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1、Are CEOs Ready to Seize AIs Potential?Charting the path to value creation.Not value destruction.JANUARY 2025Are CEOs Ready to Seize AIs Potential?1Table of Contents02/Foreword03/Executive summary05/Introduction06/What CEOs see:The big picture of AI08/Perception vs.reality:How ready are CEOs for AI?0

2、9/CEO perspectives on the transformative potential of AI12/Impact of centralized,top-down management.14/AI-driven innovation:The need for speed19/Equipping leaders for the AI-enabled era22/AI governance and ethical considerations25/Strategic agility,change management,and decision-making enhanced by

3、AI28/Ignition to innovation:The CEO playbook for AI30/The rise of agentic AI31/AI is a business capability first and a technology second.32/Authors33/Appendices33/Research methodology34/Geographic demographics of surveyed CEOsAre CEOs Ready to Seize AIs Potential?2Optimism is the only free stimulus

4、in this world.artificial intelligence is not only a generational technological shift.It is our single greatest opportunity to stimulate a new century of innovation,progress,and growth.We are in the early days of this renaissance.From an economic perspective,AI will have a nearly$20 trillion global i

5、mpact by 2030.Every$1 spent on AI solutions and services will generate nearly$5 in value to the global economy.In terms of human productivity,AI will unlock nearly one billion hours of productivity this year for ServiceNows customers alone.Think of what people will do with one billion hours.Imagine

6、the scientific advances,the more responsive citizen services,the more sustainable supply chains.If linear thinking is what limits the worlds potential,human and artificial intelligence together will move us from linear to exponential.In my book,Winners Dream,I wrote that our destiny is defined by ou

7、r dreams.This is the lens that focuses the tenacity,audacity,and courage needed to lead great enterprises.To lead in the age of AI requires us to dream big so that people are inspired by the art of the possible.We also need to deliver a new business logic,one that marks a clean break from the tactic

8、s and technologies of the 20th century.This research from Kearney and Futurum gives CEOs a compass to chart the opportunities with AI.It also looks at the cultural and environmental impacts that will be among the biggest measures of our success.This is not a time for incrementalism.Its a time for ex

9、ponential thinking and the courage to lead.If we choose to embrace it together,the ceiling on our dreams has no limits.Bill McDermott Chairman and CEO,ServiceNowForeword for Kearney&Futurum CEO StudyAre CEOs Ready to Seize AIs Potential?3Organizations worldwide are navigating the complexities of dep

10、loying AI responsibly,profitably,and at scale.This global study uncovers eight major takeaways from CEOs,emphasizing the need to avoid inflated optimism,maintain ROI focus,address cultural concerns,build a robust data foundation,and prioritize measured rollouts over all-or-nothing leaps.The confiden

11、ce paradoxWhile 78%of CEOs say they feel confident about capturing value from AI,success rates are higher in organizations where executive leaders relinquish day-to-day control.In high-performing firms,only 59%of CEOs maintain direct oversight,compared to 92%among less successful ones.Delegating ope

12、rational execution to specialized teams allows for more effective implementation and stronger results.The ROI blind spotDespite widespread acknowledgement of AIs game-changing potential to create business value,rigorous tracking of returns is still not the norm.In organizations with high-achieving i

13、nitiatives,48%prioritize rigorous ROI measurement versus only 17%in organizations reporting underwhelming results.Anchoring AI projects in measurable returns early on ensures sustained momentum and leadership buy-in,justifies the investment case(initial and ongoing),and supports strategic pivots whe

14、n needed as projects advance.Myopic ambitionAlthough CEOs tout AIs transformative possibilities,95%of companies focus on quick gains through immediate problem-solving rather than higher-value opportunities like workforce transformation or business model innovation.This short-term mindset risks forfe

15、iting the competitive advantage that comes from a steady investment in next-generation AI skills and capabilities.Failed AI initiatives linked to aggressive strategiesFirms reporting minimal AI success are more prone to adopt a rushed,aggressive approach going after 100s of use cases,with 58%taking

16、a“catch-up”approach compared to 45%of more successful peers.Speed without sufficient pilots,governance,or ROI safeguards commonly leads to oversights and shortfalls.Gradual,proof-of-value rollouts backed by change management often yield more lasting results.Executive summaryAre CEOs Ready to Seize A

17、Is Potential?4Bridging the AI culture chasmDespite AIs promise of performance gains,many CEOs list workforce concerns about job security and evolving roles as a leading barriersecond only to data hurdles.Proactive communication,targeted training,and inclusive change management can turn apprehension

18、into support,reframing AI as a tool to enhance human potential.Making the shift from data deficit to data dividendExcessive focus on algorithms often comes at the expense of ensuring data quality and integration.Over 60%of executives with stalled or ineffective AI cite fragmented data and outdated i

19、nfrastructure as main culprits.Unified data architecture,rigorous governance,and consistent standards are vital to unlocking AIs full value,ensuring reliable returns.The fast-follower advantageOver half of the surveyed CEOs prefer a fast-follower model rather than being first movers,learning from ot

20、hers successes and failures before scaling AI.This careful strategy helps refine governance,strengthen data readiness,and build organizational trust,enabling early wins to expand seamlessly across the enterprise.Our analysis reveals a striking disconnect:The most successful companies are those where

21、 top leadership deliberately steps back from hands-on AI strategy.Are CEOs Ready to Seize AIs Potential?5No other technology in the last 30 years holds the potential to disrupt and radically change a broad base of businesses than artificial intelligence.AI will not only shape the design and developm

22、ent of new products and services,but also the programs and processes with which organizations operate.Our study of over 200 CEOs operating globally across industries as diverse as finance,manufacturing,retail,and healthcare with over$1 billion USD in annual revenues establishes a benchmark for CEO r

23、eadiness and effectiveness during disruptive times.Conducted through surveys and in-person,in-depth interviews,it captures actionable insights into leadership strategies,innovation priorities,and AI-driven decision-making.We explore CEOs strategies as they experiment with,and integrate,AI to drive e

24、fficiencies,boost competitive advantage,and ensure long-term sustainability and impact.These discussions reveal how operational transformation,the scaling of AI initiatives,and talent development intersect with cultural and ethical considerations to shape success.Leaders emphasize balancing short-te

25、rm gains with long-term value,underlining the importance of change management,clear governance frameworks,and a well-defined strategic roadmap.By examining both the data-driven metrics and the human element behind AI integration,this study provides a comprehensive view of how top executives navigate

26、 the complexities of AI adoption across industries.By pairing the breadth of survey findings with the depth of senior leadership experiences,this research identifies key success factorssuch as building internal capabilities,engaging the right external partners,and aligning AI initiatives with overar

27、ching business objectives.It aims to serve not only as a benchmark of CEO readiness but also as a roadmap for those striving to capture AIs potential in a rapidly evolving,highly competitive landscape.IntroductionAre CEOs Ready to Seize AIs Potential?6Five emerging themes emerge from our CEO engagem

28、ents that provide critical insights into how successful organizations approach AI adoption,their challenges,and the opportunities that lie ahead.By understanding these key areas,CEOs,board members,IT leaders,and business stakeholders can better navigate the complexities of AI and position their orga

29、nizations for long-term success.1.Strategic alignment:Set up to scale upA striking 64%of leaders without a formal AI roadmap report minimal returns from their initial pilots,underscoring the need to tightly anchor AI efforts to core business objectives and lead the strategic direction with a tomorro

30、w-back lens.Rather than treating AI as a standalone technology,CEOs link it directly to both near-term gains and tomorrows breakthroughs.This measured approach helps leadership double down on high-growth areas,weed out low-impact projects,and preempt potential value erosion if AI threatens an existi

