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1、The State of AI Infrastructure2024 EditionAn annual report on trends and developments in AI infrastructure based on Microsoft-commissioned surveys conducted by Forrester Consulting and Ipsos.2AI is sweeping across industries and transforming the way businesses operate,innovate,and compete.But how ar

2、e organizations actually using AI today,and what are their plans for the future?What are the main challenges and priorities they face in implementing AI at scale?And what role does infrastructure play in enabling AI adoption and performance?We explore these questions and more,based on surveys of ove

3、r 1,500 business leaders from various sectors and regions.We also share insights and best practices from leading-edge organizations that are already leveraging AI to create value and drive growth.Whether you are just starting your AI journey or looking to scale it up,this paper will help you underst

4、and the state of AI and AI infrastructure,and how to build a strategy that works for your business.3AI is here.Its just the beginning _4AI is challengingfor everyone _9AI infrastructure remains elusive _13Start with the trifecta:performance,security,and cost _17One size does not fit all _20Harnessin

5、g the power of AI now _25Take the next steps on your AI journey _27Research methodology _28Table of contents4AI is here.Its just the beginning.Welcome to the new era,where AI is not only intriguing and engaging consumers but exponentially increasing business productivity,transforming business models

6、,and reimagining customer experiences.From retail to healthcare,theres no doubt AI is making a difference in ways like:Aggregating customer data to serve personalized recommendations at scale in retail.Powering CT scanners with robust algorithms for more accurate diagnostics and improved medical car

7、e.Predicting machine lifecycles for real-time maintenance and run-time efficiencies in factories.Preventing financial fraud via real-time detection using advanced AI tools and models.Using consumer-friendly chatbots to streamline customer service processes.Recent Microsoft-commissioned research show

8、s most companies are actively ramping up their AI capabilities,with 95%of businesses surveyed planning to increase their AI usage over the next two years.Across industries,AI adoption is believed to be critical for success.Collectively,there is a consensus over the importance of AI,not just from an

9、organizational standpoint,but also from a personal standpoint.This is an important distinction these numbers show that its not only organizations that are driving adoption,but that people see the value personally.Source:A commissioned study conducted by Forrester Consulting on behalf of Microsoft an

10、d NVIDIA,May 2023Strongly agree/AgreeStrongly agree/AgreeStrongly agree/AgreeStrongly agree/Agree75%73%72%76%80%75%TotalFinanceHealthcareRetailManufacturingISVTotalFinanceHealthcareRetailManufacturingISV66%68%62%66%73%64%5AI is critical to my organizations successAI importance for successAI importan

11、ce for successAI is critical to my personal successBase:Total(n=900),Finance(n=180),Healthcare(n=180),Retail(n=180),Manufacturing(n=180),ISV(n=180)Source:A commissioned study conducted by Ipsos on behalf of Microsoft,October 20236Organizations in this final stage have fully implemented and are both

12、actively utilizing and optimizing.Deployment means that an organization has deployed in specific areas and is gradually expanding usage.Organizations in this earliest stage are in the initial stages of exploring options,gathering information,and identifying AI use cases as well as planning and strat

13、egizing their AI implementation.Organizations in the pilot stage are currently conducting small-scale implementations to evaluate feasibility and effectiveness.Organizations are in different stages of AI implementation Organizations are in different stages of AI implementation 38%15%25%22%Many organ

14、izations are at the starting lineMore than a third of companies are in the early stages of AI adoption:exploring options,gathering information,and planning various use-cases to strategize implementation,while a quarter are in the early pilot testing stage.With a majority of organizations still figur

15、ing things out,business leaders have an opportunity to beat their competition and gain advantages.But to do so,theyll need to act quickly in implementing their own AI strategies.Base:Total(n=900),US(n=500),Germany(n=200),India(n=200).Source:A commissioned study conducted by Ipsos on behalf of Micros

