1、IBM Institute for Business Value|Research InsightsSeizing the AI and automation opportunityThe moment is now2IBM has the proven tools,insights,and expertise to help you identify and execute high-impact automation-and AI-powered solutions across your businessto make IT systems more proactive,business

2、 processes more efficient,and people more productive.For more information,please IBM can help1Leaders in generative AI adoption and data-led innovation report theyre reaping the rewards They reveal earning 72%greater annual net profits and growing annual revenues 17%more than their competitors.High

3、expectationsExecutives anticipate roughly doubling their revenue growth from AI-enabled automation in their operations in the next three years.Supercharged AI,supercharged automationAlmost nine in ten leaders in generative AI adoption(87%)say the technology helps them execute more high-impact automa

4、tion initiatives.An overwhelming consensus:benefits outweigh risks Eight out of ten respondents(82%)overall agree that benefits from generative AI are worth potential risks.We are at an opportune moment to investigate the potential that generative AI and automation create for organizations.Key takea

5、ways2IntroductionGenerative AI is everywhere.It has democratized data and accelerated the model-to-monetization cycle.Three out of four CEOs say their competitive advantage rests on it.1Companies at the forefront of generative AI adoption and data-led innovationa group we call Generative AI Leaders(

6、see Perspective,“Generative AI Leaders”)are already reaping outsized rewards,reporting 72%greater annual net profits and 17%more annual revenue growth than peers.Momentum is spreading,with 92%of C-suite executives expecting to digitize their organizations workflows and leverage AI-powered automation

7、 by 2026.2 The challenge:while some organizations speed up,others cant keep up.The widening gap between early adopters and hesitant businesses is creating a great divideone in which organizations that struggle to embrace AI-driven solutions could lose ground in an increasingly technology-driven mark

8、etplace.In response to these dramatic developments,the IBM Institute for Business Value(IBM IBV)has undertaken its most complex,far-reaching study on AI and automation.We surveyed more than 2,000 C-suite executives around the world,including Chief Automation Officers,about key strategies and investm

9、ents as they advance intelligent workflows with AI and automation to improve connectivity and scale to value(for more information,see“Research and methodology”on page 27).We also highlight our Generative AI Leaders mentioned above.The discrete group is making critical investments in this advanced te

10、chnology,enhancing AI and automation across their organizations.Eight out of ten(82%)respondents overall agree that benefits from generative AI are worth potential risks.As all facets of society navigate this new terrain,its an opportune moment to investigate the impacts and potential that generativ

11、e AI and automation create for organizations.In the chapters that follow,we dig into four critical areas:data and preparedness;workforce talent and digital assistants;the IT opportunity;and investment priorities.Along the way,we share case studies of real-world impact.Finally,we present an action gu

12、ide,with an 11-point blueprint for optimizing intelligent automation.3PerspectiveGenerative AI LeadersWhat sets them apartIs everyone getting on board the generative AI revolution?It might seem that way,but not all initiativesor enterprisesare performing equally.One-fifth of our respondents(19%)reve

13、aled themselves to be what we call Generative AI Leaders.They cite the technology as critically important to them and view generative AI capabilities as the primary driver of their automation investments.This select group is pulling away from the pack in terms of generative AI strategy and adoption,

14、and in business and technology performance.Gen AI leaders aggressively invest in automation also citing it as very or critically importantto fast-track their digital transformation agenda.They plan to accelerate performance with intelligent workflowsand are investing and scaling IT platforms and app

15、lications while decreasing IT complexity with automation.Their proactive,aggressive stance is palpablefor example,they regard automation as an accelerator to digital transformation 25%more often than their non-Leader peers(see figure).FIGURE Goals for automation investments60%56%48%53%58%74%83%66%de

16、liver better IT platforms and applicationsdecrease IT and network complexity accelerate performance with intelligent workflowsaccelerate digital transformationAll othersGenerative AI LeadersQ.On a scale of 1-5,of what importance is each of the above reasons for your organizations investments in auto

17、mation?%=respondents who answered 4 or 5.Goals for automation investments34C-suite urgency:Data that drives productivity Extreme digitalization has erupted,spawning innumerable data sources and micro-insights.Add generative AI into the equation and the impact across the enterprise and vast ecosystem

18、s is compounded.An entirely new level of sophisticated data is fueling a new level of AI,accelerating the intelligence of automated workflows.These super-automated,super-intelligent workflows can help organizations increase productivity and meet customer demandskeeping their competition scrambling.E

19、xecutives look to automation for wider business impact,of course,but theyre also advancing and extending their internal digital transformation agenda with real-time insights,decisions,actions,and resiliency.The proof is in the performance:Gen AI Leaders,with their heavier investments in automation t