31、ng advantage.Just over half of CEOs also embrace a fast-follower stanceusing focused pilots to validate ROI before scalingwhile staying ready to pivot quickly as market forces evolve.By fusing strategy with adaptability,leaders optimize AIs business impact and protect their competitive edge.This bal

32、anced blueprint sets them up to capture immediate ROI and cultivate the breakthroughs that drive future growth.2.Data readiness and integration:Overcome foundational AI hurdlesNearly two-thirds of CEOs cite disconnected or low-quality data as the main barrier preventing AI solutions from scaling bey

33、ond pilot phases,underscoring how critical robust data readiness is to any AI initiative.Siloed infrastructures,fragmented technology stacks,and inconsistent governance all limit AIs capacity to deliver meaningful insights.By tackling these foundational issues,CEOs can drive both immediate returns a

34、nd long-term opportunities,focusing on high-growth areas ripe for data-driven innovation while also avoiding the potential erosion of competitive advantages in domains with weaker data support.Piloting AI in carefully selected use cases helps test whether existing data processes can support broader

35、deployment and ensures leaders can measure outcomes before committing major resources.This measured approach balances todays impact with readiness for tomorrows breakthroughs,allowing organizations to sidestep low-probability ventures and maximize the value of robust data environments.What CEOs see:

36、The big picture of AIAre CEOs Ready to Seize AIs Potential?73.The Talent equation:AI(artificial intelligence)+HI(human intelligence)=ImpactDespite active recruitment efforts,57%of surveyed companies still lack sufficient internal expertise to meet current AI needs.This talent shortfall makes it hard

37、er to seize both immediate and longer-term AI opportunitieswhether doubling down on high-growth applications or warding off competitors where AI might erode an existing advantage.To bridge the gap,organizations blend external recruitment,consulting partnerships,and targeted internal training.Several

38、 CEOs note a preference for cultivating“data-savvy generalists”who can leverage off-the-shelf AI tools and quickly scale up skills in tandem with early pilots.This incremental method delivers tangible ROI while preparing the workforce for more sophisticated deployments.By concentrating on near-term

39、wins yet staying flexible enough to pivot toward breakthrough projects,leaders ensure AIs benefits extend well into the future.4.Effective AI governance:Mitigate risks from day oneOnly 22%of organizations with AI governance councils consistently trackbias-detection metrics,signaling that oversight i

40、s still evolving.While many firms rely on existing committees or compliance teams,formal governance frameworkscomplete with cross-functional councilsprove more adept at curbing risks like bias,regulatory pitfalls,and ethical missteps.This foresight enables leaders to secure steady,near-term payoffs

41、without jeopardizing future credibility or competitive standing.Moreover,CEOs who invest in governance early can avoid eroding value in areas vulnerable to AI-driven disruption.By enforcing clear guidelines and continual risk assessments,they set a sturdy foundation for AI initiatives that scale res

42、ponsibly.Over time,these structures will grow in parallel with AI expansion,ensuring boards and executives remain informed and agile as regulatory and ethical landscapes shift.5.Change management:Take the team with youDespite only 39%of high-performing AI adopters citing dedicated change management

43、frameworks as a key success factor,leaders who invest in this area see smoother rollouts and stronger adoption.By proactively addressing job-security fears and skill gaps,CEOs can uphold near-term performance while preparing employees for future AI use cases.Failing to do so often triggers cultural

44、friction,stalled pilots,and missed opportunities.Interviews show that many frontline and senior staff fear displacements,especially in labor-intensive roles.Transparency and focused upskilling assuage these worries,aligning AI with immediate productivity gains and longer-term workforce transformatio

45、n.This measured approach helps leaders avoid misallocated resources on low-impact changes and protects current advantages against AI-driven shifts in the market.78%71%19%of CEOs have measurable confidence in extracting value from AIof traditional incumbent companies incorporate total cost of ownersh

46、ip in AI business casesspecifically aiming at next-gen AI innovationEnergyIndustrialTechTraditional Incumbent(10+years)Customer Satisfaction 76%Supply Chain Resilience 42%Factor TCO in FeasibilityDigital Native(10 years)Revenue Growth,Cost ReductionInitial Capital Costs 35%More Agile But Less Struct

47、ured Governance75%64%57%AI Success RateDigital Native Firms Have a Different AI Focus Than Traditional Incumbent FirmsAre CEOs Ready to Seize AIs Potential?8Perception vs.reality:How AI ready are CEOs?CEO Perceptions and PreparednessThe shift to AI is no longer speculative89%of surveyed CEOs acknowl

48、edge the strategic importance of leveraging AI for business transformation,yet only one in four CEOs feel fully prepared to integrate it across their organizations.The gap between recognition and readiness highlights a profound challenge:AI demands not just technological adoption but a reimagining o

49、f decision-making,culture,and competitive strategy.CEOs perceive these challenges and their preparedness as being where AI is both a differentiator and a disruptor.Are CEOs Ready to Seize AIs Potential?9The incorporation of generative AI into business strategy has become a defining challenge and opp

50、ortunity for modern CEOs.Across industries,leaders are recognizing AIs potential to transform operations,drive innovation,and redefine competitive dynamics.From initial exploratory applications to long-term transformative visions,the journey of AI adoption reveals a mix of optimism,strategic caution

51、,and profound insights into the evolving role of technology in business.This section explores the perspectives of global CEOs on AIs transformative potential,shedding light on their priorities,challenges,and aspirations.For many CEOs,the journey begins with incremental adoption,focusing on manageabl

52、e use cases that deliver immediate value.The CEO of a North American financial services company articulated this approach by noting,We are starting with pedestrian applications like customer statement generation and regulatory processes.These initial steps are critical not only for demonstrating val

53、ue but also for building organizational confidence in AI capabilities.Similarly,the CEO of a global retail refrigeration solutions company emphasized the importance of test cases,stating,2025 is our target year for significant AI investments,and were focusing on learning from small-scale experiences

54、 to inform broader applications.These early wins establish a foundation for trust and readiness,paving the way for more ambitious AI initiatives.As organizations progress,the focus shifts to leveraging AI for transformative applications that reshape industries.The CEO of a South American security fi

55、rm has a vision for the security industry that illustrates this trajectory.He described a shift from manpower-intensive operations to hybrid solutions integrating AI and human expertise:The goal is to use AI to provide proactive security solutions,such as identifying patterns and predicting potentia

56、l threats.This shift from reactive to proactive strategies demonstrates how AI can fundamentally alter the value proposition within an industry,driving efficiency while enhancing outcomes.Similar advancements are seen in industries like healthcare,where predictive analytics can identify high-risk pa

57、tients before serious conditions develop.Central to these transformations is the strategic value of data,a theme echoed by many CEOs.The CEO of a North American financial services company highlighted this by stating,The high valuation of data companies is a testament to the power of leveraging data

58、effectively.AIs ability to process vast datasets enables organizations to uncover actionable insights,whether through predictive analytics in healthcare,CEO perspectives on the transformative potential of AIIn three years time,things will drastically change when it comes to the impact of AI.We know

59、that in a few years,we wont need people to do the job.It will be AI-driven.CEO of a global staffing firm,headquartered in EuropeAre CEOs Ready to Seize AIs Potential?10as noted by the CEO of a North American insurance company,or through personalized marketing in the fashion industry,as outlined by t

60、he CEO of a European retail clothing manufacturer.These data-driven applications not only optimize current operations but also unlock new revenue streams and competitive advantages.As the European clothing manufacturing companys CEO explained,We are outlining a long-term plan for AI,including innova

61、tion in fabric and machine development,which is a five-year goal.This level of strategic planning can transform industries traditionally reliant on humans in the process.CEO overconfidence can mask organizational under confidenceAlthough 78%of CEOs strongly believe in their ability to guide AI,only

