《Writer ：2024企業級生成式AI解決方案評估：首席信息官（CIO）分步指南（英文版）（24頁）.pdf》由會員分享，可在線閱讀，更多相關《Writer ：2024企業級生成式AI解決方案評估：首席信息官（CIO）分步指南（英文版）（24頁）.pdf（24頁珍藏版）》請在三個皮匠報告上搜索。

1、Evaluating generative AI solutions for enterpriseA step-by-step guide for CIOs GUIDESTable of contentsIntroductionUnderstanding the generative AI landscapeEvaluating AI and LLM vendors:a quick framework for CIOsBest practices for selecting the right generative AI solutionDISCOs journey with generati

2、ve AI:Insights for CIOsThe time is now to embrace enterprise-ready generative AI128111721INTROGenerative AI is fueling a new wave of innovation for enterprise companies.Our recent global survey of technical leaders and decision-makers found that 96%of companies expect generative AI to be a key enabl

3、er for their business,with 82%anticipating rapid growth in adoption.If youre an enterprise technical leader,now is the time for you to prioritize adopting and integrating generative AI into your companys overall business strategy.And now is also the time for you to keep an eye on how this technology

4、 is implemented to ensure quality and minimize technical debt.Traditionally,CIOs have been responsible for keeping the lights on,reducing risk,and managing the status quo.But with the advent of generative AI,CIOs understand they have to be more proactive,do more with less,and drive business outcomes

5、 at scale.As CIOs adopt this shift,they take on the role of driving transformative progress within their organizations.Thats why weve created a step-by-step guide specifically for CIOs to evaluate generative AI for enterprise use.At its core,this guide is designed to empower you as an enterprise tec

6、hnical leader with a roadmap for evaluating generative AI solutions with confidence.Through a comprehensive,step-by-step process,youll gain the insights needed to make strategic decisions and guide your organization to success.From demystifying the technology and its capabilities to identifying the

7、right vendors and implementing solutions,this guide will equip you with the knowledge and tools you need to navigate the complex world of generative AI.So lets dive in and discover how generative AI can transform your business and how you can successfully evaluate and integrate it into your enterpri

8、se strategy.1Generative AI is an exciting,fast-evolving technology thats already changing the way we do business.As youre no doubt aware,an explosion of generative AI vendors has flooded the market over the past few years.Understanding the generative AI landscapeCompute hardwareChips optimized for M

9、L trainingEnd user applications without proprietary modelsCopilotAppsClosedfoundation modelsPre-trained models exposed via APIGPT-4CHATGPTFull-stack platformsEnd-user facing applications with proprietary modelsOpen-sourcefoundation modelsModels released as training weightsStable DiffusionCloud platf

10、ormsCompute hardware exposed to developers2There are three main types of generative AI solutions to consider for enterprise use:?Custom stacks are built in-house and can be personalized to the exact needs of your organization.?AI assistants and point solutions are great for incremental productivity

11、and personal work?Full-stack platforms support more complex,organization-wide applications.generative ai landscapeBenefits and challenges of adopting generative AI solutionsAdopting generative AI solutions offers a host of advantages.It boosts business growth by ramping up production,delivering more

12、 insightful analyses,and enhancing the quality of outputs.These improvements can help streamline operations and elevate customer experiences,making everything more efficient and effective.Generative AI speeds up how quickly products reach the market.Plus,it helps make sure that work sticks to brand

13、and compliance rules,cutting down on mistakes or rule-breaking.3watch the videoWalk through the generative AI landscape with Kevin Wei,Solutions Architect at Writer Going beyond chat bots:full-stack generative AI as a strategic business initiativeIf youve experimented with generative AI tools like C

14、hatGPT,you already know that it speeds up time-consuming,manual work,like generating personalized content and summarizing reports.But chat interfaces built on top of LLMs are only part of the story.With a full-stack solution,the capabilities go beyond content generation and personal productivity.Ret

15、rieval-augmented generation(RAG)delivers company-specific knowledge for customer support,sales,and employee training.AI guardrails drive consistent,compliant outputs for public-facing documents.When integrated with existing workflows,generative AI improves data analysis and operational decision-maki

16、ng.Full-stack generative AI opens the door for enterprises to streamline operations,drive efficiency,and provide outstanding customer experiences.Our 2024 survey of CIOs and technical decision-makers showed that IT,customer support,and security are the top business areas for generative AI adoption.g

17、enerative ai landscape4But integrating AI into your business isnt easy.It requires a commitment to change at every level of your organization.You need to educate and train your employees on how to use AI and the new processes and technology that it brings.You also need to address any concerns or res

18、istance to AI that might come up.And,if youre building in-house,you need to invest engineering time and resources to build and maintain your AI stack,which can be a significant commitment.generative ai landscape5What do you think are the top business areas for generative AI?IT operationalCustomer su

19、pport SecurityMarketingTraining Meeting support HRFinanceOther65%64%54%50%46%40%36%25%3%10203040506070t ak e aw ayIT,customer support,and security teams hold the most potential for generative AIIn the next two years,97%expect that new teams will be using generative AI.This data shows the need for a

20、shift in focus from AI assistants,which have limited overall business impact,to full-stack solutions that deliver significant,measurable business growth.generative ai landscape6Over the next two years,which teams do you expect to start using generative AI at your company?Training31%Customer support

