from AI solutions.(AI-specific learning)We then grouped r

36、espondents into four categories:Limited Learners,Organizational Learners,AI-specific Learners,and Augmented Learners.(See Figure 2,page 3 For theSe breakdownS.)2MIT SLOAN MANAGEMENT REVIEW BCGBecoming adept at these learning activities which rep-resent only a slice of an organizations overall learni

37、ng capability significantly improves a companys ability to manage uncertainty.Most Companies Have Limited Learning CapabilitiesGiven the uncertainties facing many companies,its strik-ing that most organizations have limited learning capabili-ties;59%of all companies represented in our sample report

38、low levels of both organizational learning and AI-specific learning.Only 29%of respondents agree or strongly agree that their enterprise has organizational learning capabili-ties.While 27%of organizations report learning with AI,only 15%combine AI-specific learning with organizational learning capab

39、ilities.These Augmented Learners are the focus of this report.Learns through experiments and tolerates failure Supports employees presenting new ideas Learns from postmortems on successful and failed projects Codifies learning from initiatives Gathers and shares information that employees learnOrgan

40、izational learningAI-specific learning Uses AI to lead to new learning Uses AI to learn from performance Builds AI solutions with human feedback loops Enables employees to learn from AI solutionsFIGURE 1 Characteristics of Organizational Learning and AI-specific LearningWe outline characteristics of

41、 organizational and AI-specific learning based on nine survey questions.12%15%59%14%AI-specific LearningOrganizational LearningLowAI-specific LearnersLimited LearnersOrganizational LearnersAugmented LearnersHighLowHighFIGURE 2 Learning Capabilities VaryOnly 15%of organizations are Augmented Learners

42、 organizations that enhance organizational learning with AI.OrganizatiOnal learning An organizations capability to change its knowledge through experience.ai-specific learningThe measure of organizations use of AI for learning.augmented learnersOrganizations that score high on organizational learnin

43、g and AI-specific learning.limited learnersOrganizations that score low on organizational learning and AI-specific learning.In our global survey,we assessed an organization as having“high”or“low”organizational and AI learning capabilities.For more detail,see“About the Research,”page 2.Learning to Ma

44、nage Uncertainty,With AI3Limited learning capabilities constrain opportunities and undermine organizations ability to manage uncertainty.Augmented Learners Are Better at Managing UncertaintyAmong our sample,15%of organizations report high lev-els of both organizational learning and AI-specific learn

45、ing.These Augmented Learners display abilities and advantages that lead to better outcomes than organizations with limited capabilities.They are more likely to improve financial out-comes with AI than Limited Learners:99%of Augmented Learners report annualized revenue benefits from AI.(see sidebar,“

46、enhancing OrganizatiOnal learning With ai imprOves financial OutcOmes,”page 5.)Whats more,they are much more likely to be prepared to deal with uncer-tainty from talent,technology,and legal disruptions.Figure 3 shows that organizational learning alone or AI-specific learning alone offers some benefi

47、ts,but their combination represents the most powerful hedge against multiple types of uncertainty.Organizational learning with AI may well prove to be a source of resilience against other forms of disruptions or uncertainty.Augmented Learners Are Better Prepared for Many Types of UncertaintyCombinin

48、g organizational learning and AI-specific learn-ing capabilities helps enterprises manage uncertainty and disruptions from talent mobility,changing technology,and evolving regulatory and legal requirements.(see fig-ure 5,page 6.)Disruptions From Talent MobilityElevated rates of workers quitting,reti

49、ring,being laid off,or even ghosting employers create risks and ambiguities for organizations striving to compete.Shilpa Prasad is head of incubation,AI Ventures at LG Nova,the subsidiary of LG Electronics that works with startups to fuel innova-tion for the company.She observes that“60%of the work-

50、force will likely hit the age of 65 by the year 2028 or 2030,which means that a lot of knowledge will go out from the workforce because theyll retire,not because theyre going somewhere else to work.”When employees leave organi-zations,their knowledge can leave with them unless the company has effect

51、ive organizational learning capabilities.These problems are not new for organizations.In indus-tries like chemicals,aerospace,and oil and gas,retirement rates have been an increasing cause for alarm for years.However,companies have new resources to address these challenges.Augmented learning is a va

52、luable resource for addressing disruptions from talent mobility.Only 39%of organizations with limited learning feel prepared to han-dle the disruption in knowledge from departing employ-ees,but this readiness increases to 64%if the companies have organizational learning capabilities.Using AI can fur

53、ther contribute to this readiness:Eighty-three percent of Augmented Learners are prepared to deal with the uncertainty of knowledge disruption from talent mobil-ity twice as much as Limited Learners.1.653%58%76%82%Limited LearnersOrganizational LearnersAI-specific LearnersAugmented LearnersAI will a

54、llow us to manage uncertainty in our industry.Percentage of respondents in each learning category who strongly agree or agree with the above statement.FIGURE 3 Learning With AI Helps Organizations Manage UncertaintyOrganizations that combine organizational and AI-specific learning(Augmented Learners

55、)are 1.6 times more likely to feel prepared to manage uncertainty than organizations with limited learning capabilities.4MIT SLOAN MANAGEMENT REVIEW BCGSIDEBAR ENHANCING ORGANIZATIONAL LEARNING WITH AI IMPROVES FINANCIAL OUTCOMESNumerous studies now show the direct financial benefits of AI adoption.