62、28%of mid-level managers share this optimism about their firms overall readiness.This mismatch points to a hidden cultural hurdle:Top-down enthusiasm for AI can overlook lingering anxieties about job security,skill gaps,or insufficient governance at the operational level.Executives who recognize and

63、 address this internal under confidencethrough transparent communication,structured upskilling,and clear metricstend to unlock deeper adoption and more resilient AI outcomes.Incumbent organizations tend to prioritize long-term goalsCompared to digital natives(less than 10 years in operation),traditi

64、onal incumbents(more than 10 years in operation)place heavier emphasis on improving customer satisfaction(76%)and shoring up supply chain resilience(42%)when deploying AI.In addition,71%weigh total cost of ownership(TCO)over mere upfront spendunderscoring a multi-year view of AI investments.Yet inte

65、rviews reveal that legacy infrastructures in these organizations often come with deeply siloed data and complex governance hurdles,slowing down early pilots despite their commitment to robust,long-range returns.Once they address data unification,however,incumbent organizations typically see pilot wi

66、ns as stepping stones to broader,enterprise-wide AI transformationsfurther cementing their propensity to plan and invest for the long haul.Traditional Incumbent Organizations Focus Areas in AI DeploymentTraditional incumbent firms prioritize long-term goals like customer satisfaction,TCO,and supply

67、chain resilience.Challenges:Legacy systems,siloed data,and governance hurdles slow early pilots.Figure 1:Incumbent firms emphasize TCO,customer satisfaction,supply chain with AIFocus AreasCustomer SatisfactionSupply Chain ResilienceTotal Cost of Ownership(TCO)200406080100Percentage of Organizations(

68、%)76%42%71%Are CEOs Ready to Seize AIs Potential?11CEOs confident in AIs value creation abilityAcross the board,80%of surveyed firms report at least moderate confidence in extracting measurable value from AIyet only 19%say they actively position AI for transformative growth rather than near-term gai

69、ns.This paradox emerged clearly in CEO interviews:while most leaders see AI as a game-changer for operational efficiencies or cost reduction,few have fully mapped out how to leverage advanced capabilities for higher-impact use cases.That gap partially explains why industries like energy,manufacturin

70、g,and technology report the highest rates of AI successeach nearing or exceeding 60%as they integrate AI into complex workflows more readily such as predictive maintenance and automated quality checks.But this isnt always the case.Sectors facing fewer competitive pressures or immediate customer dema

71、nds,such as hospitality suppliers or B2B manufacturing,often invest in AI pilots to build confidence and demonstrate“quick wins,”with the intention of scaling once they have concrete proof of ROI.Regardless of industry,the consensus remains that AI is poised to deliver strategic advantages if organi

72、zations can bridge the divide between strong initial optimism and structured,long-term adoption.Sustained focus outperforms a more frenzied catch-up approachOrganizations struggling to show AI results are more likely to employ highly aggressive strategies58%of companies with no measurable AI outcome

73、s pursue“catch-up”style rollouts,compared to just 45%among those reporting success.Contrary to expectations,CEO interviews reveal that a rush to achieve immediate market parity often bypasses key preparatory steps like thorough data readiness,pilot validation,or structured change management.By contr

74、ast,firms that methodically plan for iterative deployments,ensure cross-functional buy-in,and tie AI initiatives to well-defined long-term metrics see more consistent gains.Many leaders note that a slower,more deliberate approachone which balances near-term wins with infrastructure and cultural read

75、inessultimately fuels broader and more sustainable AI impact.The collective edge:Distributed leadership strengthens AI outcomesData shows that 92%of CEOs not seeing tangible AI results insist on leading AI strategy themselves,compared to only 59%in organizations achieving measurable success.This gap

76、 suggests that centralized,top-down control can hamper domain-level expertise and hinder cross-functional collaborationboth critical enablers of sustainable AI.Interviews further reveal that when the CEO remains a strategic guide rather than a hands-on manager,resource allocation and ROI measurement

77、(49%vs.17%among unsuccessful peers)become more effectively embedded in everyday business practices.Are CEOs Ready to Seize AIs Potential?12In these winning organizations,AI initiatives are championed by specialized teams and middle managersthose who proactively integrate technology insights with ope

78、rational realitiesenabling a nimbler,results-focused approach.Leaders of high-performing AI initiatives often encourage“AI champions”in middle management to identify use cases and partner with IT on proof-of-concept projects,fostering ongoing peer-to-peer learning.This democratized approach lowers t

79、he risk of top-down mandates imposing ill-fitting solutions,ensuring AI adoption progresses organically while sustaining broader organizational buy-in.Impact of centralized,top-down managementFigure 2:The counterintuitive leadership effect:Less is often more with AI.Impact of CEO Leadership on AI Su

80、ccessCentralized,CEO-led AI strategies correlate with limited success.Effective AI initiatives thrive with domain-level leadership and operational integration.Successful OrganizationsUnsuccessful OrganizationsCEOs Leading AI StrategyEffective Resource Allocation and ROI Measurement200406080100Percen

81、tage of Organizations(%)59%49%92%17%Are CEOs Ready to Seize AIs Potential?13Limited immediate customer demand,yet a growing internal pushMany CEOs report minimal direct pressure from customers to adopt AIonly 24%cite explicit client requests for AI-based solutionsyet over half acknowledge feeling a

82、strong internal imperative to prepare for AI-driven disruption.This paradox emerged in interviews,where leaders stressed that waiting for external demands could leave their organizations behind the curve once consumer expectations shift,which they broadly expected them to do soon.Consequently,despit

83、e customer silence,59%of firms say they are actively investing in“foundational”AI pilots to build up data readiness and upskill teams,aiming to be prepared when market pressures inevitably rise.Fast-follower strategies outperform aggressive followersData shows that organizations taking a measured,fa

84、st-follower approach53%of the sampleachieve more consistent AI outcomes than those attempting immediate,large-scale rollouts.The discrepancy is especially pronounced in firms that struggled to produce results,58%of which pursued highly aggressive adoption.Interviews confirm that rapid expansion ofte

85、n exposes data fragmentation and cultural resistance before robust pilots can validate ROI.By contrast,methodical followers who fine-tune smaller AI deployments first report smoother scaling and higher confidence among stakeholders.Incumbent organizations legacy tech:Both burden and advantageIronica

86、lly,legacy IT infrastructurecited by 44%of incumbent organizations as the top obstacle to early AI pilotscan evolve into a long-term differentiator once data pipelines are modernized.Traditional incumbents often possess massive archives of historical data:a rich resource for training advanced predic

87、tive models or automating complex workflows.In contrast,digital natives may enjoy“cleaner”but less voluminous datasets,limiting the breadth of potential AI insights.Leaders who systematically tackle outdated systems while extracting value from extensive data repositories stand to create a formidable

88、 competitive moat.72%90%63%38%21%41%75%39%North AmericaLatin AmericaEuropeare AI upskillingface AI talent challengesfocusing on AI techhiring specialized AI talentClarifyingStrategicRoadmapsAcquiring Skilled AI TalentElevating Data Readinesshave formal pilot projectsRegionally Divergent AI JourneysD

89、igital Native Companies:AI Priorities45%71%80%of traditional incumbent organizations more than 10 years old emphasize sustained strategic roadmaps(vs.27%)of industrials and tech firms prioritize embedding AI talent in core teamsof CEOs value AIs role in enhancing operational efficiencyAre CEOs Ready

90、 to Seize AIs Potential?14AI-driven innovation:The need for speedAI Leadership Development and Skill GapsThe urgency for AI-driven innovation has never been more evident,as CEOs recognize its transformative potential across industries.With 80%highlighting AIs role in enhancing operational efficiency