20、o accelerate performance with AI-powered intelligent workflows,report outperforming their competitors in workforce agility(by 36%more),profitability and efficiency(24%more),innovation(53%more),and revenue growth(17%more).(See Figure 1.)The foundational element to all of this is data,but data is not

21、inherently valuable by its mere existence.Its usefulness depends on the transparency,trust,and security of its origins.Applying strong governance to both data management and the use of AI is essential to maintaining this usefulness.Chapter 15FIGURE 1Generative AI Leaders:Artificial intelligence,real

22、 results55%54%48%47%56%67%75%72%revenue growthprofitability/efficiencyworkforce agilityinnovationAll othersGenerative AI LeadersFor example,in our increasingly sustainability-conscious world,customers expect full transparency from the first to the last mile of the supply chain.When coupled with good

23、 governance of the data and AI pipeline,intelligent workflows make this visibility possible.But visible data does not always equate to consumable data.A corresponding need for data visualization is emergingin effect,translating and conveying data in easily understandable formats.Combined with AI and

24、 analytics,data visualization can help simulate decision impact,anticipate operational challenges,model preemptive new strategies,andof utmost importance in unprecedented timesevaluate options when theres no available historical data.Visualization and simulation are on the C-suite radar,with more th

25、an half(52%)of executives expecting these models to enable greater transparency and visibility for predictive operations.Data,AI,and automation are dependent on one another.Basically,there is no AI without data.And AI is foundational to automation.Thats why 66%of respondents say their digital transf

26、ormation initiatives will not succeed without an integrated data and AI strategy.Often,that holistic thinking needs to extend beyond the enterprise itself.For enhanced transparency and visibility,executives are increasingly integrating intelligent workflows with their ecosystem partners.In fact,53%o

27、f executives expect new technologies to enable greater transparency and visibility with those ecosystem and network digital connections.And by 2026,more than twice as many executives expect that workflows extended to ecosystem partners will be digitized with intelligent automation.Q.On a scale of 1-

28、5,how does your organizations performance compare with that of your competitors/peers over the last 3 years?%=respondents who answered 4 or 5.“We need to get to a golden processtraditional AI and machine learning interacting with generative AI,enhancing forecasting,and providing proactive alerts.”Cl

29、ient executive,semiconductor industryFIGURE 1 Generative AI LeadersArtificial intelligence,real results6Case studyBlueIT:Accelerating digital transformation and sustainability3IT outsourcing provider BlueIT is on a mission to help its clients implement an IT strategy that helps ensure performance,op

30、timizes IT spend,and reduces carbon emissions.Key to achieving these objectives is its ability to offer clients a comprehensive view of their entire IT environment and help them proactively reallocate resources to reduce waste and improve application performance.A major priority for BlueIT right now

31、 is its shift from traditional ITOps to AIOps.Before,the BlueIT team relied on disparate monitoring tools and manual intervention to optimize their clients environments.Now,they have a full-stack view and AI-powered automation.This helps the BlueIT team to identify resource congestion before the end

32、-user experience is impacted,while also reducing waste.Results Executes application resource decisioning 60%faster Reduces mean time to restore(MTTR)by 50%Reduces waste across client environments Frees up more time to help clients meet their goals“The place I see the power of the AI approach is in t

33、hese tools that can proactively show us where potential problems are and recommend actions to improve the sizing of resources and assure performance.”Francesco SartiniChief Innovation Officer,BlueIT67An evolving chemistry:AI assistants and employee collaborationWhile AI and automation can make workf

34、lows more intelligent,to truly improve business performance requires a further step:augmenting the intelligence of employees.This is an especially critical pointit means reimagining the human-technology relationship through automation.Generative AI has warranted the most buzz recently;its the latest

35、 in rolling tides of technological advances.Eight out of ten C-suite executives agree:generative AI will fundamentally transform their workflows and how people can do their jobs productively.Chapter 2“The chatbot becomes the peoples co-pilotsteering you to the report or information you are seekingmu

36、ch faster.”Client executive,consumer products industry8Gen AI Leaders report exceptional results in this realm.86%agree that investing in generative AI is a key ingredient to their automation initiatives.And eight in ten say generative AI is enabling digital assistants to support making predictions

37、and generating solution ideas to complex problems(see Figure 2).Generative AI enables better visibility,insights,and decision-making across ecosystemsGenerative AI is enabling digital assistants to make predictions and generate solution ideas to complex problemsGenerative AI is accelerating the pace

38、 of discovery to new sources of innovation63%75%85%Q.Thinking about your organizations generative AI strategy,to what extent do you agree with the above statements?%=respondents who answered agree and strongly agree.FIGURE 2 Generative AIThe key to transformative workflows49Empowering employees,remo

39、ving repetitive workAutomation can enhance productivity and reduce repetitive,tedious work.That frees up more time to focus on activities that add more strategic value to build customer and business partner relationships(see case study,“SELTA SQUARE”).Bonus:these value-add activities are often more

