1、Leadership in the Age of AI 1INTRODUCTION132Despite,or perhaps because of,the endless opportunities AI promises,anxiety and excite-ment over the disruptive role it will play are running high.One thing is certain:ensuring that your organization is prepared for the new era of AI is no longer optional.

2、The question now is:are leaders ready to rise to the challenge and provide the vision and adaptability to seize the opportunities?To answer this question,Egon Zehnder and Kearney partnered to engage 100 executives in a survey across four countries and six sectors,gauging their views on how prepared

3、their organizations,and they themselves,are for the coming AI era.We conducted over two dozen interviews with leaders to refine our findings further.We heard that leaders over-whelmingly see AI as an opportunity,more than a risk,but that leaders feel the path to success is still unclear.Harnessed fo

4、r good,AI offers endless possible solutions to the many converging crises leaders navigate today.This report provides insights into how executives anticipate AI will impact organizations,jobs,and their roles and how prepared they feel to lead through this unprecedented dis-ruption.We will explore fa

5、ctors and drivers of leadership and organizational readiness that could guide leaders amidst the inevitable tech change ahead.The age of artificial intelligence(AI)has erupted into our world,marking its presence with striking advancements.AI models are demonstrating new capabilities almost daily,to

6、the point where the question is no longer what AI can do but rather what it cant.Unlike the hype around the metaverse or blockchain technology,AI is already driving bottom-line results across multiple sectors.A multidisciplinary team of researchers at MIT Sloan has proved an unprecedented boost of u

7、p to 40%in highly skilled workers performance through the use of generative AI*;potentially adding trillions to the global economy.This monumental shift will change the way people work,learn,and communicate and has the potential to shake up entire industrieseven society itself.*Generative AI(Gen AI)

8、refers to deep-learning AI models that can generate high-quality text,images,and other content based on the data they were trained on.“AI has joined the list of rapid changes and challenges people are facing today.It is no surprise then that many are asking How do I adapt?”Judith Wiese,Siemens“Disru

9、ption is inevitable in any significant technological change.Its crucial for innovation and constant adaptation and progress.”Patrick Trippel,Inventus Power45THE AI OPPORTUNITY276On the one hand,the significant opportunity identified by leaders,both for their role and for their organization as a whol

10、e,was the increased efficiency that the effective use of AI could bring;around three-quarters identified this as an opportunity for their roles,with a similar number identifying it as an opportunity for their organization.Other AI opportunities that executives identified included more effective deci

11、sion-making,improved risk management,and the creation of innovative products and services.On the other hand,respondents were alert to the potential risks associated with AI.Workforce displacement and data privacy&security emerged as the two main concerns for leaderswith regard to both their individu

12、al roles and their organizations(see Figure 2).INSIGHT Attitudes toward AI are positiveleaders see it as an opportunity more than a riskExecutives are keenly aware of the opportunities that AI could present.Specifi-cally,these opportunities relate to AI applications that could support or replace off

13、ice jobs,including machine learning,natural language processing,expert sys-tems,and generative AI.More than 90%agree that AI represents an opportunity for them in their roles rather than a risk.Leaders are also confident that AI is an opportunity for their organization,with 85%seeing AI as an opport

14、unity to improve their organizations capabilities(see Figure 1).“Nobody has a real clue about AIs true magnitude and end-state.”Martin Brudermller,BASF“AI is not about disruption,it is about opportunities.”David R.Hardoon,Aboitiz98Figure 1RiskRisk915%of participantsChanceChance9185%of participantsFo

15、r my organizations capabilities,I see AI as primarily being a:For me in my role/position,I see AI primarily being a:Figure 11110EfficiencyWorkforce displacementInnovative products/servicesROLEORGANIZATIONData privacy&securityDecision-makingDependence&reliabilityCompetitive advantageTransparency&inte

16、rpretabilityRisk managementBias&fairnessConsumer experienceOtherOtherRegulatory complianceWorkforce displacementBias&fairnessData privacy&securityRegulatory complianceDependence&reliabilityTransparency&interpretabilityOtherEfficiencyConsumer experienceInnovative products/servicesDecision-makingCompe

17、titive advantageRisk managementOtherChance(%of participants)Chance(%of participants)Risk(%of participants)Risk(%of participants)7355553248578475484451636436752Figure 2Figure 21312“The fear of AIs failure is a concern,but is heavily outweighed by the opportunity it promises.”Mark Rose,Avis