16、oft,October 20237Those companies that have started integrating AI are focused on supporting customer-facing applications and increasing efficiency through automation.These use cases tend to bring higher ROI,as they focus on getting more value out of their workers by reducing time spent on lower-valu

17、e tasks.This makes sense,considering respondents,on average,expect a 34%ROI from their AI platforms.Businesses are focused on automation and customersWhat AI workloads has your organization deployed?62%Document-process automation(e.g.,claims management and automation)49%Knowledge mining(e.g.,content

18、 search,product discovery optimization)70%Conversational AI(e.g.,customer service assistant,language understanding,voice control)52%Speech transcription and analytics(e.g.,call transcription and analysis,multimedia content captioning,conversation transcription)59%Machine translation(e.g.,real-time s

19、peech translation,document translation,web localization)Base:(n=641)Source:A commissioned study conducted by Forrester Consulting on behalf of Microsoft and NVIDIA,May 2023On average,46%of customer-facing applications and 44%of business/core applications leverage AI functionality.8Stages of AI readi

20、ness“Leading-edge organizations”blaze the path forwardWhile many organizations are early in their AI journeys,15%of businesses are advanced in their AI infrastructure and are considered“leading-edge organizations”.These leading-edge organizations tend to be early adopters of technology and can provi

21、de valuable learnings on effective AI implementation strategies.Our recommendations are based on an analysis of leading-edge organizations plus other key insights to provide AI best practices and recommendations any company can leverage.15%Leading-edge38%AI beginnerFully implemented and optimizingPi

22、loting,testing,and deployingExploring and planning47%DevelopingBase:Total(n=900)Source:A commissioned study conducted by Ipsos on behalf of Microsoft,October 202371%of leaders in leading-edge companies say that their organization is eager to try new technology and having IT thats more advanced than

23、many of their competitors compared to 47%of non-leading-edge companies.59%99%9The AI landscape continues to evolve and AI implementation poses many different challenges and obstacles to overcome.Business leaders are faced with the daunting task of figuring out the best path forward.My technology env

24、ironment is very complex and dynamically changing.We have complex needs and multiple departments use different applications.all with varying needs.In just a few years,I believe the AI will be much more advanced than what we have today.AI is challenging for everyoneof organizations have challenges in

25、 scaling and operationalizing AI of business leaders believe the AI market is growing and evolving Base:Total(n=900)Source:A commissioned study conducted by Ipsos on behalf of Microsoft,October 202333%39%10The greatest challenge?Tackling the talent gap Organizations have an immediate need for AI exp

26、erience and talent.Addressing this gap by bolstering employees skills and training today is the key to bridging the gap and moving forward quickly.Along with AI talent sourcing,its not surprising that many of the other challenges businesses face are centered around technological and strategic challe

27、nges.Security considerations,having adequate capabilities for designing,implementing,and managing infrastructure,and having the appropriate AI tools are key technology challenges.And along with employee talent,unclear ROI of AI implementation,the right resources to support AI development and managem

28、ent and collaborating across business functions are top organizational challenges.Security,capabilities,and ROI considerationsLeaders who rank having the skills required to develop or customize AI models as one of their top 3 technology challenges(out of 13 items).Leaders who rank having enough tale

29、nt as one of their top 3 organizational challenges (out of 13 items).Base:Total(n=900)Source:A commissioned study conducted by Ipsos on behalf of Microsoft,October 202356%11Top technology chaTop technology chal llenges organizations facelenges organizations faceInfrastructure challenges remain top o

30、f mindThe right infrastructure can make or break your AI projects.Overwhelmingly,the AI challenges fall within infrastructure(hardware,software,and tools)and remain the most common roadblock in implementing and leveraging powerful AI tools.Prioritizing the right AI infrastructure is key to successfu

31、l AI implementation,scaling,and innovation.My organization doesnt have the proper infrastructure to support my organizations desired AI workloads.Base:Total(n=641),Total(n=900)Source:Commissioned studies conducted by Forrester Consulting and Ipsos on behalf of Microsoft,May 2023 and October 2023(des