56、Clearly,organizations are finding ways to extract financial benefits through AI,even if many such efforts fail or their costs exceed revenues.Extensive past research also surfaces the general benefits of organizational learning for companies.In prior research,we found that organizations with superio

57、r learning capabilities are more likely to obtain signifi-cant financial benefits from their AI use than organizations with lesser learning capabilities.In this study,we find that using AI can improve organizational learning capabilities and that these learning improvements are similarly tied to imp

58、roved financial results.Organizations using AI to improve organizational learning are 1.4 times more likely Over the past three years,AI has created additional business value.Limited LearnersOrganizational LearnersAI-specific LearnersAugmented Learners66%76%89%95%1.4Our organization has realized rev

59、enue benefits from AI on an annualized basis.Limited LearnersOrganizational LearnersAI-specific LearnersAugmented Learners71%72%79%99%1.4Percentage of respondents who strongly agree or agree that AI has created additional business value over the past three years.Percentage of respondents who report

60、revenue benefits from AI.FIGURE 4 Enhancing Organizational Learning With AI Leads to Financial BenefitsOrganizations that combine organizational learning and AI-specific learning(Augmented Learners)are 1.4 times as likely to realize additional business value and annualized revenue benefits from AI.t

61、o recognize some revenue benefits from AI compared with organizations with limited learning capabilities.Indeed,virtually all of these organizations(99%)recognize or observe some revenue benefits from AI.Whats more,organizations that combine AI and organizational learning are significantly more like

62、ly to have realized revenue benefits from AI compared with companies that excel at organizational learning but not learning with AI,and with companies that excel at AI-specific learning but not organizational learning.That is,combining organiza-tional learning and AI-specific learning enables organi

63、zations to cross a revenue benefit threshold that neither type of learning alone can generate.5Learning to Manage Uncertainty,With AIAs more and more workplace communications occur via digital channels,emerging AI capabilities can make this raw data sensible,and tacit knowledge accessible,on demand.

64、Jackie Rocca,former vice president of prod-uct at Slack,describes how AI can surface and distill the trove of information from past conversations in a platform like Slack when people need it.“People can get context from coworkers who left the company months or years ago and still learn from that kno

65、wledge,”she points out.Generative AI tools can help synthesize and disseminate personalized knowledge.“GenAI helps you get more value out of this knowledge so that you can find what youre looking for and be more effective in using all that data that has been available to you but hasnt been very easy

66、 for you to access and use,”Rocca says.While tools like wikis make it easier for people to record knowledge,AI capabilities can bolster organizational learning about what workers know.That enables organizations to better handle knowledge Legal disruptions48%61%68%79%1.6Limited LearnersOrganizational

67、 LearnersAI-specific LearnersAugmented Learners2.2Talent disruptionsMy organization is prepared to deal with uncertainty from 39%64%58%83%Limited LearnersOrganizational LearnersAI-specific LearnersAugmented LearnersTechnology disruptions49%71%68%86%1.8Limited LearnersOrganizational LearnersAI-specif

68、ic LearnersAugmented LearnersPercentage of respondents in each learning category who strongly agree or agree that their organization is prepared to deal with each type of uncertainty.Some values calculated with rounding.FIGURE 5 Combining Organizational Learning With AI Learning Helps With Many Type

69、s of UncertaintyOrganizations that combine organizational and AI-specific learning(Augmented Learners)are more likely to manage talent,technology,and legal disruptions.6MIT SLOAN MANAGEMENT REVIEW BCGloss from talent mobility,reducing uncertainty around how and when to capture tacit knowledge.One cl

70、oud services provider wasnt preparing for a poten-tial pandemic when it developed its learning tool,but when in-person meetings were no longer possible due to COVID-19,its platform and micro-learning content enabled the company to sustain and even enhance mean-ingful educational experiences.The comp

71、anys responsible AI lead explains how an innovative learning tool turned into a powerful tool for managing uncertainties wrought by the pandemic.Before the pandemic,the company had begun shiftingits learning modules to shorter,AI-supported“micro-adaptive”approaches suitable for a“TikTok world.”The p

72、andemic necessitated a remote work environment that changed what employees needed to know and,further-more,made it more difficult for the companys educational content providers to determine what employees knew and didnt know on an ongoing basis.The adaptive modules tailored content recommendations t

73、o each individual as the system assessed individual users learning capabilities.“AI became a huge part of that,”this executive says.“We monitored users self-reporting and skills self-assessments in their profiles and from the learning platform.”By analyzing skills and competency proficiency across s

74、ystems throughout the organization,the company identified what its employees were learning and needed to learn.She adds,“The AI-enabled modules did not just enable a different delivery of content;the platform helped people better understand what they knew and how that intersected with what they need

75、ed to know.”Drawing on the learning approaches and habits of many of the companys workers,the learning modules made tailored recommenda-tions based on individual needs that reduced uncertainty about what an individual needed to learn next.Enhancing organizational learning with AI provided flexibilit

76、y to man-age necessary changes during an unanticipated crisis.Technological and Regulatory UncertaintyIncreasingly frequent technology innovations lead to signifi-cant strategic and operational uncertainty.Adapting systems over and over again can be exhausting and disruptive to tech-nologists and bu

77、siness users alike.Just when companies had begun to understand how to incorporate AI use into their business strategies,generative tools introduced changes that required a reassessment.(see“the state Of ai in business,”page 14.)Tonia Sideri,director of the AI and Analytics Center of Excellence at No