40、interesting for employees as well as skills-enhancing.Almost half of executives(47%)say that skills shortages could have the greatest impact on organizations over the next three years.Automation and AI can not only improve employees jobs and increase productivity,they can help bridge labor shortages

41、 and augment skills.However,those positive aspects to automation dont necessarily make for a smooth evolution.80%of executives agree that workforce augmentation can be constrained by inadequate change management.Extending a warm welcome to digitally automated support requires a distinct shift in per

42、spective,and this requires guidance and encouragement from executive leadership.Our research shows Gen AI Leaders demonstrating a particularly proactive stance.Much more frequently than other organizations,theyre easing the transition with key initiatives,such as implementing a Center of Excellence

43、around intelligent automation,using multidisciplinary teams to blend technology and business expertise,hiring a Chief Automation Officer or its equivalent,and educating staff on working with digital assistants(see Figure 3).These steps can help reskill the workforce to understand AI and automation a

44、nd and how to use them productively and properly.58%54%30%34%40%71%78%50%hired a Chief Automation Officertrained staff to work with digital assistantsimplemented a Center of Excellencehired for skillsand demographics not degreesAll othersGenerative AI LeadersQ.On a scale of 1-5,what talent initiativ

45、es has your organization pursued to support your automation strategy?%=respondents who ranked the initiative a 4 or 5.FIGURE 3 Excellent at empoweringGenerative AI Leaders lead in workforce inspiration10Case studySELTA SQUARE:A first-of-its-kind,automated process for drug safety monitoring5 Leading

46、South Korean R&D company Daewoong Pharmaceutical helped launch a new companySELTA SQUAREthats innovating a critical process that could improve drug safety for people around the world.Its a process called pharmacovigilance(PV),a legally mandated discipline for detecting and reporting adverse effects

47、from drugs,then assessing,understanding,and preventing those effects.SELTA SQUARE is using intelligent automation software to run an automated PV service that could be a game changer for the way pharma companies help ensure consumer safety.The intelligent automation software provides a vast improvem

48、ent over a critical but tedious process that involved extensive searches of databases,medical literature,and case reports as well as the names of each products active pharmaceutical ingredients.Along with the searches,PV personnel needed to take and save screenshots,download source documents,documen

49、t search results,and upload the data to a Daewoong Pharmaceutical server.The results are impressive:Results Quadrupled the speed of the PV process Reduced literature search times from five minutes to one minute Gave specialists more time to enhance PVs quality Helping to provide safer medicines“Huma

50、n experts still decide how to act upon the information,now they just get to the key information much faster.”Min Kyung ShinCEOSELTA SQUARE1011Decision-making and digital assistantsIn general,workflow automation defines how work gets done through a sequence of tasks performed by both the workforce an

51、d the digital systems that they collaborate with.By generating insights that are available as needed and that are based within a wide context,AI-powered workflows steer teams toward higher value customer and partner collaborations,complex problem-solving situations,and forward-thinking innovative ac

52、tivities.20%25%30%35%40%45%50%Traditional AIMachine learning+Generative AIMonitoring and reporting alertsMonitoring and taking actionActing on scheduled events across a workflowSupporting complex data analytics and recommendationsSupporting mission-critical decisions that alter essential outcomes31%

53、more35%46%34%more29%39%33%more27%36%38%more24%33%31%more32%42%20232026Increasingly,the digital side of the equation is acquiring more complex analysis and decision-making skills via both traditional and generative AI.More than three out of four(77%)C-suite executives report that digital assistants e

54、nable better insights and decision-making.Over the next three years,they expect digital assistants to support the workforce in making exceedingly complex and mission-critical decisions(see Figure 4).Q.For the above activities,what percentage are performed by automation tools,today and in 3 years(202

55、3 and 2026)?FIGURE 4 Mission criticalAutomated tools are expected to increasingly support complex decisions12Executives understand the potential of intelligent automation.Six in ten are investing in automation to boost workforce productivity and agility.Almost half have introduced new automation tec

56、hnologies to make operations more predictable,flexible,and intelligentespecially when automating proactive customer and employee experiences.54%are evaluating the roles of automation and AI in delivering new ways of working,with 52%citing better customer experiences as their top priority.These organ

57、izations are reconsidering essential ways of working,with automation part of a broader redesign to enhance productivity.Its a tectonic shift,with the importance of physical work location increasingly low,and opportunities to access skills and capabilities from virtually anywhere in the world escalat

58、ing accordingly.Ecosystems play heavily here as well.These new logistics require robust,defined workflows that interact with digital tools and human teams huddledoften virtuallywith ecosystem partners.And ecosystems add another consideration for all-important data because,both within the enterprise