18、on Young“AI is going to be big and will impact everything!”Lior Ron,Uber Freight “Every human working with AI has not only the power but also the responsibility to evaluate content generated by AI critically.”Carsten Knobel,Henkel“Regulators need to set the right frame,which is a risk-free environme

19、nt to test and scale and then pair with appropriate incentives and regulation at real-life adoption.”Martin Brudermller,BASF“Middle management is under pressure.In the past,you were promoted for your knowledge,but theres a new expert in townAIand it knows what you know and more.Connecting,engaging,a

20、nd collaborating people-centric skillswill become even more relevant than ever.”Judith Wiese,SiemensLeadership in the Age of AILeadership in the Age of AI14 AIs bias.The quality of an AI models output is directly linked to the data its trained on.If the training data is not a balanced reflection of

21、the real-world diversity it is trying to represent,the AI may generate biased results.Ensuring that AI operates fairly involves selecting training datasets comprehensively representing the target outcomes,thus promoting unbiased and reliable outputs.Four Common RisksFigure 3With so many risks and co

22、nsiderations,where should leaders focus their concerns?Amidst the challenges of the current poly-crisis,it can be difficult to identify and focus on the myriad of risks associated with the current wave of AI.Through our experience with clients and research,we have identified four key risks leaders s

23、hould look out for(see Figure 3).Data hallucination.While generative AI models are highly accurate,they remain 100%confident,even when wrong.This proves the inevitable need for a“human-in-the-loop”process to verify model outcomes continuously and is confirmed by our survey results indicating a conce

24、rn around dependence and reliability.Ballooning costs.As the data volumes stored by AI platforms rise,so do the collection,storage,and processing costs.More efficient data management techniques can help mitigate some impact.The concern around costs clearly emerged from our conversations with leaders

25、,even though we did not address it in the survey.Risks from third-party(3P)services.Relying on 3P services for handling sensitive data and compliance can expose businesses to risks,particularly if security measures are lax or standards are inconsistent.To safeguard against these vulnerabilities,cond

26、ucting due diligence on 3P providers carefully is essential,as well as enforcing strong data protection practices and contracts that clearly define roles and responsibilities.15Data hallucination Misleading of fabricated dataBallooning costs Rising collection,storage,and processing costsRisks from 3

27、P services Potential data breaches,varying compliance standards,etc.BiasInaccurate prediction results due to bad data16INSIGHT Executives believe that significant change within their organizations is on the horizon,but less for their individual rolesBusiness leaders expect AI to be a major disruptiv

28、e force in the near term,with 70%of respondents agreeing that AI will disrupt their organization within the next five years.How-ever,fewer executives expect the same level of disruption when it comes to their own roles.Less than half agree that AI will disrupt their role in the next five years,while

29、 a third expect no disruption(see Figure 4).Moreover,our conversations with leaders revealed anticipation of a transformational wave within their organizations,spurred by AI;leaders predicted it would reshape future business landscapes.Despite recognizing the disruptive potential of AI,especially in

30、 streamlining operations and enhancing strategic decisions,many do not foresee their individual roles undergoing significant change.The sentiment across the board suggests an awareness of the necessity to adapt,with a hint of caution regarding the full scope of AIs implications yet to be fully grasp

31、ed.This reflects a measured optimism about AIs role in driving effi-ciency and competitive edge,while leaders also acknowledge the gaps in their own under-standing of AIs future impact.43703621921=Role=OrganizationAgreeDisagreeNeither Agree/DisagreeBusiness leaders expect AI to be more disruptive to

32、 their organization than to themselves and their position in the next 5 years17Figure 41918“AI has a huge potential to be truly disruptive.But I dont believe it will fundamentally change the way we operate our business;rather,it will create a huge value-add and bring ammunitions for efficiency,faste

33、r decision-making,and other business outcomes.”Rebecca Oldfield,Infineum“Data-driven job profiles,which already leverage insights based on machine-driven decisions,will only experience little changes for their leadership through AI.”Rolf Schumann,Schwarz Gruppe“In my role as CEO,I need to be a role

34、model and a driver for change.Change always starts at the top.This is a crucial belief in our cultural transformation,and I think you can transfer this to the adoption of disruptive technologies as well.We need to be ready when it comes to all kinds of disruptions,especially when they have an impact

35、 in the magnitude of Gen AI.”Carsten Knobel,HenkelLeadership in the Age of AILeadership in the Age of AI2120HOW PREPARED ARE LEADERS AND THEIR ORGANIZATIONSFOR AI?32322On the other hand,among executives who believed that their organization was unprepared,three-quarters thought that the lack of readi