91、 and 66%prioritizing AI to drive processes like storage and application migration to the cloud,the focus is on tangible improvements and measurable gains.This urgency reflects a profound shift in leadership priorities:leveraging AI not only as a tool for optimization but as a strategic differentiato

92、r in a competitive landscape.The next section delves into how CEOs are channeling this urgency into actionable strategies,fostering innovation while navigating the complexities of AI integration.Are CEOs Ready to Seize AIs Potential?15Regionally diverse AI journeysNorth American organizations report

93、 making more sustained progress in AI investments than other regions,with 72%focusing on workforce upskilling,75%grappling with the availability of specialized talent,and 39%engaged in formal pilot projects.Latin American companies,by contrast,rank a“robust infrastructure and technological foundatio

94、n”highest(90%),reflecting interviews where leaders stress the need to modernize core systems before taking on advanced AI deployments.Europe also shows elevated interest in specialized AI hiring(63%),particularly in sectors like manufacturing and financial services,where legacy processes require dom

95、ain-specific expertise.Across these varied geographies,the data underscores how local market pressures and infrastructure constraints shape whether organizations prioritize people,technology fundamentals,or use-case experimentation first.The Middle East and Africa are still very early with AI adopti

96、on,but CEOs cite using AI to evaluate CVs as one of the first major uses in the region.Notably,APAC also does not see AI as a major revenue generator(47%)as much as the global average(63%).Managing warehouses,stock levels,sales,optimum invoice size,and SKU composition by outlet,by channel,and by geo

97、graphy.We know that in two to three years max,this will be totally driven by AI.Divisional CEO of a global food&beverage company,based in AfricaAre CEOs Ready to Seize AIs Potential?16Startups and stalwarts divergeDigital natives appear focused on clarifying strategic roadmaps(71%),elevating data re

98、adiness(37%vs.29%for traditional incumbent peers),and acquiring skilled AI talent(67%)to maintain competitive momentum.This mirrors interview findings,where startup CEOs often describe a fast-follower mindsetrunning lightweight pilots to validate AI solutions and investing heavily in analytics-savvy

99、 hires.By contrast,incumbent organizations are more likely to emphasize“sustained viability”(45%vs.27%for digital natives)and stronger internal alignment (38%vs.25%),reflecting a longer-term lens that includes TCO considerations and historical data migrations.Moreover,interviews show that 73%of trad

100、itional incumbent firms engage AI-focused consultancies,often to modernize entrenched technology stacks and unite siloed data before scaling any disruptive AI initiatives.Figure 3:The key ways established enterprises and new startups differ on AI prioritiesStartups and Stalwarts Diverge on AI Priori

101、tiesDigital native firms focus on strategy,data readiness,and talent to drive innovation.Traditional incumbent organizations prioritize sustained viability and aligning legacy systems with AI capabilities.Digital Native CompaniesTraditional Incumbent CompanieClarifying Strategic RoadmapsElevating Da

102、ta ReadinessAcquiring AI TalentSustained ViabilityInternal Alignment200406080Percentage of Organizations(%)29%29%33%45%38%71%37%67%27%25%Are CEOs Ready to Seize AIs Potential?17Sector snapshots:AI in actionCertain industries exhibit distinct levels of comfort and self-sufficiency in AI strategy.Heal

103、thcare,for instance,shows a pronounced reliance on AI-focused consultancies(100%in this dataset)but reports lower demand for specialized AI hiring(40%),suggesting that many providers prefer to outsource advanced modeling and data science work.Figure 4:Heatmap of CEO concerns about AIHeatmap of AI Co

104、ncerns by IndustryAutomotiveBusiness ServicesConsumer ProductsEnergy&UtilitiesFinancial Services&InsuranceFood&BeverageGovernment/Public SectorHealthcareInformation TechnologyManufacturing&IndustrialReal Estate&ConstructionRetail/Online RetailTelecommunicationsTravel&Hospitality0.50.50.50.50.00.00.0

105、1.00.50.50.00.51.00.00.01.00.750.00.01.01.00.00.01.00.50.50.00.51.00.00.50.00.670.330.330.331.00.00.330.670.01.00.00.01.00.00.01.01.00.00.01.01.00.00.01.0Data Privacy&SecurityOperational DisruptionsROI UncertaintyTalent AdaptationIndustryProportion WorriedAI ConcernsEnergy organizations prioritize w

106、ell-defined governance policies(63%)and robust infrastructure(88%),leveraging AI primarily for predictive maintenance and real-time optimization while dedicating fewer resources to talent acquisition(38%)or internal training(25%).Finance respondents show relatively low concern about data accessibili

107、ty(38%)yet are more advanced in automated compliance and risk analyticsan observation corroborated by CEOs who speak of stable,well-governed data practices in financial institutions.0.00.20.40.60.81.0Are CEOs Ready to Seize AIs Potential?18Partnerships power progressIndustries diverge widely in how

108、they collaborate with external parties to close AI capability gaps.In finance,88%of respondents are building internal training programs,potentially leveraging AI solutions for transaction monitoring or fraud detection without wholly relying on technology vendors.By contrast,sectors like consumer pac

109、kaged goods(75%),industrials(71%),and technology(71%)emphasize recruiting specialized AI talent,aiming to embed data science know-how in core product and operational teams.It was also clear in interviews that the so-called big tech firms such as Microsoft are leading in tech partnering.Meanwhile,med

110、ia organizations lead the use of managed AI services from technology providers(69%),a pattern that emerged in interviews with leaders who value rapid deployment and lower in-house overhead for high-volume content analytics.These differences illustrate how AI partnerships are shaped by each sectors r

111、eadiness,strategic goals,and capacity to nurture internal expertise,with a number of CEOs saying they are primarily working with partners who are already experts in their industry.Yet AI expertise isnt everythingAlthough technology and consumer packaged goods firms report an above-average focus on h

112、iring specialized AI talent(at or above 70%),interviews reveal a recurring gap:nearly half of these same organizations cite incomplete data governance or inconsistent data pipelines as barriers to scaling beyond pilot phases.In several cases,well-funded recruitment efforts outpace the foundational i

113、nfrastructure needed to deploy advanced analytics reliably.Leaders caution that without parallel investments in data readiness and robust project oversight,newly hired data scientists may struggle to deliver the strategic and operational gains executives anticipate.For many,the lesson is that meanin

114、gful AI impact hinges not just on expertise but on aligning that expertise with enterprise-wide data integrity.External experts as catalysts instead of crutchesWhile 73%of traditional incumbent organizations and 100%of healthcare respondents rely on specialized,AI-focused consultancies,recent interv

115、iews suggest an emerging shift:leaders now aim to transition from full outsourcing toward co-development arrangements.Under this model,domain experts within the company partner closely with external specialists to shape AI solutions that reflect both technical rigor and real-world operational nuance

116、s.Nearly 60%of CEOs in these collaborative efforts highlight the importance of skill transfer during the engagement,ensuring internal teams gradually build up the capacity to manageand ultimately innovate uponAI systems themselves.This blend of outside expertise and insider perspective has yielded f

117、aster pilot successes and reduced long-term consultancy dependency.19%77%70%North AmericaLatin AmericaEuropecite data readiness as a pressing challenge seek AI project guidancestruggle with talent and skills,especially in advanced analyticsSuccess driven by pilot squads and internal AI championsStro

118、ng R&D collaborations63%89%cite a need for expert guidance on AI project managementwill leverage AI for strategic transformationRegional ImperativesAre CEOs Ready to Seize AIs Potential?19Equipping leaders for the AI-enabled eraInnovation and Urgent Need for AIOverall,the data suggests that region-s