59、and within ecosystems,that data must be consumable,flexible,and secure.“We need to measure behavior to predict behavior.”Client executive,manufacturing industry13Amplifying advantages:The automation of IT itselfWeve talked about the potential of automating intelligent workflows,and weve discussed th

60、e potent power that AI-driven automation can give employees to redesign their jobs.But were not through yet.The automation of IT itself is an often-underestimated aspect of automation strategy and associated initiatives.Here,we explore the potential financial upsides of IT automation,how automation

61、can alleviate IT risks,and why automation can make IT operations more proactive and productive overall.To shift from reactive to proactive IT management,organizations must leverage AI and machine learning algorithms to automate IT and network operations(see case study,“Electrolux”).Our research reve

62、als the potential here.While almost two-thirds of organizations(63%)automate application integration,only about half(47%)automate event streams,enterprise messaging,and API management.However,our research shows other IT automation initiatives acceleratingfast.Automation rates in IT service managemen

63、t,DevSecOps,and IT operations management are expected to double or more over the next three years(see Figure 5)and this is across all respondents,indicating a deep,across-the-board trend.Chapter 353%83%57%Network operationsmore34%74%IT service management118%more36%71%DevSecOps97%more32%74%IT operati

64、ons management131%moreTodayNext 3 yearsQ.On a scale of 1-5,to what extent is your organization automating the above end-to-end IT workflows over the next 3 years?%=respondents who answered 4 or 5.FIGURE 5 Automation soars across the board14Case studyElectrolux:A legendary innovator aims for comprehe

65、nsive AI management of IT operations6 From an Electrolux facility in northeastern Italy,a small team monitors the operational efficiency of their vast and complex global IT infrastructure that spans 10,000 servers,networking devices,and more across 65 countries.As Electrolux continues to find new wa

66、ys to automate and innovate everyday living,theyre also adopting AI-driven automation to quickly resolve IT issues worldwide to support cost efficiency and manufacturing volumes,and even contribute to ambitious environmental sustainability goals.Results IT issues resolved in one hour instead of thre

67、e weeks Less production downtime More time to enrich staff expertise Supporting a 75%reduction in CO2 emissions from operations Improved product availability for Electrolux customers“Sizing the difference amongst events and incidents is the first step to a complete AI management of operations,and pr

68、obably the one that can bring the fastest return on investment in self-learning technologies.”Joska LotGlobal Solution Service Architect:Monitoring and Events ManagementElectrolux AB1415Automation as risk-tamerWhy are organizations bullish on automating IT?For starters,theyre optimistic about metric

69、sboth from a technical performance perspective and financially.The more complex the IT environment,the better the business value of automation:80%of executives expect ROI on IT automation to increase as data center workloads grow in volume and complexity(see Figure 6).80%say that ROI on IT automatio

70、n will increase as data center workloads grow in volume and complexityGrowth in IT automation over the next 3 yearsAchieved and expected ROI from automation investments20230-3%30%77%166%mean2000160180(estimated)(estimated)TodayNext 3 years53%83%Network operations34%74%IT

71、service management32%74%IT operations managementFIGURE 6 Great expectationsIncreased IT automation,increased ROIQ.To what extent do you agree with the following statement:ROI and IT automation will increase as data center workloads grow in volume and complexity.%=respondents who agree and strongly a

72、gree.Q.On a scale of 1-5,to what extent is your organization automating the above end-to-end IT workflows over the next 3 years?%=respondents who answered 4 or 5.Q.What was the ROI on your automation investments and initiatives in 2021 and 2023?What do you expect it to be in 2025 and 2030?16Much of

73、automations value in IT lies in managing risks and issues(see Figure 7).For example,the adoption of automated governance policies helps ensure AI-generated assets can be traced back to the foundation model,data set,or other inputsand ease needed adjustments and reactions to evolving regulations.In f

74、act,80%of Gen AI Leaders say their organization has progressed toward using automated governance policies for regulatory compliance.Modeling and analysisObservabilityDynamic topologyAIOpsProactivityGovernanceAs well,artificial intelligence for IT operations,or AIOps,uses data analytics,machine learn

75、ing,and other AI technologies to automate the identification and resolution of IT issues.7 It can provide event correlation,helping organizations to predict and prevent potential outages and lessen negative impacts to the business and its customers.AIOps can help resolve unanticipated incidents more

76、 quickly while also identifying their probable causes.This can greatly reduce the manual effort required to determine what went wrong and how to avoid recurrences.FIGURE 7 Proactivity at the coreHow automation can benefit ITSource:IBM Institute for Business Value.17Dynamic topology,a dynamic tessell

77、ation sculpting method,8 visualizes data from multiple sources,offers actionable insights for issue resolution,and provides IT Ops teams with AI-based remediation suggestions to facilitate the path to resolution.And observability provides operations visibility into applications and infrastructure,to