32、cending order,showing top 7 of 13 items)Skills required to develop or customize AI models Security considerations Having adequate capabilities for setting up,scaling,and managing AI infrastructure Accessing appropriate AI methods/tools Outdated/legacy systems Ability to scale infrastructure on deman

33、d Orchestrating workloads across cloud and on-premisesRelated to infrastructure12Leaders are looking to partners for helpFor companies not sure how to start leveraging AI,partnering with a solution provider with deep AI expertise and proven AI solutions can help companies accelerate AI production an

34、d address AI infrastructure challenges.Business leaders are looking to partners to help with infrastructure design and implementation,training and support,security and compliance,and strategic planning and consultation.Where it gets interesting is that as companies move further along their AI journe

35、y,they start to prioritize things like performance,optimization,and cloud provider integration.Engaging the right partner can help businesses of any size and at any stage of AI implementation accelerate their AI journey.This is both a huge opportunity for partners,and a burden.They must make sure th

36、eir staff is ready to go and able to help with consulting,strategy,and training.47%44%44%44%52%50%47%44%Leading-edgeLeading-edgeNon-leading-edgePerformance monitoring and optimizationTraining and supportSecurity and complianceSecurity and complianceInfrastructure design and implementationInfrastruct

37、ure design and implementationCloud provider integrationStrategic planning and consultingBase:Total(n=900)Source:A commissioned study conducted by Ipsos on behalf of Microsoft,October 2023Where partners are expected to helpWhere partners are expected to help (top 4)(top 4)13AI infrastructure remains

38、elusiveIf youre not sure how to approach your AI infrastructure,youre not alone.Robust and scalable infrastructure specifically built for AI is critical to support the complexities of new AI-driven workloads and processes,but AI infrastructure is a key challenge for most leaders,who face many obstac

39、les in implementing and operationalizing AI,such as:Outdated and legacy systems that are not designed to handle the complexity and volume of AI workloads.Data security and privacy concerns,especially sensitive and personal data,that require robust protection and compliance measures.Workload orchestr

40、ation challenges,such as managing multiple platforms,tools,and frameworks,and optimizing resource utilization and performance.Skills gap,as many organizations lack the talent and expertise to develop,customize,and deploy AI models and applications.The accelerated rate of technological advancements l

41、ike GenAI that have large implications on the type and complexity of the infrastructure needed.57%54%39%34%14Microsofts definition of AI infrastructure:“A combination of hardware,software,and tools that enable the development,deployment,and management of AI models and applications.”Integrating AI ca

42、pabilities into existing IT infrastructure through the utilization of cloud resources,services,and APIsThe different ways organizations define“AI infrastructure”The different ways organizations define“AI infrastructure”A combination of hardware,software,and tools that enable the development,deployme

43、nt,and management of AI models and applicationsA comprehensive set of AI-specific algorithms,frameworks,and libraries that form the foundation of the companys AI capabilitiesDedicated hardware and network infrastructure specifically designed to support AI initiatives(e.g.,high-performance servers or

44、 GPUs,reliable network infrastructure,etc.)Defining AI infrastructure Infrastructure challenges are amplified due to diverse interpretations of AI infrastructure among organizations.These interpretations range from integrating AI capabilities into the existing IT infrastructure to establishing a ded

45、icated hardware and network infrastructure and developing a comprehensive tech stack that includes algorithms,frameworks,and libraries.This can make something as simple as communicating needs with vendors a real challenge when the same language is not being used.Not having a clear definition just ad

46、ds to the challenges of getting started with AI.At the most simplistic,AI infrastructure includes the hardware,software,networking,and tools and services used to develop,implement,and optimize AI.As AI continues to evolve,itll be more important than ever to settle on a standard definition that can b

47、e used across all industries.Base:Total(n=900)Source:A commissioned study conducted by Ipsos on behalf of Microsoft,October 202343%42%16%15Businesses are already understanding the urgency and importance of having a solid foundation for their AI initiatives.41%of leaders agree that infrastructure is