36、ness stemmed from a lack of time,money,and people dedicated to building readiness for AI disruption.Leadership understanding also has a role to play:just over half of the respondents agreed that a lack of leadership under-standing contributed to a lack of readiness(see Figure 6).It is worth emphasiz

37、ing that the arrival of AI comes at a time when leaders are already stretched,navigating the many challenges that organizations face today.This poly-crisis goes beyond organizational or industry boundariesit extends to geopolitics,polarized domestic politics and rising populism,and an existential pl

38、anetary crisis.If leaders can return to their values in shaping the landscape for an AI-ready economy and society,AI could solve humanitys many crises.Implemented right,AI has the potential to be a democ-ratizing tool,used in service of humanity,and not as a force that erodes it.INSIGHT Leaders beli

39、eve their organizations are unprepared for the shiftSo,do executives feel that they and their organizations are ready to navigate the disrup-tions of AI while seizing the opportunities?Of the leaders surveyed,only 21%agree and strongly agree that their organization has the necessary capabilities to

40、deal with the expected disruption of AI in the next five years(see Figure 5).In general,executives see themselves as better prepared to deal with the disruption than their organization,but still,only 40%agree and strongly agree that they have the necessary capabilities to do so.This ties back to our

41、 findings regarding a higher expected disruption,with the understanding of leaders that this disruption would require significant resources to be handled.In turn,leaders may also feel better informed than their organizations of whats to come.INSIGHT Leaders understanding of AI is critical,while lack

42、 of sufficient resources is the biggest stumbling block for feeling preparedThose leaders who believe their organization is prepared for AI-related disruption recog-nize the importance of leaderships understanding of AI in driving that readiness.Nearly 90%agree that leaderships understanding was a c

43、ore reason behind their organizations readiness.Other factors identified as contributing to readiness included cultural support of change,with 74%of respondents agreeing;and the allocation of sufficient resources including time,money,and people(70%agreed).“Organizations and CEOs are not ready for AI

44、 as the full-fledged implications are not yet understood.”Bill Anderson,Bayer AG2524“There is a phase of curiosity at the beginning of technological change,and also what is being communicated around it,but then leaders need to move on to creating a visionary approach,with very tangible examples,so t

45、hat people can start to understand the benefits.”Batrice Guillaume-Grabisch,Nestl“Leaders are particularly challenged to deal with the perceived loss of control in the organization.”Marianne Janik,Microsoft“Leaders will use Artificial Intelligence,laggards not.And of course:You will always need smar

46、t people!”Bill Anderson,Bayer AGLeadership in the Age of AILeadership in the Age of AI2726Disruption expectedDisruption unexpected36364383190I have the necessary capabilities in my role for the expected disruption of AI in the next 5 years(%of participants)My organization has n

47、ecessary capabilities for the expected disruption of AI in the next 5 years(%of participants)Disruption expectedDisruption unexpectedStrongly disagreeStrongly disagreeStrongly agreeStrongly agreeStrongly agreeDisagreeDisagreeNeither agree nor disagreeNeither agree nor disagreeAgreeAgreeExecutives wh

48、o expect their role to be disrupted report worse preparation for expected disruptionExecutives who expect their organization to be disrupted report worse preparation for expected disruption Percentages may not total 100 due to rounding.Figure 5 Percentages may not total 100 due to rounding.Figure 5(

49、64 respondents)(36 respondents)(79 respondents)(21 respondents)2928My organization is ready for the disruption,because:Leadership under-standingSufficient resources (time,money,people)Cultural support of change44772619897074Executives are convinced their understanding of AI is a major driver for AI

50、readiness (%of participants)DisagreeNeither agree nor disagreeAgreeMy organization is not ready for the disruption,because:Leadership under-standingSufficient resources (time,money,people)Cultural support of change6517359Executives attribute the lack of readiness primarily to insufficient

51、 resources(%of participants)DisagreeNeither agree nor disagreeAgreeHigher readiness is reported to be driven by leadership understanding while lack of preparedness is reported as due to insufficient resourcesFigure 6Figure 63130HOW CAN ORGANIZATIONS IMPROVE AI READINESS TO PREPARE FOR THE FUTURE?432

52、INSIGHT Starting to develop a strategy is a crucial step for increasing organizational readiness,but it is not enough on its ownGiven the importance of leadership in driving preparedness for the challenges that AI could bring,it is no surprise that leaders are taking action to increase their organiz