78、 facilitate availabilitymainly through event analysis via logs,metrics,and tracing.Todays scenario and modeling analyses often combine AI,analytics,and data visualization,while also leveraging generative AI-powered computing capabilities.Simulating decision impact,anticipating operational challenges

79、,modeling preemptive new strategies,andcriticallyevaluating options when theres no available historical data are among the strengths here.The common thread?Proactivityand automation by its very name is exactly that.Its automatic,preemptive,and anticipative,with instincts honed by curated data and so

80、phisticated AI.Gen AI Leaders,in particular,demonstrate enthusiasm about automating IT operations.Over the next three years,they expect to automate IT operations management and process mining and discovery 19%more than other organizations,to name just two examples(see Figure 8).FIGURE 8Pioneering pr

81、ogress:Generative AI Leaders accelerate IT automation70%67%76%64%83%80%89%76%IT service managementIT operations managementIT networkingprocess mining and discoveryAll othersGenerative AI Leaders“When change happens,you need to align your architecture,your data structure,and your processes in a consi

82、stent way with the changing business requirements.Generative AI allows that to happen at speed.”Client executive,pharmaceutical industryFIGURE 8 Pioneering progressGenerative AI Leaders accelerate IT automationQ.On a scale of 1-5,to what extent will your organization automate the above IT operations

83、 by 2026?%=respondents who answered 4 or 5.18Follow the money:Investments equal prioritiesMoney talks,and how executives prioritize their technology investments reveals their devotion to intelligent automation.Almost seven in ten(67%)emphasize AI,natural language processing,chatbots,and machine lear

84、ning.And more than half(52%)of executives expect new technology and integration to enable greater transparency and visibility for predictive operationsenhanced with visualization and simulation.From a holistic IT perspective,60%invest in automation to decrease IT and network complexity.And 50%invest

85、 to deliver new and improved IT platforms and applications.Overall,accelerating workflow and digital transformation agendas and performance are prime motivators of automation investments.If money talks,generative AI investments have their own distinct voiceand create profound impact.Gen AI Leaders p

86、rioritize generative AI investments as critical,and theyve aligned their enterprise architecture with business activities and processes 40%more so than their peers.Additionally,these organizations are exceeding application and systems availability requirements while achieving performance goals as th

87、ey automate network operations,service management,and operations management.Applying Financial IT Operations(FinOps)technologies(see Perspective,“FinOps,GreenOps,AI,and automation”)combined with active resource management enables them to optimize IT spend while maintaining availability and performan

88、ce.Gen AI Leaders are also integrating apps and systems as they automate data flows with event streams,enterprise messaging,and API managementand they are doing this substantially more often than other organizations.For example,this elite cadre reports automating data flows with event streams 40%mor

89、e often than their peers(70%versus 50%)enterprise messaging 38%more often(65%versus 47%),and API management 28%more often(55%versus 43%).Chapter 419,PerspectiveHow FinOps,GreenOps,AI,and automation can drive sustainability goalsWith its ethereal name,cloud computing doesnt evoke images of a smog-gen

90、erating,resource-guzzling technology.Yet the“cloud”is very much grounded,existing onand impactingour planet.Consider bricks-and-mortar server farms where data is stored,and computational power supports cloud and AI applications.These buildings and systems that are,in effect,the cloud now have a grea

91、ter carbon footprint than the airline industry.9 As public awareness of this impact increases,organizations face increasing pressure to use cloud technology responsibly and sustainably.Enter FinOps and GreenOps.FinOps is an evolving cloud financial management discipline and cultural practice that en

92、ables organizations to optimize business value.This practice helps engineering,finance,technology,and business teams to collaborate on data-driven spending decisions.10 GreenOps is an operating model that integrates the technologies,techniques,and business practices that can optimize efficiency in t

93、he cloudwhile also reducing environmental impact.It fosters more efficient resource usage with better cooling,greener building materials,and smarter control systems,which are foundational to data centers.11 How do automation and AI play here?One example:AI can generate the data needed for FinOps ins

94、ights.And automating workloads can help run resources only as needed and can automatically adjust what resources are running.From a sustainability perspective,this helps to align supply to demand,effectively optimize cloud usage,and provision capacity dynamically.12 In effect,automation and AI are c

95、ommon threads running across both disciplinesand key contributors to an organizations sustainability strategy.FinOps is a portmanteau of“Finance”and“DevOps,”stressing the communications and collaboration between business and engineering teams.13 1920Automation begets automationAlmost nine in ten(87%

96、)executives expect their automation strategy to help identify and execute more high-impact automation initiatives.How?AI-powered intelligent workflows and IT automation can pinpoint the processes that could most improve business performance.By then harnessing the power of process mining data science