48、the area they need most help with and 39%need help with strategic planning and consulting,citing specialized components like infrastructure or security as well as broader design and implementation.Additionally,43%are predominantly proactive in developing their AI infrastructure strategy,compared to

49、16%who are mostly reactive.Theres a clear opportunity for partners to provide the consultation and expertise companies need to optimize their infrastructure for AI.Strategic planning and consulting is desired by many organizations across all industries.Business leaders that were earlier in their imp

50、lementation were more likely to need help with 42%of AI beginner organizations stating they needed help.As organizations begin their journey,they can leverage the consultation of partners.Making AI infrastructure a priority41%41%40%39%Training and support Infrastructure design and implementationSecu

51、rity and compliance Strategic planning and consulting Base:Total(n=900)Source:A commissioned study conducted by Ipsos on behalf of Microsoft,October 2023ProactiveReactiveA mix of both proactive and reactive Areas organizations need the most help withAreas organizations need the most help withMost le

52、aders aim to be proactiveMost leaders aim to be proactiveFinanceHealthcareRetailManufacturingIndependent Software Vendors 51%43%38%39%43%16Industries bring their own nuancesManufacturing tends to be the most proactive(51%)in planning for AI infrastructure,significantly more so than those in healthca

53、re and retail.In such a process-driven industry,even minor gains in efficiency can bring critical advantages over the competition.AI technologies,even in its current form,brings giant leaps forward in operational efficiency.The entire industry stands to gain significant benefits through process opti

54、mizations,advanced automation,and predictive maintenance.Business leaders across other industries can follow manufacturings example and move quickly to stand up the right infrastructure for their AI needs.Like any other business strategy decision,these differences highlight the cross-industry nuance

55、s that need to be considered when taking on any new technology.Manufacturing organizations aim to be the most proactiveBase:Total(n=900)Source:A commissioned study conducted by Ipsos on behalf of Microsoft,October 202344%42%37%37%Start with the trifecta:performance,security,and costThere is no doubt

56、 theres a lot to consider when finding the right AI infrastructure a business needs,and the speed of changes being brought to the market add further complexities.As businesses start analyzing vendors and setups,they can look to these top considerations as a starting-off point:performance,security,an

57、d cost.Performance and scalabilitySecurity and privacyCost effectivenessIntegration with existing systemsTop priorities for AI infrastructureBase:Total(n=900)Source:A commissioned study conducted by Ipsos on behalf of Microsoft,October 20231749%44%52%Security and privacy also take precedence,with 42

58、%of business leaders citing it as a top priority.This is especially true for finance and healthcare where they must secure confidential data against unauthorized access,cyber threats,and data breaches while complying with stringent regulations.While security fell slightly in importance for retail,ma

59、nufacturing,and ISV,these industries still rated it as a key priority to address overall.These factors are essential for ensuring the reliability,efficiency,and effectiveness of AI infrastructure solutions,and addressing the key challenges that leaders face.Security and privacyPerformance and scalab

60、ility“Security and privacy”tops the list for finance and healthcareFinanceHealthcareIndependent software vendors With 44%of leaders prioritizing performance and scalability,particularly in industries managing high-volume and complex AI workloads like retail,manufacturing,and independent software ven

61、dors,the imperative for AI infrastructure lies in providing swift and reliable computing resources to optimize resource utilization,reduce latency,and scale up and out as needed.Focusing on performance and scalability means looking beyond the cost to consider all the benefits that come with AI and m

62、aximizing the full impact of AI infrastructure implementations.Base:Total(n=900)Source:A commissioned study conducted by Ipsos on behalf of Microsoft,October 20231837%32%20%31%29%23%19%23%Cost effectivenessNot surprisingly,cost effectiveness is a priority,with 37%of business leaders across industrie

63、s citing getting the value they need from their AI infrastructure and meeting ROI goals as important.Cost is even more relevant for retail industries.Continuous performance monitoring and optimization Support and maintenanceRobust data management Flexibility and customizationUser-friendly tools and