119、pecific constraints strongly shape whether organizations zero in on data foundations,skilled workforce,or real-time analytics support as their most urgent leadership development priority.Across the board,AI leadership readiness has emerged as a critical factor for success.Our survey reveals that 89%

120、of CEOs actively leverage AI for strategic improvements,but only a fraction feel their leadership teams are adequately prepared to guide these efforts.This disconnect underscores a pressing need for upskilling,with a particular focus on fostering a deeper understanding of AIs capabilities,risks,and

121、ethical considerations.Developing these skills at the leadership level will be paramount,enabling organizations to implement AI effectively and navigate its complexities with confidence and foresight.The following section explores CEOs strategies to bridge these gaps and cultivate leadership that ca

122、n thrive in an AI-driven world.Resistance&Misalignment(Traditional Incumbents)Rely on Consultancies(Traditional Incumbents)Lack Strategic Vision (Digital Natives)Cross-Department Alignment (Digital Natives)20040608010038%73%51%45%Traditional Incumbent vs.Digital Native Companies:AI ChallengesAre CEO

123、s Ready to Seize AIs Potential?20North America and Europe:Fewer “building block”obstaclesNorth American and European organizations generally report fewer core dependencies blocking AI adoption,with only 19%of North American firms flagging data readiness as a pressing challenge.In Europe,77%of CEOs w

124、ant advice on AI project management and implementationthe highest among surveyed regionssuggesting a desire to better understand how best to structure successful AI efforts.By contrast,Latin America struggles significantly with talent and skill availability(70%),especially in advanced analytics and

125、data science.Asia,meanwhile,exhibits an elevated need for guidance on real-time decision support(50%),a gap often traced back to siloed infrastructures and underfunded change management.In interviews,CEOs from North America highlight that smaller“pilot squads”and internal AI champions drive successf

126、ul rollouts,whereas leaders in Latin America frequently seek external partnerships or vendor-provided training.Europes comparative advantage also correlates with well-established R&D collaborationsoften university-ledthat yield practical frameworks for evaluating AI ROI.Traditional incumbents intern

127、al hurdles vs.digital natives strategic vision gapTraditional incumbents report encountering more resistance and misalignment among internal stakeholders,with 38%marking it as a major barrier,compared to 25%in digital natives.Paradoxically,these same older organizations typically enjoy richer histor

128、ical datasets,enabling them to test AI initiatives at scale once they secure executive-level buy-in.Digital natives,on the other hand,appear more agile but often lack a cohesive,meaningful strategic vision(51%)a discrepancy echoed in CEO interviews,where startups race to integrate AI yet scramble to

129、 define a roadmap that resonates across departments.Across all age groups,63%of companies cite the need for expert guidance on AI project management and implementation,revealing a widespread skills gap in orchestrating AI initiatives from pilot to production.Some incumbent firms bring in specialized

130、 consultancies to navigate legacy systems and entrenched processes,while digital natives attempt to recruit cross-functional“AI champions”who can bridge technical and strategic objectives.Ultimately,aligning We are trying to free up time for tech-skilled employees to work on AI projects.This approac

131、h allows employees to focus on new AI projects,creating a self-sustaining cycle of innovation.CEO of a media and entertainment company,based in EuropeAre CEOs Ready to Seize AIs Potential?21internal forces remains an intricate,high-stakes leadership challenge for both mature corporations and nimble

132、startups alike.Industries wrestling with different challengesDisparities in AI strategy and governance vary by sector.Industrials and technology struggle with clear roadmaps(57%),even with tech expertise,while 50%of operations teams cite gaps in AI ethics and governance,critical in manufacturing,log

133、istics,and supply chains.Interviews reveal tech leaders excel at pilots but lack unified ethical frameworks,often seeking external guidance.Finance prioritizes advanced risk analytics within compliance structures over data accessibility.These nuances highlight the need for tailored leadership develo

134、pment,aligning AI strategies with sector-specific operational challenges and priorities for effective implementation and long-term success.Cross-functional training for AI takes center stageAn emerging insight in both traditional incumbents and digital natives is the recognition that AI leadership c

135、annot reside solely within IT or specialized data-science teams.Close to 45%of all firms surveyed plan to institute organization-wide AI literacy programs within the next 12 months,aiming to equip department heads in marketing,operations,and finance with baseline technical fluency.Interviews reveal

136、that senior executives in particular benefit from these cross-functional training efforts,as it strengthens collaboration and reduces friction when scoping AI projects.In several success stories,line-of-business managersnewly trained in the fundamentals of analytics and machine learningbecome highly

137、 effective AI“champions,”bridging the gap between data experts and frontline employees.This more inclusive approach accelerates pilot approvals and speeds up proof-of-concept validation,further reinforcing that AI adoption hinges on a concerted,holistic upskilling strategy.Pragmatic ROI goals obscur

138、e responsible AI leadershipBoth ethics and governance challenges stall AI initiatives for 37%of leaders,with operations leaders particularly emphasizing the need for algorithmic accountability.CEOs often prioritize early ROI demonstration,leaving less focus on ethical standards.In response,industrie

139、s like healthcare and finance are piloting ethics committees or AI review boards to address compliance and strategically allocate AI resources.By treating governance and ROI as complementary,executives can mitigate risks,from ethical to technical,while fostering trust.A proactive approachcombining d

140、ata security,ROI strategies,workforce training,and transparent governancepositions organizations to harness AIs transformative potential confidently and responsibly.Are CEOs Ready to Seize AIs Potential?22As AI redefines industries,governance and ethical considerations become business imperatives fo

141、r CEOs.Eighty percent of CEOs view ethical riskssuch as biased decision-making,privacy violations,and accountability gapsas significant barriers to AI adoption.Despite this,fewer than half report having a formal AI governance framework.This disparity suggests an urgent need to embed governance and e

142、thical oversight into AI strategies.Establishing clear accountability,building diverse datasets,and prioritizing transparency will be critical to mitigate risks and foster trust among stakeholders.This section delves into the steps organizations take to align AI innovation with responsible practices

143、.Surprisingly,digital natives are more worried about AI risksDigital natives rank the reliability of AI systems(39%)among their top concerns,reflecting fear of technical failures or unanticipated outcomes during early-phase deployments.By contrast,incumbent organizations are more focused on aligning

144、 AI initiatives with recognized industry standards(49%)and achieving tangible ROI(49%).Interviews confirm that these mature organizations,often juggling legacy infrastructure and larger datasets,want robust guidance from regulatory bodies and professional associations before fully embedding AI into

145、core operations.Meanwhile,digital natives exhibit leaner decision-making structures,allowing them to experiment with AI prototypes more quickly but also leaving them more vulnerable to reliability hiccups that can erode stakeholder confidence.AI governance and ethical considerationsWe are not well-p

146、repared for handling AI failures and ethical issues.Regular crisis management procedures are probably not sufficient for AI-related incidents.CEO of a food,beverage,and pharmaceutical equipment supplier,based in EuropeAre CEOs Ready to Seize AIs Potential?23AI breaching borders:Regional priorities h

147、indering global convergenceFirms in North America place a premium on data privacy and security(72%),citing concerns about breaches and the reputational damage of mishandled dataoften driven by high regulatory visibility in areas such as finance and healthcare.Despite this security-first mindset,Nort

148、h America shows relatively low adoption of explicit ethical guidelines(42%)and bias-detection measures(36%),underscoring a gap between technical safeguards and broader governance frameworks.In contrast,where 41%express concern over transparent governance and accountability,Asia prioritizes internal

149、AI ethics committees and expands board-level oversight.At 40%,Latin America highlights compliance with evolving regulations as a key worry,driven in part by uncertain local and regional policy environments.Interviews reinforce these findings:while North American and European markets emphasize techni