97、,businesses can delve into their processes and event logs,revealing critical insights into patterns,inefficiencies,and bottlenecks.This data-driven approach paves the way for targeted productivity improvements,ultimately driving optimized process performance and bolstering overall business success.I

98、n fact,more than half of Gen AI Leaders(54%)think that process mining,integrated with IT observability,will provide an enterprise view of operations and impact analysis.Also,application connectivity,with AI libraries,applications,and APIs,enables application-level sharingand potentially even more au

99、tomation.Organizations can now use open source libraries,frameworks,and tools for code-based,automated,and visual data science capabilities to tune models for specific business needs.In multiple ways,automation can lead to even more automation.Executives have high expectations for automation and AI

100、strategies to deliver results during the next three years,and they anticipate significant financial returns from generative AI.The average ROI of generative AI projects is edging up,with executives saying they expect it to exceed 10%by 2025.As a result,enterprises are planning to boost generative AI

101、 adoption over the next two years.This rapid uptick is partially fueled by familiarity:leaders today are better acquainted with generative AI than they were with traditional AI amid the initial AI hype cycle.As a result,executives have a much more focused view of where to deploy generative AI.14 As

102、well,our respondents across the board expect to roughly double their revenue growth from AI-enabled operations in the next three years(see Figure 9).All othersGenerative AI Leaders7.41%8.59%2023202616.36%18.40%FIGURE 10AI-powered prosperity:Revenue growth expected to double over next three yearsAll

103、othersGenerative AI LeadersFIGURE 9 AI-powered prosperityRevenue growth expected to double over next three yearsQ.What additional annual revenue growth is due to AI-enabled automation in 2023 and 2026?21Generative AI and automation are reshaping society,business,the workforce,and technology,and the

104、potential rewards are enormous.To understand and accelerate the promise of generative AI and automation tomorrow,what should C-suite leaders do today to remove roadblocks and mitigate risks?What can they deliver this yearand improve upon next year?At the same time,how can they integrate generative A

105、I into a broader transformation strategy?How can generative AI and automation evolve from“breaking news”to mainstream mantra?Continue to our action guide for advice,perspective,and direction.“Were getting pull from the business.Youve got to prove the value.We are moving away from the hype quickly an

106、d focusing on the things that are practical to get the value flywheel moving.Currently we have two focused performance cases:one is financial and the other one is cycle time,and we have identified specific measures that we will track associated with each.”Client executive,distribution industry22Acti

107、on guideThe path to intelligent automationOur research indicates that generative AI is not to be used sparingly.Generative AI Leaders report that this technology could have a multiplier impact,with half of these executives expecting generative AI to improve multiple aspects of their business,from de

108、cision-making to customer and workforce experiences.And 77%say there are major returns to scaling with AI.In other words,the more your organization does,the bigger the potential returns.Generative AI Leaders are not all talkand really,their results speak for themselves.These organizations report ear

109、ning 72%greater annual net profits and growing annual revenues 17%more than their competitors.While this select group comprises 19%of our total,theres good news:your organization could join their ranks,if you emulate their tactics and learn from their success(see Figure 10).Lets get started.2223FIGU

110、RE 10Exploiting AI and automationSeize the momentor miss outSource:IBM Institute for Business Value.23Foundational practicesIntegrate your datastrategy with yourautomation strategy.Focus on workforce higher-valuetasks with digital assistant and workforce collaboration.Develop agile workflows to reac

111、t quickly to escalating situations.Increase productivity with intelligent automation for real-time decisions and actions.Implement AI-driven intelligent scenario simulation and visualization.Increase visibility and security in intelligent workflows across ecosystems.Embed automated workflows with su

112、stainability circularity goals,metrics,and decision support.Generative AI leading practicesAccelerate Generative AI adoption to speed data utilization and insights.Establish governance on generative AI use and adoption to manage risks and seize opportunities.Focus on core operational use cases.Innov

113、ate with generative AI capabilities.Monitor usage and outcomes.Extend FinOps capabilities across the enterprise24,241.Integrate your data strategy with your automation strategy.Rethink processes and workflows with robust data management systems in a hybrid cloud model,combined with AI-powered automa

114、tion.Connect your business and IT with the integration tools required to connect data and operations.Tool your automation workflows with application connectivity to enable multisource application data sharing.2.Focus your employees on workforce higher-value tasks,incorporating productive workforce c

115、ollaboration using AI assistants.Increase workflow automation to enable employees to focus on higher value analysis and customer experience innovation.Empower workforce talent with AI-generated insights to advance more complex decision-making across mission-critical workflows.Create agile and scalab

116、le,resilient IT operations,aligned with modern business speed and productive pace.3.Develop agile intelligent workflows to react quickly to escalating situations.Configure workflows by assembling data in varied computing environments,supporting AI and extreme automation.Amplify AI to make these work