64、interfacesBeyond these top three priorities,businesses expect the following from their AI infrastructure:Cost effectiveness is more important to leaders in the retail industry(42%)than other industries and tops their list of AI infrastructure priorities.Base:Total(n=900)Source:A commissioned study c

65、onducted by Ipsos on behalf of Microsoft,October 2023AI infrastructure priority Cost effectiveness(rank 3 of 10)Organizational challengesROI is unclear(rank 2 of 13)Barriers and blockers for AI adoptionCost and ROI (rank 4 of 20)Other priorities19Leading-edge organizations face different challenges

66、compared to businesses that are earlier in their AI infrastructure implementations.As an organization moves further along,flexibility,data management,maintenance,and support compete with earlier priorities like performance,security,cost effectiveness,and integration.As new technologies and processes

67、 become their standard mode of operation,priorities change,and its important for leaders to proactively plan for these changes.Understanding that more things become important as your organization progresses will enable you to pivot priorities quickly to meet changing and expanding needs.One size doe

68、s not fit all Priorities are fluid,shifting to match an organizations constantly evolving context.Factors like industry,market,AI maturity level,and platforms create a constantly evolving environment to navigate.Leaders need to be able to plan for these shifts in priorities by understanding the orga

69、nizations changing context and impact on implementations.AI beginnerLeading-edgeDevelopingLeading-edgeAI beginnerLeading-edge47%37%17%34%DevelopingLeading-edge51%38%AI beginnerLeading-edge47%37%Priorities that intensify by readiness levelPriorities that intensify by readiness levelSecurity and priva

70、cyRobust data managementPerformance and scalabilityBase:Total(n=900)Source:A commissioned study conducted by Ipsos on behalf of Microsoft,October 2023Level of AI readiness20The AI infrastructure capabilities needed vary based on business model and workloads.One company may need fully customizable so

71、ftware,services,and computing while off-the-shelf AI models,services and platforms may be fine for another.As AI continues to evolve,the needs of companies and even the solutions are rapidly changing.Because of this,providers are ramping up their offerings to reach a wider range of needs and providi

72、ng multiple points at which a customer can come into their system.Weve identified three different categories of customers for AI infrastructure.Workload type AI leaders have a defined AI strategy and want to lead their market by building their own innovative,homegrown AI models and applications.They

73、 require highly performant supercomputing infrastructure that can flexibly meet complex storage,network,computing,and security needs.Their AI workloads are incredibly complex,involve massive models,and require control at every layer of their AI infrastructure.Business drivers:Developing an end-to-en

74、d AI service,solution or platform,from the ground up.Require unlimited scalability and the ability to deliver customized user experiences.AI leadersAI leadersAI power users also have a defined AI strategy and are heavily customizing pre-built AI models,infusing company-specific content and data,and

75、retraining.They need control over each layer of their AI infrastructure but typically dont require massive compute power when working with pre-trained models.Business drivers:Looking to maximize efficiency and minimize time to market.Save time by using pre-built models and optimizing for their needs

76、.AI power usersAI power usersAI ready companies want infrastructure that is ready to go so they can focus on defining their AI strategy.They dont want to worry about the ins and outs of infrastructure,they are looking for a scalable,out-of-the-box solution that can support discrete processes now and

77、 support AI growth.Business drivers:Taking their first steps with AI.Need off-the-shelf solutions.AI readyAI ready21The infrastructure requirements will be different depending on the planned use-case.For example,an early pilot project and actual full-scale implementation have completely different in

78、frastructure.requirements.For more advanced models,we need GPUs that will be more useful.But for now,we have some,light-weight models that can be run in CPUs.On-premisesHybridCloudThere is no one-size-fits-all to determining whether a company should be on-premises,hybrid,or on the cloud every type o

79、f solution has their positives and negatives.With a myriad of factors at play,ultimately the decision about what is best lies with the company and their unique situation.For example,on-premises AI infrastructure may offer more control but require more upfront investments and can be expensive to main