53、ational read-iness.To lead their organization through this change,leaders have shared personal learn-ing,or understanding of AI,as an initial step to be able to undertake any change efforts.At the forefront of these efforts is developing a strategymore than three-quarters of respon-dents are taking

54、this step,even though there is no clear blueprint for leaders to follow.While leaders may feel unsure of the next steps in the face of the transition,it is clear from our conversations that making a start with adoption,even amidst uncertainty,is better than not starting at all.However,this action al

55、one is not enoughespecially as strategy development is inherently tricky against an uncertain and constantly changing picture of possibilities and risks.Only 14%of respondents reported that strategy development was their sole focus,with the majority saying that they are taking additional actions,inc

56、luding investing in infrastructure(49%),building external partnerships(44%),and recruiting experts(39%).While AI is acknowled ged to have significant disruptive potential,its opportunities may still be greater.Com panies take these risks and opportunities seriously,as evidenced by a thirteen fold in

57、crease in AI-related corporate investments in the last decade.However,more than a business-as-usual approach will be required to ensure that an organization will thrive in the age of AI.Profound change and strong cultural development will be needed,which will not happen if leadership isnt at the for

58、efront.We believe that the disruption does not start with strategy or operations,but with leaders themselves.The more they can adjust their professional identity as they embrace AI,the greater the transformation that will occur.Business leaders can act boldly and strategically to achieve organizatio

59、nal readiness for AI.That will require a deep understanding of current market capabilities and possible gaps in capability within themselves and their organizations.Our conversations with leaders highlighted five key success factorsthey can serve as cornerstones for leaders as they drive AI adoption

60、 strategies(see Figure 7).33“You better embrace it as a business leader because,if not,your competition and the rest of the market is going to absorb the necessary dynamic capabilities in real-time,and youre going to be lethargic and left behind.”Richard Ashworth,Amedysis3534 Security controls.Estab

61、lish a robust data security framework.This should include defin-ing user access levels and security measures that adhere to governance,compliance,ethical standards,and privacy regulations.Architectural design.Craft an architectural framework that is inherently scalable.This design should be capable

62、of evolving to meet the demands of future use cases while remaining in line with the organizations core principles and values.Change management.Develop a robust change management strategy.This strategy should ensure a smooth transition and integration of generative AI into existing work-flows,foster

63、ing acceptance and operational harmony.Maintain a people-focused ap proach during this change,ensuring that all technological changes serve the indivi-duals they are meant to enable.Business case development.Evaluate the potential for value creation meticulously.This involves a comprehensive assessm

64、ent of benefits,costs,practicality of implemen-tation,and associated risks before deploying generative AI applications.By prioritizing value creation,leaders can ensure the adoption of effective AI initiatives.Data quality management.Prioritize the integrity of data.It is crucial to ensure that the

65、data fueling generative AI is accurate,complete,and free from biases to yield depend-able and valuable results.Five Success FactorsFigure 7Business case development for assessing value creationData quality management for accurate outcomesSecurity controls for data protectionArchitectural design for

66、scalabilityChange management for successful Gen AI adoption3736“AI is like a new colleague.They need to be trained,you have to give them clear work assignments and take your time with them!”Marianne Janik,Microsoft“To embrace the change within a big organization,you need to have a clear vision,but y

67、ou also need the organization and the infrastructure to support it.”Batrice Guillaume-Grabisch,Nestl“Leadership needs to stay close to tech trends through personal initiative(do not outsource!)and continuously invest in several smaller projects to explore new trends.These projects should be supporte

68、d bottom-up to make the team realize these opportunities firsthand.”Ron Lior,Uber Freight“You need to show people examples of success in order to get people onboard.”Mark Rose,Avison YoungLeadership in the Age of AILeadership in the Age of AI3938CONCLUSION54140Very few leaders can claim to be expert

69、s in AI or know precisely how to translate AI oppor-tunities into strategic action.However,beyond the solutions introduced earlier,our discus-sions with leaders across industries have identified several practical steps that one can take to position themselvesand their organizationsfor success.Start

70、small,go low,go slow,but go.While the opportunity that AI promises is clearly recognized,capturing the opportunity with practical next steps can be an overwhelming ask.Leaders weve spoken to suggest starting small.Driving smaller,manageable initia-tives with tangible results can break down the daunt

71、ing uncertainty that comes with the shift,educating and boosting curiosity along the way.This is the foundation for fast and sustainable transformation.Create room for transparent exploration.Leaders could create a psychologically safe space for exploration within their teams and organizations.Allow