117、flows even smarter.Manage APIs to share third-party sources of data between applications.API management moves the data to where and when it is needed.Establish event-driven architecture so that workflows are automatically data-triggered by the detection of a situation.4.Increase productivity with in

118、telligent automation for real-time decisions and actions.Deploy AI and machine learning to allow better pattern recognition,workflow optimization,and solution gathering.Combine predictive and prescriptive analysis and insights with business know-how for better decision-making and to deliver differen

119、tiated outcomes.Train AI assistants to self-learn and provide predictive,proactive insights to boost workforce productivity,freeing their time to solve real business challenges.5.Implement AI-driven intelligent scenario simulation and visualization.Develop robust AI and automation capabilities to sp

120、eed insights and decision-making across ecosystem intelligent workflows.Apply generative AI models with visualization and simulation to uncover and proactively react to operational bottlenecks in real time.Explore digital dashboard approaches,cloud management platforms,and cloud-based process mining

121、 solutions.6.Increase visibility and security of intelligent workflows across ecosystems.Boost transparency,visibility,and security at every touchpoint in every workflow across ecosystems.Leverage the security and openness of hybrid cloud environments to deploy intelligent automation faster and more

122、 smoothly.Integrate workloads as a productive automation platformconnecting networks and applications across the enterprise.Action guideThe path to intelligent automation25,257.Improve sustainability circularity goals,metrics,and decision support.Embed while automating workflows.Optimize IT operatio

123、ns to avoid the financial and environmental costs of overprovisioning.Innovate process and data mining engineering,including configurations with lifecycle circularity considerations.Monitor transaction reliability(what happened when)with event streaming.8.Extend FinOps capabilities across the enterp

124、rise to gain visibility into costs and spending spanning all AI,hybrid cloud,and application modernization investments.Access your organizations maturity in business and engineering teamsand their initiatives.Develop recommendations and actionable key performance metrics.Map the actions and metrics

125、to specific projects,applications,and initiatives to optimize spend and outcomes.15 Utilize ROI calculators to develop options for end-state scenarios around architecture and operating patterns.9.Accelerate generative AI adoption to speed data utilization and insights.Invest consistently in the near

126、-and long-term potential of automation.Foster an open culture that encourages continuous experimentation,new skill development and ways of working,and productive collaboration.Upskill people and train them on the tools needed to speed decisions and actions.10.Focus on core operational use cases.Inno

127、vate with generative AI capabilities.Monitor usage and outcomes.Connect devices and physical assets with intelligence to provide data for process mining to understand the current state,learn from it,and act accordingly.Embed automation within these physical devices and assets,supported by AI assista

128、nts for greater productivity,responsiveness,and efficiencies.Concentrate investment in high-priority workflows,pilot,and scale with speed.11.Establish governance on generative AI use and adoption to manage risks and seize opportunities.Map the full range of preemptive data initiatives needed to conn

129、ect people and technology across the organization and its ecosystem.Enact a culture that encourages discovery and openness to change with the understanding that ideas can come from anywhere.Put in place a comprehensive governance model that encompasses all dimensions of generative AI transformation

130、in the organization and aligns to the corporate key performance indicators(KPIs).26Karen ButnerGlobal Research Leader for AI-powered automation,supply chain operations,and the Virtual Enterprise IBM Institute for Business V IvorySenior Partner and the Global Automation Leader IBM C Karen serves as t

131、he IBM Institute for Business Value Global Research Leader for AI-powered automation,supply chain operations,and the Virtual Enterprise.She is responsible for market insights,industry trends,and thought leadership inspiration.Karen is frequently invited to keynote at international conferences and is

132、 widely quoted in leading business and industry publications.Her passion is to assist clients in the development of strategies and improvement agendas to bring significant value in the digital and physical transformation of their global operations,networks,and performance.William(Bill)Lobig Vice Pre

133、sident of Product Management IBM Automation S is the Vice President of Product Management,IBM Automation Software,with a demonstrated history of working in the IT services industry.Bill has been in the software space for over 20 years.He has held various roles in IBM engineering and product manageme

134、nt,ranging from unstructured data/content management,information life cycle governance,business process management,machine learning and AI,and IT automation.Bill advises organizations on how to be more productive by automating their business processes,helping ensure the ongoing optimization of their

135、 IT systems,and helping clients modernize applications to hybrid cloud architectures.Tom is a Senior Partner and the Global Automation Leader,IBM Consulting.Tom leads a practice that enables clients to digitally transform workflows with AI,robotic process automation(RPA),process intelligence,and bus

136、iness process management,leveraging automation capabilities to fuel next-generation business operating models with the creation of a digital workforce.With over 24 years of experience in the technology services industry,Tom is a trusted advisor on how emerging technologies can drive growth for clien