80、tain,difficult to scale,and hard to keep up to date with the latest technologies.AI infrastructure in the cloud offers fast deployment,scalability and flexibility,and typically the best technology available,but some have concerns with security,privacy,and meeting compliance requirements.Hybrid setup

81、s offer the benefits(and drawbacks)of both but with higher degrees of complexity.Startups may benefit even more from a cloud set-up due to their small employee size and their naturally increased focus on getting their product to market as fast as possible.Nonetheless,key themes that came across for

82、each of these were security and cost effectiveness.Platform considerations Data security Cost effectiveness Existing IT infrastructure integration Security and compliance Cost effectiveness Scalability and elasticity Data privacy and security Flexibility and scalability Cost optimizationTop three pr

83、iorities by solution setupTop three priorities by solution setupBase:(n=641)Source:A commissioned study conducted by Forrester Consulting on behalf of Microsoft and NVIDIA,May 20232249%31%17%3%Half of business leaders said they have a hybrid setup with plans to migrate fully to the cloud for better

84、IT governance and security,increased productivity and scalability,more successful deployments,greater innovation,and ROI.For those that are“AI ready,”a cloud provider may provide a more comprehensive out of the box solution to get started.Further than deciding whether to have an on-premises,hybrid,o

85、r cloud setup,the vendor choice is fraught with a range of choices.Key features like having high quality AI algorithms,ability to manage networking capabilities,integration with open-source tools,API accessibility,scalability,clear documentation,and multi-cloud/hybrid enablement came through as the

86、highest requirements.How would you describe your organizations current AI workload implementation?Mix of on-premises and public cloud with plans to migrateMostly to fully public cloud with no plans to migrateMix of on-premises and public cloud with no plans to migrateOn-premisesBetter IT governanceI

87、ncreased productivityHigher percentage of AI concepts successfully deployed in productionIncreased scalabilityIncreased data security for ML models and data sets Base:(n=641)Source:A commissioned study conducted by Forrester Consulting on behalf of Microsoft and NVIDIA,May 2023What are the main bene

88、fits of hosting AI workloads in the cloud?23FinanceHealthcareRetailDifferent industries have different priority nuances.More regulated industries like finance and healthcare put a higher focus on security and privacy,while manufacturing and ISVs require strong performance and scalability.Additional

89、factors like solution set-up and level of AI maturity will also make a difference in both their organizational and technical priorities.Industry context AI lets us shorten the time required for so many things.And it helps our performance and overall activity.Security is a major concern,with so much

90、data available and protections needed.(Infrastructure let us)use machine algorithms to detect threats in real time and enhance cybersecurity.1.Security and privacy2.Performance and scalability3.Integration with existing systems1.Performance and scalability2.Integration with existing systems3.Securit

91、y and privacy1.Security and privacy2.Performance and scalability3.Integration with existing systems1.Performance and scalability2.Security and privacy3.Cost effectiveness1.Performance and scalability2.Cost effectiveness3.Integration with existing systemsTop 3 AI infrastructure priorities by industry

92、Top 3 AI infrastructure priorities by industryBase:Total(n=900)Source:A commissioned study conducted by Ipsos on behalf of Microsoft,October 2023ManufacturingIndependent Software Vendor24Harnessing the power of AI now To help businesses move forward in their AI journey,we recommend four actions to h

93、elp navigate the challenges and speed AI production and integration.Infrastructure is at the core of AI innovation.It can determine how fast,how good,how easy,how groundbreaking,and how engaging an AI application,solution,or platform will be.Companies should carefully examine their AI goals and stra

94、tegy and determine what infrastructure capabilities and platform(on-premises,cloud,hybrid)best fit their needs today and in the future.It is rare that existing infrastructure can power the demands and complexity of AI.Most businesses will need to make changes,either overhauling their existing infras