150、cal controls,many APAC and Latin American leaders view transparent accountability and regulatory clarity as essential to long-term AI viability.By contrast,European CEOs cite they are relatively unprepared for risk compared to their North American peers.Industries vary in governance and ethics appro

151、aches to AISectors also diverge in how they embed AI governance.Consumer packaged goods(CPG)companies lead in conducting regular audits and assessments(83%),though only 25%report collaborating frequently with external experts on ethics.Health-related organizations,conversely,post the lowest levels o

152、f data privacy concerns(20%),suggesting that existing patient confidentiality norms already guide internal data practices,though interviews reveal that these same healthcare firms rarely implement staff training or awareness programs for AIa potential blind spot if frontline medical professionals an

153、d administrators remain unaware of algorithmic risks.Meanwhile,a strong minority of industrial and technology CEOs highlight cross-functional task forces tasked with aligning AI innovation strategies to legal and regulatory frameworksa model that ensures new AI solutions undergo a rigorous review cy

154、cle before deployment.Stronger governance equals better AI outcomesOnly 17%of CEOs in underperforming organizations list AI governance,ethics,and risk management as explicit C-suite or Board responsibilities,compared to 45%among those with meaningful AI success.A similar pattern emerges around indus

155、try standards:just 16%of less successful firms engage with external best practices,whereas 51%of higher-performing peers do so,reinforcing that clearer,more consistent oversight yields more reliable results.Several interviewees indicate that thorough governance prevents ballooning risks,such as undi

156、scovered algorithmic bias or brand-damaging compliance failures,thereby accelerating user adoption and stakeholder confidence.For many,adopting recognized standardsor crafting internal equivalentsbridges the trust gap between senior leadership,frontline staff,and regulators,enabling AI projects to t

157、ransition more smoothly from pilot to production.The rise of internal ethics review boards:An early signalA subset of industrial and healthcare firms say they are establishing dedicated AI ethics boards composed of IT,legal,and operational leaders.Although under 20%of organizations surveyed currentl

158、y use such boards,these committees highlight a likely key opportunity for a proactive approach to resolving ethical“gray areas”before AI models go live.Are CEOs Ready to Seize AIs Potential?24AI security loopholes likely in non-financial sectorsWhile financial institutions commonly embed security re

159、views into every phase of AI deployment,industries like CPG and media appear more exposed.Interviews suggest that only half incorporate robust cybersecurity frameworks into AI rollouts,leaving potential vulnerabilities unchecked.As AI permeates more functions,bridging that security-ethics gap may be

160、come a vital strategic step for boards and C-suite executives.Ensure clean,connected data for effective AI functionality.Protect intellectual property when using AI systems,especially public models.Develop special crisis management processes for potential AI failures or mistakes.Protect sensitive da

161、ta,particularly when using external AI services.Ensure AI decisions are explainable and transparent,especially in regulated industries.A Blueprint for Success:Top Governance Action Items Cited by CEOsImplement safeguards to prevent discrimination and promote transparency in AI decisions.Navigate AI

162、regulations while maintaining competitiveness.Acquire and develop expertise to implement and manage AI initiatives.Maintain ownership and control over AI systems instead of relying solely on external providers.Align cross-functional teams on AI strategy to bridge departmental gaps.47%64%North Americ

163、aAsia PacificEuropeof North American companies emphasize effective communication for cross-functional alignment.Focus on short-cycle planning and proof-of-concept validation to mitigate compliance risks.of APAC organizations prioritize rigorous ROI and impact evaluations,reflecting limited risk tole

164、rance.63%75%that believe the C-suite is key to measurable gainsof CEOs not seeing significant AI success believe the C-suite must set the strategic AI visionRegional InsightsAre CEOs Ready to Seize AIs Potential?25Strategic agility,change management,and decision-making enhanced by AIStrategic Leader

165、ship and AI VisionAs organizations increasingly integrate AI into their core operations,leaders are redefining how strategies are set,how teams adapt,and how decisions are made in real time.Whether focusing on near-term process optimization or far-reaching digital transformation,the interplay betwee

166、n C-suite guidance,change management capabilities,and technology integration emerges as a decisive factor in achieving meaningful AI outcomes.Below,we examine how strategic leadership,regional priorities,cross-departmental collaboration,and emerging obstacles shape the path from AI experimentation t

167、o tangible successunderscored by interviews and survey data insights.IP&Licensing ComplexitiesIntegrating AI into Existing Tech StacksAdjusting Work&ProcessesCross-Functional Alignment20040608010024%32%63%62%Change Management HurdlesAre CEOs Ready to Seize AIs Potential?26Should the C-suite be setti

168、ng the strategic vision?Data indicates a nuanced relationship between top-level oversight and AI success:75%of CEOs not seeing significant AI results believe the C-suite must set the strategic AI vision,compared to 67%among leaders who do report measurable gains.Interestingly,the discrepancy is narr

169、ower in certain sectors:93%of industrial companies and 92%of CPG companies affirm the importance of having executives set high-level AI goals.Interviews confirm that while top-down leadership can provide resource clarity and enterprise-wide alignment,excessive CEO involvement occasionally stifles do

170、main experts who might otherwise champion localized,high-impact use cases.Striking the right balancewhere C-suite leaders define a coherent roadmap yet empower specialized teams to innovateproves critical for sustainable AI-driven growth.Geography shapes the AI game planRegional differences also inf

171、luence how AI-based strategies and decision-making processes evolve.North American organizations are most concerned about effective communication(47%),suggesting the need for consistent cross-functional messaging and stakeholder engagement.Meanwhile,64%of Asian companies emphasize rigorous impact an

172、d ROI evaluationslikely reflecting limited risk tolerance in markets where regulatory landscapes are evolving.Latin American leaders,consistently navigating high regulatory ambiguity,report significantly more energy devoted to short-cycle planning and proof-of-concept validation to mitigate complian

173、ce and operational risks.These nuances indicate that the locus of AI decision-makingbe it around communication,impact measurement,or compliancecan shift dramatically based on local market pressures and cultural expectations.Adapt to endure:The old guards priorityData shows that companies seeing no A

174、I results are more likely to cite cross-departmental change management support as pivotal(58%vs.26%among successful peers),suggesting that those struggling often realize too late how crucial organizational alignment is to adoption.Interviews confirm that traditional incumbent organizationsoften encu

175、mbered by legacy processesneed systematic change strategies to navigate entrenched silos and unify different teams around an AI roadmap.Conversely,digital natives can move faster but may lack the structured governance or managerial experience necessary to handle large-scale rollouts.Overall,the abil

176、ity to socialize AI initiatives internallythrough pilot successes,ongoing training,and open channels of feedbackemerges as a force multiplier for both near-term productivity gains and longer-range transformation.Were finding lots of opportunities with AI for operational efficiencies,but not so much

177、in ways to re-invent our business yet.CEO of a global printing and packaging supplier,based in North AmericaAre CEOs Ready to Seize AIs Potential?27Bulldoze barriers to unleash AICompanies point to building cross-functional alignment(62%)and adjusting workflows and processes(63%)as their leading hur

178、dles when integrating AI into daily operations.Beyond cultural resistance,practical challenges like integrating with existing tech stacks(32%)or navigating IP and licensing complexities(24%)often delay or derail promising initiatives.This strain is especially visible in the operations sector,where 7

179、1%cite workflow reconfiguration as a top concern,overshadowing other change management obstacles that remain below 51%.Observational data from interviews reinforces that a thoughtful approach to technology retrofittingpaired with robust project oversightcan preempt many of these friction points,ther

180、eby allowing AI projects to scale without repeatedly getting entangled in legacy-system intricacies or ownership disputes.Pilots the prime catalyst for dynamic decision-makingOne key emergent trend is using small-scale AI pilots to refine decision-making processes on the fly.Around 42%of interviewed