137、ts.About the authors2627Related reportsAutomate to elevateAutomate to elevate:Unlocking the value potential of AI-powered process mining.IBM Institute for Business Value.May 2023.ibm.co/automate-business-processesThe power of AI&automationThe power of AI&Automation:Boosting workforce productivity an

138、d agility.IBM Institute for Business Value.May 2023.ibm.co/automation-workforce-productivityAI&Automation:Proactive ITThe power of AI&Automation:Delivering proactive IT platforms and applications.IBM Institute for Business Value.May 2023.ibm.co/automation-proactive-it IBM Institute for Business Valu

139、eFor two decades,the IBM Institute for Business Value has served as the thought leadership think tank for IBM.What inspires us is producing research-backed,technology-informed strategic insights that help leaders make smarter business decisions.From our unique position at the intersection of busines

140、s,technology,and society,we survey,interview,and engage with thousands of executives,consumers,and experts each year,synthesizing their perspectives into credible,inspiring,and actionable insights.To stay connected and informed,sign up to receive IBVs email newsletter at can also find us on LinkedIn

141、 at ibm.co/ibv-linkedin.The right partner for a changing worldAt IBM,we collaborate with our clients,bringing together business insight,advanced research,and technology to give them a distinct advantage in todays rapidly changing environment.Research and methodologyThe IBM Institute for Business Val

142、ue,in conjunction with Oxford Economics,interviewed and polled over 2,000 executives with equivalent roles and titles including Chief Automation Officer(CAO),Chief Supply Chain Officer(CSCO),Chief Operations Officer(COO),Chief Information Officer(CIO),and Chief Financial Officer(CF0).These responden

143、ts spanned 21 countries,as well as 10 industry sectors representing energy and utilities,petroleum,industrial products,electronics,telecommunications,government,healthcare/life sciences,consumer products,and transportation/logistics,each comprising 5%to 15%of our total respondent sample.The size of

144、organizations surveyed,in terms of revenue,ranges from$500 million to$500 billion.About Research InsightsResearch Insights are fact-based strategic insights for business executives on critical public-and private-sector issues.They are based on findings from analysis of our own primary research studi

145、es.For more information,contact the IBM Institute for Business Value at .281 The CEO Study:CEO decision-making in the age of AI.Global C-Suite Series.28th Edition.IBM Institute for Business Value.June 2023.https:/ The power of AI&Automation:Intelligent workflows.Data story.IBM Institute for Business

146、 Value.2023.https:/ Accelerating digital transformation and reducing environmental impact.IBM case study.Accessed October 18,2023.https:/ CEO guide to generative AI.Pulse study.IBM Institute for Business Value.2023.Unpublished data.5 A game changer in the pharmaceutical industry.IBM case study.Acces

147、sed October 18,2023.https:/ 6 A legendary innovator brings AIOps to its global enterprise.IBM case study.Accessed October 18,2023.https:/ Yasar,Kinza and Stephen J.Bigelow.AIOps(artificial intelligence for IT operations).TechTarget.Accessed September 2,2023.https:/ Garofalo,Emma.“Dyntopo in Blender:

148、Dynamic Topology for Beginners.”Make Use Of(MUO).February 17,2022.https:/ Monserrate,Steven Gonzalez.“The Staggering Ecological Impacts of Computation and the Cloud.”The MIT Press Reader.Accessed October 18,2023.https:/thereader.mitpress.mit.edu/the-staggering-ecological-impacts-of-computation-and-t

149、he-cloud/;Erdenesanaa,Delger.“A.I.Could Soon Need as Much Electricity as an Entire Country.”The New York Times.October 10,2023.https:/ State of FinOps Survey 2023.FinOps Foundation.Accessed October 18,2023.https:/data.finops.org/11 Vanara,Filippo.Rise of FinOps and GreenOpsThe Importance of These St

150、rategies in 2023 and Beyond.IDC Blog.January 19,2023.https:/blog- Workload Management&Automation.FinOps Foundation.Accessed October 18,2023.https:/www.finops.org/framework/capabilities/workload-management-automation/13 What is FinOps?FinOps Foundation.https:/www.finops.org/introduction/what-is-finop

151、s/14 The CEOs guide to generative AI.Enterprise generative AI:State of the market.IBM Institute for Business Value.July 2023.https:/ The CEOs guide to generative AI.Tech spend:How will you pay for it?IBM Institute for Business Value.September 2023.https:/ and sources 29 Copyright IBM Corporation 202

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155、y are provided.This report is intended for general guidance only.It is not intended to be a substitute for detailed research or the exercise of professional judgment.IBM shall not be responsible for any loss whatsoever sustained by any organization or person who relies on this publication.The data used in this report may be derived from third-party sources and IBM does not independently verify,validate or audit such data.The results from the use of such data are provided on an“as is”basis and IBM makes no representations or warranties,express or implied.6NKRX9NB-USEN-01