78、vo Nordisk,notes that“technology is evolving faster than organizations can address.Combining that with the hype around technologys possible effects pulls the organization to do something.”Emerging technologies become“a propeller for the organization,”she observes,even if its initially unclear what t

79、he business case is or where investments should go.Reassessing technology investments can be beneficial,even if organizations dont end up adjusting their strategies but,rather,reinforce them to work within the new technological landscape.Whats more,technology adoption can lead to more,and more compl

80、ex,regulatory scrutiny and compliance issues,raising difficult questions about how to navigate increas-ingly uncertain legal environments.Surprisingly,using AI to amplify organizational learning dramatically improves a companys ability to manage uncertainty from both tech-nology and regulatory disru

81、ptions.Compared with orga-nizations with limited learning capabilities,Augmented Learners are significantly more likely to be prepared to deal with uncertainty from technology disruptions(86%versus 49%)and regulatory disruptions(79%versus 48%).(see figure 5,page 6.)Learning to manage uncertainty tha

82、t comes from a depen-dence on older technology and from future waves of tech-nology is a growing opportunity for Augmented Learners.Shelia Anderson,CIO of Aflac U.S.,shares how the insurer uses generative AI to reverse-engineer code in certain leg-acy systems.This approach is projected to boost curr

83、ent levels of system productivity by five to 10 times by revealing hidden complexities.“We have built in approaches to learn-ing that leverage AI and actually help to inform our organi-zation on how AI can be used as well,”Anderson says.She notes that Aflac also has a technology incubator that uses

84、AI to evaluate new technologies and rapidly prototype lead-ing candidates to prove out concepts for the business.If a prototype appeared to be viable for the business,Anderson says,“we would use AI to build a full business model with the return on investment or productivity savings or what-ever busi

85、ness value metric were looking to achieve.”On the regulatory front,large organizations with global operations can use AI to navigate complex,uncertain reg-ulatory frameworks that vary from one country to the next.For example,ELCs Gottipati observes,“From a company point of view,you make one product

86、and distribute it.But then,if the requirements are different for different countries,and also certain ingredients are limited in certain countries,Learning to Manage Uncertainty,With AI7it becomes time intensive to keep track of all these changing regulations and at the scale at which we operate.”Th

87、e com-binatorial explosion of products in a large number of mar-kets is difficult to keep up with.But Gottipati sees potential in using AI to help manage the myriad combinations.“Thats where I think AI can play a huge role:to identify the right combination of products before we ship anything,or send

88、-ing us alerts and assisting with compliance,”she notes.Using AI can offset growing legal complexity.Technology and regulatory uncertainty are inherently intertwined.As difficult as technological disruptions can be,legal disruptions can exacerbate technological uncer-tainty in addition to creating u

89、ncertainty on their own.Mark Surman,president of the Mozilla Foundation,notes that the software company is still very early in the process of figuring out the legal implications of AI.He says,“The core piece is,theres just so many questions about copyright and what it means to own knowledge.Maybe th

90、e copyright law we have just needs to be interpreted for the AI era.Or maybe we need new copyright law.”Within and beyond the boundaries of organizations,AI has turned the question of knowledge ownership upside down because,as Surman points out,“many of the main large language models are built on st

91、uff that,arguably,doesnt belong to them.”Augmented Learners have an advantage here because they have abilities that those unable to learn with AI lack.For example,knowing how to build your own AI tools could hedge against uncertainty from third-party solutions sub-ject to upcoming copyright regulati

92、on.Surman explains that this knowledge can help an organization navigate current legal uncertainties:“The one thing that is known and safe is whats inside the organization to the degree that you have good practices that information is clean and belongs to you.So if you train a large language model o

93、n your companys information,its yours.”Surman also sees open source as critical for managing that uncertainty.He expects that“open source will play a huge role in the organizational learning and corporate AI space because it lends itself to on-premises privacy,respecting customized models.It creates

94、 market demand for open-source models that you can fine-tune on your own data.”However,taking full advantage of open source requires organizational learning.Openness isnt restricted to the models themselves.For example,federated learning allows multiple organizations to train models collaboratively

95、while keeping their data pri-vate.Surman believes that“private AI using open-source models becomes a hedge against regulatory uncertainty.Federated learning,in which I benefit from my data in the partnership,you benefit from your data in the partnership,and theres some area where we collectively ben

96、efit or at least we can operationalize on each others data,is super juicy.”While standards for federated learning are still being worked out,Augmented Learners are better able to manage regulatory and legal uncertainties like these.Three Ways to Enhance Organizational Learning With AIWhile it may be

97、 tempting to identify organizational learn-ing as or,more pointedly,reduce it to knowledge management or learning and development,organizational learning involves far more than these important activities.It encompasses whether organizations view unsuccess-ful experiments as failures or as sources of

98、 learning;how organizations develop,not just manage,knowledge;and how organizations anticipate the unknown rather than merely capture what is known.It occasionally requires setting aside old ways of working to make learning new Combining organizational learning with AI-specific learning yields more

99、benefits than taking either approach alone.8MIT SLOAN MANAGEMENT REVIEW BCGAI technologies represent new capabilities for capturing existing tacit knowledge.In a more down-to-earth context,LG Novas Prasad observes that AI-based augmented reality(AR)glasses have the potential to capture the tacit kno

100、wl-edge of factory workers on the shop floor who have mastered a certain way of working with machines.“If theyre doing a technique on the shop floor that only they know,AR glasses can allow real-time content creation,”she says.While AR use is not common today,Prasad states this use case has the pote