72、 for the experimentation with different forms of AI within a secure sandboxembrace utility-ready tools and capabil-ities at your fingertips,guided by organizational oversight and governance.This will bring playfulness to the transition at hand and could boost overall engagement and enthusiasm.Allow

73、for consistent dialogue and organization-wide visibility of the sandbox learnings and outcomes;it could create a cultural shift of openness to the new technology.Moreover,leaders should ensure that all necessary stakeholders are included in this process.“Go slow and pick something that works.Find te

74、chnological interventions that are repeatable,scalable,easy to understand,and accurate.”Richard Ashworth,Amedysis“I see my role as the person who can educate,navigate AI as a journey,starting with small and digestible use cases to build confidence before looking at the more advanced AI capabilities

75、available.”Ciara Moore,Bank of Ireland“AI developments in the organization are an evolutionary rather than revolutionary way.”Rolf Habben Jansen,Hapag LloydLeadership in the Age of AI4342Disrupt yourself first,or AI will.Allow yourself as a leader to engage with this new technology by,for example,en

76、rolling in an introductory online course,encouraging your col lea gues to take the same approach.Some leaders weve spoken to emphasized personal learning,or understanding of AI,as one of the most crucial characteristics for embarking on a successful transition.Engage with experts in the field and em

77、brace an internal shift of continuous learning.Last but not least,leaders need to keep a sharp eye on investments in AI and not lose the“venture mindset”on those investments.This would mean being sharp about choosing the“right investment use cases”where the business case is clear,either to manage ri

78、sk or to drive growth potential.And secondly,being ruthless about killing those investments where“value cant really be realized”due to some real obstacles.Finally,never losing sight or focus on“scaling”value-creating use cases,as that is key to realizing more sustainable value.“I think the big chall

79、enge is the people.And I dont agree that its the frontline people,but its the leadership.Whether its senior leadership or mid-management,they both tend to operate the same way theyve always operated.”Patrick Trippel,Inventus Power“Its all about the leadership mindset.”Jennifer Zhu Scott,IN.Capital“M

80、aintaining your own judgment as a leader is absolutely critical.”Marianne Janik,Microsoft“You cannot get a company to embrace change if they dont have a clear understanding of where they want to go.”Batrice Guillaume-Grabisch,NestlLeadership in the Age of AI45Are you preparing to lead your organizat

81、ion into the age of AI?While our survey found that leaders are overwhelmingly looking at AI as an opportunity,the picture is not yet clear on how to harness this opportunity practically.It may be some time before a clear organizational strategy can emerge,but leaders can already test their own level

82、 of readiness to lead in the age of AI by reflecting on a few questions:1.Am I tending towards fear or excitement when I think about AI and its possibilities?Where do I focus my efforts on risks and barriers,or possibilities and potential?2.Am I dreaming big enough when thinking about the potential

83、use cases for my organization?Am I being audacious enough in my thinking,or am I limiting my outlook by focusing on barriers?3.Am I creating a truly experimental environment?How do I enable my people and teams to test,learn,and fail?4.Am I seeing the possibilities and challenges from every angle?Am

84、I really listening to the views of all stakeholders to understand how AI may benefit or disrupt the different functional areas of my organization?5.Am I embracing AI in a real sense,or am I experiencing it in a theoretical sense only?How am I experimenting with the technology?Have I witnessed its po

85、wer firsthand,or am I forming judgments based on what Im reading or hearing others say?IMPRINTGET IN TOUCH4746Burcu BMichael MBenjamin LRamyani BAlex LMirko WImprintCo-AuthorsEgon Zehnder:Burcu Bicakci,SingaporeBenjamin Lpschen,DusseldorfMichael Meier,DusseldorfKearney:Mirko Warschun,MunichRamyani B

86、asu,LondonAlex Liu,San FranciscoProject ManagementEgon Zehnder:Catharina RoltschMartin KlusmannKearney:Tamarra SchneiderLisa TietzKatharina BohlenzAnton GrushinEditorial SupportDouglas Knowledge PartnersGraphic&Information DesignPaul SoujonJonas Vogler 2024 Egon Zehnder International,Inc.and Kearneyall rights reserved.No part of this publication may be reproduced,stored in a retrieval system,or transmitted in any form or by any meanselectronic,mechanical,photocopying,recording or otherwise without the prior permission of Egon Zehnder and Kearney.