95、tructure,choosing a solution provider offering a full-stack AI platform,or something in between.A companys AI infrastructure strategy can shape the future of their business,either accelerating their AI journey or blocking their innovation.Prioritize your AI infrastructure Prioritize your AI infrastr

96、ucture To overcome the AI skills gap,business leaders need to invest in training and upskilling their current employees and/or consider bringing in outside talent.Partnering with an experienced AI solution provider can also help fill the void and deliver employee training,strategy planning,and AI in

97、frastructure,production,and implementation support.Overcome the skills gapOvercome the skills gap25Across all industries,business leaders expressed a need for help with strategic planning and consulting as well as training and support from AI solution providers.Leading-edge organizations partner wit

98、h AI experts to help plan,build,and integrate AI into their business.Companies of any size and at any stage can benefit from a strategic AI solution provider.Forming a partnership with a proven AI solution provider can be key to accelerating AI production and staying competitive.Security,privacy,and

99、 compliance should be at the forefront of any AI and infrastructure plans.Secure AI is the act of securely designing,developing,and deploying AI and GenAI capabilities and systems.Follow these best practices:Keep user data private and secure.Ensure transparency in procedures and emphasize the signif

100、icance of clearly communicating sources and criteria for decision-making.Ensure security is built-in from inception to deployment of the AI systems lifecycle.Keep risk at the forefront when designing interfaces and processes.Make it secureMake it secureFind a partnerFind a partner26 2024 Microsoft C

101、orporation.All rights reserved.This document is provided as-is.Information and views expressed in this document,including URL and other internet Web site references,may change without notice.You bear the risk of using it.THis document does not provide you with any legal rights to any intellectual pr

102、operty in any Microsoft product.Explore how Microsoft Azure is redefining cloud infrastructure to prepare every business for AI by providing the world-class technology for AI workloads and doing so sustainably and responsibly.Get strategic guidance and insights on AI innovation,tailored for business

103、 leaders.Learn how businesses are balancing performance,efficiency,and cost with Azure AI infrastructure.Take the next steps on your AI transformation journey27Research methodologyIn May 2023,we commissioned Forrester Consulting to evaluate the current state of AI among IT directors and decision mak

104、ers in North America,Europe,and Asia Pacific.We further explored this topic through a second study with Ipsos in September 2023 among technical and business leaders,developers,and data professionals who are early majority adopters of technology across 3 markets(US,Germany,and India)and 5 different i

105、ndustries(finance,healthcare,retail,manufacturing,and independent software companies).Fielding:May June 2023Participants:n=641 Director and above in IT with responsibilities in AI workloads,cloud infrastructure.Company Size:1000+FTE in North America,500+in all other countriesCountries:North America(

106、US,Canada),EMEA(UK,Germany,France),APAC(Australia,New Zealand)Industries:All industries,including automotive,manufacturing,oil and gas,financial services,public sector,universities,bio life sciences.Forrester Consulting ResearchFielding:September-October 2023Participants:n=900 ITDMs who are in the e

107、arly majority of technology adopters at their organizations.Company Size:ISVs=50+employees All other industries=500+employeesCountries:US(n=500),Germany(n=200),India(n=200)Industries:Finance(US n=100,Germany/India n=40);Healthcare(US n=100,Germany/India n=40);Retail(US n=100,Germany/India n=40);Manu

108、facturing(US n=100,Germany/India n=40);ISV(US n=100,Germany/India n=40)ISVs are independent software vendors or software houses that develop software for broad commercial distribution,including SaaS.Ipsos R Partner Top Honors since 2017.Visit for a full list of awards.SINCE 2017PARTNER OF THE YEAR*A

109、ccelerate Your Azure Journey with 3Cloud 3Cloud is the premier pure-play Azure partner in the ecosystem with unparalleled expertise in all things Azure.We specialize in delivering top-tier Azure infrastructure,cutting-edge AI,robust data&analytics and ground-breaking app development.Leveraging our extensive experience,advanced tools and customized accelerators,we ensure the quickest time to value for your Azure-based projects.