101、ntial to become a more significant approach to capturing tacit knowledge as the technology/hardware matures.Using AI to distill information at scale enables the capture of salient information that would otherwise be impossible for humans to discern.Since 2021,LG Novas mandate has been to work,develo

102、p,and collaborate with startups to build new business ventures a typically daunting task,given the sheer number of potential targets worldwide.Prasad summa-rizes the question driving the subsidiary:“Can we use AI to find the right startups and create a deal flow that merits being put in front of our

103、 executive team?”The answer was decisive.AI has to work alongside humans and can narrow the search process and save executives time.While final decisions on which startups to recommend falls squarely on LG Novas human team,Prasad says that using AI can help generate a list of candidates for human ev

104、aluation and improves the companys situational awareness while expanding the num-ber of investment targets for its small team.Employees can also use AI to clarify how their knowledge would work in contexts they havent yet experienced.Expedia Group is a case in point.The company,like any large online

105、 platform,faces constant security threats.“Travel,like most other industries,is a great target for bad actors,”notes Expedia Groups chief architect,Rajesh Naidu.He says that the company is beginning to use generative AI to simulate attacks so it can prepare for them.Expedia Group learns from looking

106、 at“how an account-takeover scenario would work,or phishing,social engineering,things like that,”Naidu says.With the help of AI,the organization captures the knowledge it needs to prevent fraudulent activities before they occur.Knowledge SynthesisMaking sense of vast data sets can overwhelm legacy a

107、na-lytics.AI,however,can more effectively systematize an organizations data,pulling together internal and external data sets while making it all more digestible for managers,customers,and partners.capabilities possible.3 Whats more,organizational learn-ing encompasses synthesizing and analyzing info

108、rmation to glean what is and is not working in the enterprise.It also involves optimizing metrics,not merely maximizing performance on existing metrics.Finally,organizational learning addresses the communication,dissemination,and accessibility of knowledge.Combining organizational learning with AI-s

109、pecific learn-ing yields more benefits than taking either approach alone.AI-specific learning can significantly enhance(at least)three areas of organizational learning:knowledge capture,knowledge synthesis,and knowledge dissemination.These are not incremental additions;Augmented Learners multi-ply t

110、heir abilities in these areas.Knowledge CaptureAdopting generative AI and embracing developments in tra-ditional AI can expand an organizations ability to capture knowledge.Organizations can use it to extract tacit knowl-edge resistant to legacy codification techniques,absorb vast quantities of exte

111、rnal information,and even help crystallize knowledge that employees are still learning.Using AI helps managers capture tacit knowledge,an often intractable challenge for traditional knowledge-capture techniques.Consider the example of NASAs Mars 2020 mission.NASA wants to explore as large an area of

112、 Mars as possible,which means its Perseverance rover needs to be moving as much as possible.At the same time,the agency wants the rover to stop when it finds something“inter-esting”a concept thats difficult for operators to define.Plus,with 30 minutes of communication latency,human operators cannot

113、immediately direct the rover to stop.Vandi Verma,a principal engineer at NASAs Jet Propulsion Laboratory and chief engineer of Robotic Operations for Mars 2020,explains that AI has helped solve the prob-lem.“We have AI capabilities on the rover where itll take a wide-angle image,look at a large swat

114、h of terrain,and then try to figure out what is the most interesting feature in there,”she says.Despite the difficulty that humans have articulating what is and is not interesting,the AI learns from past data to operate semiautonomously,without anyone explicitly defining criteria for“interesting.”Pe

115、rseverance has had to overcome many obstacles while driving on Mars;using“interesting”as a guide for where to explore was an unexpected one.It had to re-create the tacit knowledge behind“interesting”to navigate the terrain successfully.4 Learning to Manage Uncertainty,With AI9Jeff Cooper,formerly se

116、nior data science director at online personal styling service Stitch Fix,describes how effective generative AI can be in synthesizing and summarizing large volumes of content.“One of the spaces weve been working hard on and considering where it might be useful involves customers who have been with u

117、s for dozens and dozens of Fixes,”he says,using the companys term for the delivery of stylist-selected clothing and accessories.“To have a stylist come in and look at all of the feedback theyve given over years potentially can be really compli-cated.With our new generative tools,we have the possibil

118、-ity of creating summaries of those things and compressing some of that information a bit further.In this case,its almost like you have a stylist working alongside a part-ner that can help do some of the extra work.”5 Generative tools excel at summarizing,a valuable feature in a business environment

119、,where desirable(and expected)response times are increasingly short.Organizations need not build their own tools to synthe-size data if a significant chunk of their data is in general business products with AI components.Our 2022 annual research report found that 55%of organizations were using third

120、-party tools with these capabilities.6(That number is likely higher now,with the widespread availability of tools based on large language models.)Slack is an example of how work platforms are using AI to assist in synthesizing knowledge.More than 700 million messages are sent in Slack each day.In la

121、rge organizations,especially,the volume of data produced across company channels can be challenging to keep up with.In response,the company developed a native AI solution for its product that helps workers instantly tap into their knowledge base by answering questions,summarizing conversations,and p

122、roviding daily recaps of channels.Rocca remarks on the value that a feature like this provides,saying,“We are creating GenAI solutions a combina-tion of generative AI and machine learning that deliver a daily recap summarizing all the channels you want to get up to speed on without going through eve

123、ry single mes-sage.A sales leader I know uses recaps to stay in the loop on his top 10 accounts,and he has many more accounts than that across many more channels.He doesnt want to know all the ins and outs that the team is doing to prepare for their next meeting.”The net effect is that users are abl