181、 CEOs from industrial and manufacturing backgrounds report assigning limited cross-functional teams to test AI-driven quality checks or predictive maintenance modules.These controlled pilots enable leadership to make data-backed judgments on where to expand AIs footprint,exposing gaps in data hygien

182、e or team skill sets.By reviewing pilot outcomes in real timeoften weeks rather than monthssenior managers can rapidly pivot resources or reshape project scopes,demonstrating a more agile approach to AI governance and budgeting.AI on the fly:Real-time operational adjustmentsAnother key insight from

183、both data and interviews is the growing reliance on AI for reactive,near-real-time decision-makingparticularly in supply chain and logistics.Over half(52%)of CEOs overseeing complex global distribution networks say AI-based dashboards have improved on-the-spot choices about inventory movement,capaci

184、ty planning,and route optimization.Although these capabilities demand advanced analytics,transparent governance,and consistent data flows,they also enhance agility in volatile markets,enabling line-of-business managers to course-correct operations without waiting for quarterly reviews.When combined

185、with structured change management and well-defined strategic goals,such real-time feedback loops can significantly increase an organizations resilience and competitive edge.215Set the North Star,Empower the Trailblazers Push vision from C-suite,delegate execution to the expert.Flatten and decentrali

186、ze hierarchies for faster results.Pilot,Prove,and Propagate Start small with big impact with discrete,high-value,lower-risk use cases.Scale only after proof-of-value.Resist the catch-up trap.43Data Is the Oxygen,People Are the Engine Modernize infrastructure relentlessly with unified,high-quality da

187、ta engine.Invest in holistic AI talent.Upskill your entire workforce.Cultivate a Fearless AI Culture Quell job-security fears with transparency.Communicate early and often on AI strategy.Reward experimentation and cross-functional collabs that bring together teams.Oversee AI with Integrity,Evolve wi

188、th the Times Install non-negotiable ethical guardrails from day one.Establish authoritative AI governance.Adapt and refine policies to stay credible and instill stakeholder trust.Are CEOs Ready to Seize AIs Potential?28Ignition to innovation:The CEO playbook for AIThe Five-Point CEO Playbook for Bre

189、akthrough AI OutcomesAs CEOs grapple with integrating AI into their organizations,a clear set of priorities and practices is vital for driving efficiencies,unlocking innovation,and accelerating growth.Drawing on survey data and in-depth interviews,these five recommendations blend strategic guidance

190、with practical execution tips,offering both a blueprint and playbook that separate tomorrows market leaders from todays followers.1.Set the North Star,Empower the TrailblazersStop micromanaging AI.Establish a bold,top-level vision for AI but delegate day-to-day execution to specialized teams.High-pe

191、rforming firms see greater success when CEOs focus on strategic oversightensuring AI aligns with product roadmaps or market-entry decisionswhile functional experts target low-complexity,high-impact wins(like automating repetitive tasks)to quickly demonstrate ROI.By training senior leadership to inte

192、rpret AI insights and tying near-term efficiency gains to long-term objectives,you set the course for sustainable growth.2.Pilot,Prove,and PropagateSpeed often kills AI projects.Smaller,focused pilotsbacked by structured metricsconsistently outperform rushed,large-scale initiatives.Launch a few care

193、fully scoped AI efforts to validate data readiness,confirm ROI potential,and build organizational trust.These early proofs minimize risk,cultivate alignment across departments,and fine-tune processes for replication.Once pilot results prove their worth,scale methodically to multiply AIs impact while

194、 avoiding overextension or wasted resources.Are CEOs Ready to Seize AIs Potential?293.Data Is the Oxygen,People Are the EngineAI hinges on two essentials:high-quality data and skilled teams.Eighty percent of leaders cite a well-organized data environmentoften powered by platforms like Snowflakeas cr

195、itical for fueling reliable insights.Clean,centralized data pipelines streamline pilot rollouts,reduce integration challenges,and yield stronger outcomes.In parallel,90%of CEOs identify talent gaps as a major AI hurdle,underscoring the need to train current staff and recruit domain-specific experts.

196、Formal AI courses,academic partnerships,and targeted advisory engagements help teams convert raw data into real innovationcreating a foundation for both near-term efficiencies and long-term competitive edge.4.Cultivate a Fearless AI CultureAI is ultimately about people,and cultural resistance can be

197、 the biggest barrier.Sixty-three percent of CEOs cite fear of job displacement or change as a major hurdle.Counter this by fostering transparency and active participation;run AI literacy programs,host cross-functional pilot teams,and invite employees to propose ideas that address real-world pain poi

198、nts.Frame AI as an asset that augments human potential rather than replacing it.Leaders who champion open dialogue see accelerated adoption,creative new use cases,and stronger moraletransforming employees into AI advocates rather than reluctant followers.5.Oversee AI with Integrity,Evolve with the T

199、imesGovernance matters more than algorithms.Bias,privacy,and regulatory compliance rank among CEOs top concerns,yet too few organizations formally track bias metrics or appoint dedicated ethics officers.By forming an AI governance council,integrating risk assessments,and regularly reviewing framewor

200、ks,CEOs can head off reputational threats and ensure scalability.Proactive oversight safeguards credibility,upholds stakeholder trust,and keeps AI aligned with business imperativeseven as regulations and technologies evolve.This forward-looking structure lets organizations adapt swiftly,maintaining

201、both ethical rigor and the agility to seize new AI opportunities.Are CEOs Ready to Seize AIs Potential?30The rise of agentic AIThe next frontier in enterprise automation is “agentic AI”where intelligent systems not only automate tasks but make autonomous decisions.By sidestepping the rigid workflows

202、 of traditional robotic process automation(RPA),these AI agents possess reasoning capabilities to handle complex,unstructured tasks and make strategic choices.From orchestrating complex logistics decisions to autonomously negotiating supplier terms,agentic AI represents a fundamental shift in busine

203、ss process automation.Traditional incumbents recognize agent-based AI as the next transformative wave following generative AI,moving beyond mere process automation to true cognitive decision-making.Whats more,CEOs appear to be ready for it.In the interviews,CEOs from diverse sectors highlighted just

204、 how far and fast they plan to push AI-based automation.An audit firm CEO believes AI will replace their entire core business.Staffing firms spoke of tripling digital staff,while the security industry described a proactive AI model that merges technology and personnel to outpace threats.Retail CEOs

205、anticipate self-service stores,and fashion leaders see AI cutting development time through automated fitting and grading.Others prefer AI as an enhancer rather than a wholesale replacement,while consumer packaged goods CEOs focus on optimizing core processes.While implementation approaches vary,most

206、 CEOs foresee agentic AI reshaping how business decisions are made rather than just automating processes.Leaders that master the playbook above wont just survive the agentic revolutiontheyll define it.Are CEOs Ready to Seize AIs Potential?31AI is a business capability first and a technology secondCE

207、Os almost universally believe that generative AI presents a genuinely transformative opportunity for organizations across virtually all industries.The success of AI is less about the technology and more about its broader integration into the business.However,its successful adoption requires strategi

208、c focus and careful planning.Our research highlights the importance of aligning AI priorities with organizational objectives,fostering a culture of innovation,and investing in the necessary infrastructure and talent.From vision to victoryWinners in the AI era share a common playbook:ruthless focus o

209、n operationsfrom targeting operational efficiency to building ethical governance.As CEOs navigate this era of disruption,their ability to lead with vision,adaptability,and a commitment to responsible AI in order to protect employees,customers,and the brand will determine their organizations ultimate