124、e to quickly reduce ambiguity about whats happening with the accounts that matter most.Knowledge synthesis with AI is not only about synthesiz-ing knowledge within a company,it also facilitates knowl-edge transfer from one context to another.Expedia Group has been using AI to synthesize data from ov

125、er 3 million properties,500 airlines,and 100 million loyalty mem-bers in the U.S.Collectively,the company manages more than 1.26 quadrillion combinations for hotel options alone,which includes variations like location and length of stay,all the way down to beachfront vistas and free parking;and asse

126、ssments of how the presentation of images impacts the end-user experience.With AI,Expedia Group can make sense of all of that information and make detailed recom-mendations to its partners.Naidu says,“We have enough information to provide really good recommendations to our hotel partners on image se

127、lection,image quality,and what content needs to be there to help drive a booking.We have the ability to suggest winning formulas that are based on our insights from other properties.”Synthesizing knowl-edge,especially across organizational boundaries,can lead to value-creation opportunities with par

128、tners throughout a business ecosystem.Knowledge DisseminationOrganizational learning depends on more than capturing and synthesizing information.A critical challenge in any learning organization is knowledge dissemination within the enterprise.Chief data officers mandate to get the right information

129、 to the right person at the right time reflects the importance of managing the dissemination challenge.Using AI to disseminate knowledge makes the process more inclusive and personal.One executive in the cloud services industry observes,“With generative AI,we have an opportunity to ensure that every

130、one is getting a learning experience that is going to meet their specific needs.That could be someone whos neurodiverse,or it could just be different learning styles or different languages.Often,we build technology and systems to meet the needs of the majority.AI can provide more rapid,lower-cost op

131、portunities that prioritize some groups that might be underserved or whose needs may not otherwise be met.We can provide an experience more rep-resentative of your entire organization and consumer base.”The opportunities to capture,synthesize,and dissem-inate knowledge with AI bring a fresh perspect

132、ive to a remark commonly attributed to Lew Platt,the former CEO of Hewlett-Packard:“If only HP knew what HP 10MIT SLOAN MANAGEMENT REVIEW BCGknows,we would be three times more productive.”As more enterprises adopt AI and participate in business ecosystems,knowing what the company knows is only part

133、of a larger learning challenge.Organizations also need to know what others,including suppliers,partners,customers,and competitors,know.Of course,know-ing every detail would be overwhelming,particularly in environments where speed matters.Furthermore,it isnt enough for the organization generally to k

134、now;individual employees need access to digestible information to make the knowledge useful.Developing Augmented Learning CapabilitiesOur research identifies five practical and actionable steps to improve organizational learning with AI.Simultaneously Improve Both Organizational Learning and AI-spec

135、ific LearningOnly 29%of organizations report having organizational learning capabilities,and only 15%of those organizations use AI to boost their organizational learning.(see figure 2,page 3.)Thats a clear mandate for enterprises to improve their limited learning capabilities.However,focusing on AI-

136、specific learning at the expense of organizational learn-ing(or vice versa)poses risks.Organizational learning that isnt ready for AI-based insights and perspectives will be less beneficial.Both types of learning need to be calibrated and worked on together.One starting place is to assess organizati

137、onal and AI-specific learning in the enterprise using the questions in the“About the Research”section.This is not a knowledge management audit.Rather,its an assessment of organizational learning that includes sup-port for new ideas,employee perceptions of organizational learning,and the ways workers

138、 use AI to learn.Learn to Explore With AIIts tempting to use AI primarily to improve existing pro-cesses say,to increase efficiency.Limited Learners are far more likely to succumb to this temptation:They are twice as likely to use traditional AI to improve existing pro-cesses than Augmented Learners

139、.Conversely,Augmented Learners are twice as likely to use traditional AI to explore 11Learning to Manage Uncertainty,With AInew ways of creating value than Limited Learners(and 1.6 times as likely to use generative AI for exploration).The tension between exploitation and exploration isnt new.Its nat

140、ural to use technological progress to exploit and improve existing processes.Exploration,meanwhile,involves trying new things.It requires managers to make conscious decisions about which new areas to explore.Avoid a strategy driven by technology availability(e.g.,“AI is cool;what are we doing that w

141、e could slap on a now improved with AI label?”)in favor of using technology to advance strategic outcomes.Our research finds that orga-nizations become better learners through exploratory projects than through exploitative projects.An exploratory approach helps organizations manage uncertainty becau

142、se the exploratory projects build depth in areas that might become strategic.Accelerate Learning With AIOur prior research found that organizational learning helps improve AI effectiveness.7 Our research this year finds that the reverse can also be true:AI can help enter-prises improve their organiz

143、ational learning.For example,Aflac has a technology incubator that looks at emerging technologies that might be useful for the business.The 1.924%26%36%45%Limited LearnersOrganizational LearnersAI-specific LearnersAugmented LearnersWe invest in high-risk projects.15%18%32%36%2.4Limited LearnersOrgan

144、izational LearnersAI-specific LearnersAugmented LearnersHow does your organization invest in AI projects?Our AI projects focus on long-term(greater than five years)impact.Percentage of respondents in each learning category who report their organizations invest in AI projects with long-term impact(re

145、porting a 4 or 5 on a 5-point scale).Percentage of respondents in each learning category who report their organizations invest in high-risk projects(reporting a 4 or 5 on a 5-point scale).FIGURE 6 Project Selection Can Enhance Learning CapabilitiesAugmented Learners are more likely to invest in long

146、-term and high-risk projects compared to Limited Learners.12MIT SLOAN MANAGEMENT REVIEW BCGincubator team partners with business leaders and teams to rapidly prototype new technologies.AI plays a critical role in quickly building,iterating,and assessing these innova-tion opportunities.Would a new un

147、derwriting system that addresses 10 times the number of parameters as existing processes be appropriate for the business?Quickly learn-ing whats possible,practical,and strategically relevant is a key source of value creation with AI.Anderson describes Aflacs incubator as“a rapid iterative approach t

148、o seeing if we can implement some of these technologies,”with the goal of learning which technologies to invest in to support organizational strategy.Every innovation opportunity cultivated with AI offers a chance to learn more about how to instantiate,operation-alize,or even expand a companys strat

149、egic aspirations.Effective learning capabilities,especially for fast learn-ing,tend to reduce the costs of technology uncertainty and encourage innovation.Strategies should incorporate a clear vision for using AI to develop an organizations learning capabilities.Choose Projects That Promote Learning

150、 Our survey results find that organizations become better learners from high-risk AI projects than from low-risk proj-ects.They also become better learners from long-term AI projects than from short-term projects.Project selection matters to how organizations learn.(see figure 6,page 12.)Viewing pro

151、jects as learning opportunities increases their potential value.Prem Natarajan,Capital Ones chief scien-tist and head of enterprise AI,says that he considers invest-ing in thoughtful new projects as bringing potential beyond traditional financial returns.He also sees longer-term strategic potential

152、like experimenting with use cases that“allow you to test and learn.Without adopting a test and learn approach,you cannot slope up into the other,more complex use cases in well-managed ways.”Learn ResponsiblyKnowledge capture and dissemination with AI carry prac-tical and ethical risks.Workers may pe

153、rceive invasive mon-itoring practices as a threat to their agency and autonomy,which can reduce employee engagement.In ecosystem partnerships,knowledge dissemination carries the risk of losing control of knowledge capital.Knowledge dissemina-tion without trust in the underlying data is a well-known

154、hurdle to data-driven decision-making.To address these pitfalls,deliberately apply responsible AI practices to ensure that knowledge capture and dissemination repre-sent established learning principles and values.For example,Expedia Group uses its partner portal to push recommendations(say,for repla

155、cing dated furniture or improving dining services)to affiliates based on sentiment analysis of its vast databases.Account representatives and managers follow up periodically to remind and encourage partners to act.The company opts for a nudge approach to disseminating knowledge instead of attaching

156、consequences or incentives that directly manipulate behaviors.Meanwhile,at Mozilla,much of the attention regarding knowledge dissemination is focused on the difficult prob-lems of ownership of knowledge capital and safety in the AI world.But,Surman says,“the one I think were not work-ing on is the q

157、uestion of economic security and equity.That may be the thing that upsets a big part of the apple cart.”Will organizations learn so well that they become less reliant on humans for production?Will learning capabilities be equally accessible to humans with a range of learning styles and needs?Will vu

158、lnerable workers become even more economically insecure when AI eliminates the tasks they are most qualified to do?The growing use of AI in organizational learning should impel companies to ensure that they learn responsibly.Learning With AI Is Key to Navigating UncertaintyConsiderable research over

159、 the past decade has focused on AIs impact on traditional financial outcomes,but our findings on the relationship between AI use and organi-zational learning could prove to be more consequential.Organizations currently face considerable uncertainty in many dimensions technological,regulatory,politic

160、al,and workforce-related,among others.Our research indicates that organizations that use AI to become better learners are 1.6 to 2.2 times more likely than those with limited learning capa-bilities to manage these external and internal uncertainties(see figure 5,page 6.)Given the rapid changes in mo

161、dern society,the longer-term benefit of improved organizational learning may prove to be far more important than potentially ephemeral short-term financial benefits.Learning to Manage Uncertainty,With AI131.Interest in AI,especially GenAI,is increasing.Since 2017,weve tracked AI use in business as p

162、art of our ongoing research program.Each year,we ask organiza-tions about their level of AI adoption.Historically,from 44%to 57%of organizations have reported piloting or deploying AI solutions.Weve attributed this relative sta-bility and fluctuation to the net effects of two main mech-anisms.On the

163、 one hand,the use of and attention to AI seem to be increasing.On the other hand,the definition of and expectations for AI are rapidly evolving.AI appli-cations that once seemed magical AI now feel routine.Furthermore,many people are becoming less aware of AI use as it becomes routine or embedded in

164、 other systems.iHowever,this year,70%of organizations report that they are now piloting or have deployed AI solutions.The prog-ress of and attention on generative AI appear to underlie this increase.More than 54%of organizations report piloting or deploying GenAI solutions.Thats a relatively high nu

165、mber,considering that many generative technologies were in their infancy less than two years ago.(see appendix figure 1.)46%2017201820192020202120222023202444%53%57%56%52%50%70%20406080100Percentage of organizations using AI0APPENDIX FIGURE 1 AI Adoption Increased Rapidly in the Past YearSince 2023,

166、the percentage of organizations piloting or deploying AI solutions rose 20 percentage points.APPENDIX The State of AI in BusinessOur research finds evidence of other trends in AI use in business beyond the relationship between AI use and organizational learning.MIT SLOAN MANAGEMENT REVIEW BCG142.Gen