210、 success in harnessing this game-changing technology.Are you disrupting or being disrupted?The choice for CEOs is clear:harness AI to deliver concrete results and spark future innovation,or risk being outmaneuvered by more agile and forward-thinking competitors.Beyond the hype lies a stark realityAI

211、 success demands relentless execution,rapid stakeholder wins,and an unshakeable focus on long-term transformation.Seize the AI advantage nowFor traditional incumbents and digital natives alike,AI isnt an IT projectits the new operating model.Market leaders are already embedding AI into their DNA,spa

212、rking unprecedented collaboration and innovation.Those who act decisively unlock unprecedented growth,adaptability,and impact.Seizing the AI advantage is not just a technological pursuitit is a strategic imperative for shaping the future of global business.Ramyani Basu Partner&Global Lead,Data&AI,Ke

213、arney Are CEOs Ready to Seize AIs Potential?32AuthorsBharath Thota Partner,Data&AI,Kearney Dion Hinchcliffe Vice President of Practice,CIO,The Futurum Group Bharat Kapoor Partner&Global Managing Director,PERLab,Kearney Ben Smith Partner&Global Lead,Digital&Analytics,Kearney Khalid Khan Partner&Ameri

214、cas Lead,Digital&Analytics,Kearney Daniel Newman CEO,The Futurum Group Tiffani Bova Chief Strategy&Research Officer,The Futurum Group Michael Roemer Partner,Digital&Analytics,Kearney Dieter Gerdemann Partner&European Lead,Digital&Analytics,Kearney Are CEOs Ready to Seize AIs Potential?33Appendices A

215、ppendix#1Research methodologyThis study is based on a combination of quantitative survey data and qualitative insights from in-depth CEO interviews,offering a comprehensive view of how business leaders are navigating AI adoption.The dual approach ensures both breadth and depth,capturing overarching

216、trends while delving into nuanced leadership perspectives that bring the data to life.All participant CEOs came from companies with annual revenue exceeding$1 billion.Survey 213 CEOsRespondents were screened to ensure they held significant leadership roles,such as regional or global CEO positions,re

217、flecting a strategic level of decision-making authority.The survey covered a wide range of industries,including financial services,manufacturing,retail,and healthcare,and was designed to explore AI adoption across various functional areas and challenges.Latin America and other regions were included

218、to provide a global perspective.The survey employed a structured questionnaire with Likert-scale,multiple-choice,and open-ended questions,generating statistically significant data across key themes.In-Depth Interviews 20 CEOs These 30-minute interviews,conducted during November and December 2024,off

219、ered an opportunity to explore individual experiences,challenges,and strategies in greater detail.The interviews were structured around core themes such as AI governance,change management,integration challenges,and talent acquisition.Insights from these discussions were qualitatively analyzed to unc

220、over emerging patterns,specific examples,and unique perspectives that enriched the broader survey findings.By combining the quantitative scale of the survey with the qualitative richness of CEO interviews,this study provides a balanced and actionable analysis of how leaders are approaching AI.The me

221、thodology ensures that the results are both statistically robust and contextually grounded,offering valuable insights for organizations navigating AIs complex and transformative landscape.32%28%16%12%based in EuropeReflects Europes increasing focus on AI adoption amid evolving regulations,innovation

222、 hubs,and government-led initiatives to drive digital transformation.As AI becomes a critical factor in competitive differentiation,leaders in Europe are aligning their strategies with global trends while addressing region-specific challenges such as regulatory compliance and diverse market dynamics

223、.based in Asia PacificDemonstrates the regions growing prominence as an AI powerhouse.Countries like China,India,and Japan are investing heavily in AI research,infrastructure,and talent development.Despite these advancements,challenges such as fragmented markets and varied levels of digital readines

224、s across the region may account for the smaller proportion of surveyed CEOs.based in Latin AmericaA region where AI adoption is steadily gaining traction.Leaders here are exploring AIs potential in industries like agriculture,manufacturing,and logistics,while also addressing barriers such as resourc

225、e constraints and infrastructure development.This proportion underscores Latin Americas emerging role in the global AI landscape,particularly as governments and businesses prioritize digital transformation.This geographic diversity underscores the varied contexts in which CEOs are navigating AI adop

226、tion.Each region presents unique opportunities and challenges,offering a comprehensive view of how AI is shaping leadership strategies across the globe.Are CEOs Ready to Seize AIs Potential?34Appendix#2Geographic demographics of surveyed CEOsThe CEOs Surveyed in This Study Represent a Global Perspec

227、tive:based in North AmericaContinues to lead in AI development and adoption,driven by its strong tech ecosystem and early investments in digital innovation.Organizations in this region often benefit from access to cutting-edge AI technologies,mature venture capital markets,and a workforce skilled in

228、 emerging technologies.This aligns with North Americas position as a global leader in AI-driven industries such as healthcare,finance,and retail.6%6%based in Middle Eastbased in Africa12%8%13%Both financial services and insurance and information technology lead in representation,highlighting these i

229、ndustries advanced adoption of AI for areas such as risk analysis,customer experience,and operational efficiency.Both manufacturing and industrial and retail/online retailshowcase AIs role in optimizing supply chains,personalizing customer experiences,and driving automation.between automative(7%)and

230、 energy and utilities(6%)further demonstrates how AI is being leveraged for innovations such as autonomous systems and sustainable energy management.Are CEOs Ready to Seize AIs Potential?35Industries Represented in this StudyThe CEOs surveyed in this study represent a diverse array of industries,ref

231、lecting the broad impact of AI across different sectors.Major players include:Smaller but critical representations include industries like healthcare(4%),where AI is transforming diagnostics and patient care,and government/public sector(3%),where leaders are exploring AI for public service efficienc

232、y.While another industry not listed accounted for 0%,the diversity within the surveyed group underscores the universal interest in AI as a driver of strategic transformation across both traditional incumbents and digital natives.AutomotiveBusiness ServicesConsumer ProductsEnergy and UtilitiesFinanci

233、al Services and InsuranceFood&BeverageGovernment/Public SectorHealthcareInformation TechnologyLogisticsManufacturing&IndustrialReal Estate&ConstructionRetail/Online RetailSportsTelecommunicationsTransportationTravel&HospitalityAnother Industry Not ListedWhat Industry Is Your Organization In?0%3%5%8%

234、10%13%Figure:Industries represented in this AI studyAppendix#3Industries53%29%14%4%0%more than 10 years oldThese companies often bring extensive resources,robust data ecosystems,and mature governance structures to their AI efforts,enabling them to adopt transformative technologies at scale.8-10 year

235、s oldThese businesses are likely balancing the agility of newer firms with the growing complexity of scaling AI initiatives across enterprise operations.6-7 years old These organizations are typically early adopters of AI,leveraging it to gain competitive advantages in dynamic markets.3-5 years old

236、While these companies may lack the long-standing infrastructure of their older counterparts,they bring the advantage of flexibility and fewer legacy constraints,allowing them to integrate AI more seamlessly.1-2 years oldThe focus of this study was on established businesses with the capacity to make

237、significant investments in AI.Are CEOs Ready to Seize AIs Potential?36Collectively,the organizations represented in this study reported annual revenues of$1 billion or more,underscoring the focus on large enterprises that are well-positioned to invest in and scale AI initiatives.These companies span

238、 a range of organizational ages,providing insights into how businesses at different stages of maturity approach AI adoption and integration.The range of company ages provides a comprehensive view of how both traditional incumbents and high-growth digital natives are navigating the challenges and opp

239、ortunities of AI adoption.Appendix#4Demographics:Company size and agePUBLISHER Daniel NewmanCEO|The Futurum GroupINQUIRIESContact us if you would like to discuss this report and The Futurum Group will respond promptly.CITATIONSThis paper can be cited by accredited press and analysts,but must be cite

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