167、erative AI is drawing attention both good and bad.Is GenAI a shiny new distraction or a crucial strategic imper-ative?Expectations for generative AI are particularly high.Ninety-one percent of organizations report that their lead-ership expects generative AI to be a core element of their business st

168、rategy across at least some of their business units in the next three years.Leadership attention to,or enthusiasm for,generative AI can lead to mixed results for a companys AI strategy if it distracts from more promising traditional In the next three years,my organizations leadership expects generat

169、ive AI to be a core element of my organizations business strategy across Generative AI _ the strategic goals of my organization.No businessunitsSome business unitsMany businessunitsNearly all business unitsAll business unitsDistracts fromHelps advance9%45%19%14%14%4%7%23%36%31%In the next three year

170、s,my organizations leadership expects generative AI to be a core element of my organizations business strategy across Generative AI _ the strategic goals of my organization.My organization focuses too much on generative AI.No businessunitsSome business unitsMany businessunitsNearly all business unit

171、sAll business unitsDistracts fromHelps advance9%45%19%14%14%My organizations focus on generative AI is taking budget from traditional AI initiatives.StronglydisagreeDisagreeNeither agreenor disagreeAgreeStrongly agree14%31%30%21%5%10%15%24%39%12%24%41%22%10%3%4%7%23%36%31%Some charts do not total 10

172、0%due to rounding.My organization focuses too much on generative AI.My organizations focus on generative AI is expanding the overall budget for AI initiatives.StronglydisagreeDisagreeNeither agreenor disagreeAgreeStrongly agreeStronglydisagreeDisagreeNeither agreenor disagreeAgreeStrongly agree10%15

173、%24%39%12%24%41%22%10%3%Some charts do not total 100%due to rounding.AI-related projects.Most survey respondents do not believe generative AI is a distraction at their company.While some organizations(26%)feel that the focus on generative AI is taking budget away from traditional AI initiatives,far

174、more(51%)feel that the attention to generative AI is expanding the overall budget for AI.Only 11%feel that generative AI is distracting,and only 13%feel that their organization focuses on it too much.(see appendix figure 2.)APPENDIX FIGURE 2 Organizations Show More Positive Than Negative Attitudes A

175、bout Generative AIMost organizations report that generative AI efforts expand the overall budget for AI efforts and help advance their strategic goals.15Learning to Manage Uncertainty,With AI3.Hopes for AI are outpacing fears.Our 2017 research found that far more people(70%)hoped that AI would perfo

176、rm some of their tasks than feared AI performing their tasks(31%).At the time,this finding countered a narrative of widespread concern about job loss.Yet,recent progress in generative models has since heightened discussions about job security among knowledge workers.Current AI models appear far more

177、 capable of replacing knowledge-intensive tasks.But instead of exacerbating concern,our research this year finds even more people(84%)hopeful that AI can assist with some of their tasks.As the performance of gener-ative models for language and images improves,people see greater potential for the tec

178、hnology.This potential has not increased their trepidation;now,only 20%of respondents are fearful that AI will assume some of their tasks.Experience with generative AI may be showing people what these models can and cannot do well.(see appendix figure 3.)Percentage of respondents who agree or strong

179、ly agree with these statements:“I hope that AI will do some of the current tasks in my job in five years,”and“I fear that AI will do some of the current tasks in my job in five years.”20172024%20406080100Percentage of respondents0HopeFear70%84%31%20%APPENDIX FIGURE 3 Individuals Are More Likely to W

180、elcome Automation Than to Fear ItDespite rapid advancements in AI,the percentage of individuals who report that they fear AI will do too much of their work has declined.Percentage of respondents who agree or strongly agree with these statements:“I hope that AI will do some of the current tasks in my

181、 job in five years,”and“I fear that AI will do some of the current tasks in my job in five years.”16MIT SLOAN MANAGEMENT REVIEW BCGAPPENDIX FIGURE 4 Organizational Strategies for AI Drop Back to Pre-Generative AI LevelsRecent technological breakthroughs require organizations to reformulate their AI

182、strategies.4.Emergence of GenAI upsets strategic plans for AI use.In 2017,we reported that 39%of organizations felt they understood the connection between AI and their strat-egy.By 2020,that figure had risen to 59%,as organiza-tions attained greater understanding of and experience with AI.However,in

183、 2024,the connection with strategy became murkier:Only 39%of organizations now report that they have a strategy for AI use,returning to the levels of 2017.Generative AI tools are in their infancy,scarcely two years into mainstream use.Technology changes,like the rising capabilities of generative too

184、ls,require execu-tives to reassess the technologys effect on strategy.The changes might fundamentally affect a value proposition or they might not.The proliferation and varieties of AI make it more difficult to incorporate their frequent changes into AI strategy,particularly when many come with the

185、potential for significant vendor lock-in.The connection between AI and strategy is important;organizations that report a strategy for AI are twice as likely to generate addi-tional business value from the technology.Perhaps the pat-tern of understanding strategy with AI will return to 2020 levels(or

186、 higher)as organizations gain experience with generative AI.(see appendix figure 4.)Since 2020,weve also been asking respondents how important AI is to their business strategy.That year,41%of respondents felt that AI was core to their organizations business strategy,while the remaining 59%felt it wa

187、s more peripheral.By 2023,61%felt that the use of AI was core.But this year,only 38%report that the use of AI is core to their business strategy.Generative AI might be an important factor in this notable shift,as executives recon-sider whether or how these new tools contribute to their strategies.Ou

188、r research finds positioning important,in that organizations are 2.6 times as likely to get business value from AI when it is core to their business strategy.While having AI at the core of strategy has been strongly correlated with getting business value from AI,it is not yet clear whether GenAI wil

189、l strengthen,weaken,or maintain this strong connection between strategic AI and business value from AI.We have a strategy for what we are going to do with AI in our organization.Percentage of respondents who strongly agree or agree.20172024%20406080100Percentage of respondents039%2020202320222021201

190、9201859%39%Percentage of respondents who strongly agree or agree.We have a strategy for what we are going to do with AI in our organization.17Learning to Manage Uncertainty,With AIACKNOWLEDGMENTSWe thank each of the following individuals,who were interviewed for this report:Shelia Anderson CIO,Aflac

191、Sowmya Gottipati vice president of global supply chain technology,The Este Lauder CompaniesRajesh Naidu chief architect,Expedia GroupPrem Natarajan chief scientist and head of enterprise AI,Capital OneShilpa Prasad head of incubation,AI Ventures,LG NovaJackie Rocca former vice president of product,S

192、lackTonia Sideri director of the AI and Analytics Center of Excellence,Novo NordiskMark Surman president,Mozilla FoundationDiya Wynn responsible AI lead,Amazon Web Services18MIT SLOAN MANAGEMENT REVIEW BCG REFERENCES 1 L.Argote,“Organizational Learning Research:Past,Present and Future,”Management Le

193、arning 42,no.4(September 2011):439-446.2 S.Ransbotham,S.Khodabandeh,D.Kiron,F.Candelon,M.Chu,and B.LaFountain,“Expanding AIs Impact With Organizational Learning,”MIT Sloan Management Review and Boston Consulting Group,October 2020.3 P.M.de Holan,N.Phillips,and T.B.Lawrence,“Managing Organizational F

194、orgetting,”MIT Sloan Management Review 45,no.2(winter 2004):45-51.4 S.Ransbotham and S.Khodabandeh,“806:AI on Mars:NASAs Vandi Verma,”December 19,2023,in“Me,Myself,and AI,”produced by MIT Sloan Management Review and Boston Consulting Group,podcast,MP3 audio,24:00,https:/sloanreview.mit.edu.5 S.Ransb

195、otham and S.Khodabandeh,“903:Fashioning the Perfect Fit With AI:Stitch Fixs Jeff Cooper,”April 16,2024,in“Me,Myself,and AI,”produced by MIT Sloan Management Review and Boston Consulting Group,podcast,MP3 audio,34:03,https:/sloanreview.mit.edu.6 S.Ransbotham,D.Kiron,F.Candelon,et al.,“Achieving Indiv

196、idual and Organizational Value With AI,”MIT Sloan Management Review and Boston Consulting Group,November 2022.7 S.Ransbotham et al.,“Expanding AIs Impact.”i Ransbotham et al.,“Achieving Individual and Organizational Value With AI.”Learning to Manage Uncertainty,With AI19MIT SLOAN MANAGEMENT REVIEWAt

197、 MIT Sloan Management Review(MIT SMR),we explore how leadership and management are transforming in a disruptive world.We help thoughtful leaders capture the exciting opportunities and face down the challenges created as technological,societal,and environmental forces reshape how organizations operat

198、e,compete,and create value.MIT SLOAN MANAGEMENT REVIEW BIG IDEASMIT Sloan Management Reviews Big Ideas Initiatives develop innovative,original research on the issues transforming our fast-changing business environment.We conduct global surveys and in-depth interviews with front-line leaders working

199、at a range of companies,from Silicon Valley startups to multinational organizations,to deepen our understanding of changing paradigms and their influence on how people work and lead.BOSTON CONSULTING GROUPBoston Consulting Group(BCG)partners with leaders in business and society to tackle their most

200、important challenges and capture their greatest opportunities.BCG was the pioneer in business strategy when it was founded in 1963.Today,we work closely with clients to embrace a transformational approach aimed at benefiting all stakeholders empowering organizations to grow,build sustainable competi

201、tive advantage,and drive positive societal impact.Our diverse,global teams bring deep industry and functional expertise and a range of perspectives that question the status quo and spark change.BCG delivers solutions through leading-edge management consulting,technology and design,and corporate and

202、digital ventures.We work in a uniquely collaborative model across the firm and throughout all levels of the client organization,fueled by the goal of helping our clients thrive and enabling them to make the world a better place.20MIT SLOAN MANAGEMENT REVIEW BCGBCG HENDERSON INSTITUTEThe BCG Henderso

203、n Institute is Boston Consulting Groups think tank,dedicated to exploring and developing valuable new insights from business,technology,science,and economics by embracing the powerful technology of ideas.The Institute engages leaders in provocative discussion and experimentation to expand the bounda

204、ries of business theory and practice and to translate innovative ideas from within and beyond business.For more ideas and inspiration from the Institute,please visit .BCG XBCG X is the tech build and design unit of BCG.Turbocharging BCGs deep industry and functional expertise,BCG X brings together a

205、dvanced tech knowledge and ambitious entrepreneurship to help organizations enable innovation at scale.With nearly 3,000 technologists,scientists,programmers,engineers,and human-centered designers located across 80+cities,BCG X builds and designs platforms and software to address the worlds most imp

206、ortant challenges and opportunities.Teaming across our practices,and in close collaboration with our clients,our end-to-end global team unlocks new possibilities.Together were creating the bold and disruptive products,services,and businesses of tomorrow.Get more on artificial intelligence from MIT S

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