21、29%HR29%Marketing27%Sales25%Product management24%IT Security23%Finance23%PR21%Executive19%IT Operations16%Manufacturing14%Other4%We dont expectnew teams to start using generative AI over the nexttwo years3%5101520253035t ak e aw ay97%of companies state new teamswill be using generative AI,led by tra

22、ining,customer support,and HR.Whats full-stack generative AI?read moreIn general terms,heres what you need for an enterprise-grade,full-stack AI platform?A large language model(LLM?A way to connect LLMs to your business data(RAG?A way to apply AI guardrail?A way to build AI app?Ways for your people

23、to use the app?The ability to ensure security,privacy,and governance for all of itWhen these pieces come together,you can use AI to accelerate business growth,increase productivity across every team in your organization,and more effectively govern the data and content your company puts out into the

24、world.A custom stack will have all these parts,but youll have to stitch them together.You get some added flexibility,but at the cost of a higher integration cost and longer time to market.Well cover the technical requirements for a full-stack generative AI solution and balancing build vs.buy decisio

25、ns later in this guide.generative ai landscape7As you evaluate generative AI vendors for your enterprise solutions,here are the most important factors to consider.By doing so,you can be sure to make the most informed decision and select the vendor that best meets your organizations needs.Evaluating

26、AI and LLM vendors:a quick framework for CIOs8watch the videoGet practical advice on evaluating solutions from KPMGs AI leaderAssess a vendors foundational technology,deployment options and infrastructure support.Understanding a vendors technical architecture is critical to ensuring the solution is

27、scalable and that you can maintain control and security of your data.Evaluate whether the vendor relies on open source,uses a wrapper approach or has developed its own proprietary technology.Also look at deployment options like single-tenant or private cloud and the quality of their infrastructure s

28、upport.Technical feasibility1Consider the cost implications of implementing generative AI solutions.Evaluate the pricing models offered by vendors,including licensing fees,maintenance costs,and any additional expenses associated with customization or integration.Look for vendors that offer customiza

29、tion options and seamless integration with existing systems.This is essential to tailoring generative AI solutions to your specific organizational needs and ensuring smooth collaboration and productivity within the existing infrastructure.Additionally,consider the vendors compatibility with third-pa

30、rty services and applications commonly used in your industry to enhance productivity and collaboration.Evaluate how vendors handle data separation,anonymization,and compliance with privacy regulations.Prioritize vendors with strong security measures and compliance with legal requirements.Assess thei

31、r data lifecycle management practices and their approach to data ownership.Look for features like redaction capabilities to maintain compliance and protect sensitive data.CostIntegration customizationGRC(Governance,risks,and compliance)234Evaluating AIEvaluating AI10Weve put together a checklist to

32、help you evaluate vendors and select the right solution.This checklist is based on questions that CIOs at global brands have asked us in their own exploration processes.Essential questionsfor evaluatingLLM vendorsDownload nowTo pick the perfect generative AI solution for your business,youll need to

33、kick things off with some key decisions?Do we build our own generative AI solution from scratch?If not,do we go for a full-stack platform or a point solution?Here are some steps to guide you through these choices and ensure youre following best practices:Best practices for selecting the right genera

34、tive AI solutionBalance build-vs-buy decisionsShould you buy an off-the-shelf enterprise solution,or should you roll up your sleeves and build something custom?This decision is tricky enough when youre dealing with something like project management software or an enterprise CRM.But throw generative

35、AI into the mix,and things get even trickier and a bit more overwhelming.11Best PracticesPalmyra LLMsState-of-the-art top-benchmarked Writer-built LLMs that are compliant,efficient,and transparent.Knowledge GraphConnects your AI apps to structured and unstructured data with graph-based RAG.AI guardr

36、ailsEnforce regulatory,accuracy,and brand compliance across all apps.App Studio and integrationsLow-code(for developers)and no-code(for business users)framework for quickly building scalable,accurate AI apps.Results*What were the results?You can include specific metrics or quotesHelp center articleA

37、ll TEMPLATESGenerate contentCUSTOMResults*What were the results?You can include specific metrics or quotesProposalsAll TEMPLATESGenerate contentCUSTOMResults*What were the results?You can include specific metrics or quotesNewsletterAll TEMPLATESGenerate contentCUSTOMAI program managementDrive change

38、 workflow by workflow to realize business value.Buying a solutionIf youre like most companies,buying a generative AI solution is probably your best bet.Its faster and simpler than building one from scratch,and it doesnt lean heavily on your teams tech skills.Youll still need someone like an AI progr

39、am director to handle setup and keep things running smoothly?Flexibility:If your company has specific requirements,buy a product that can be customized or integrated with your existing systems?Vendor support:Choose a vendor who knows your industry inside and out.The right partner can make everything

40、 easier and more effective.12Building a solutionWhat are the tradeoffs of building a custom stack?If your companys needs are unique,crafting a custom solution might be the way to go.This route lets you address specific challenges head-on but be ready for a long-term commitment to tweaking and improv

41、ing the system?Ongoing commitment:Youll need to keep refining the solution,fixing bugs,and adding new features?Resource-intensive:Be prepared to bring in new talent if your current team doesnt have the skills needed.If your company is contemplating building a generative AI solution versus buying a p

42、roduct,you have to think beyond the output.Building involves input as well,in terms of time and expertise.The tradeoff is a solution fully tailored to your needs,but it still comes with quantifiable costs:Stitching together various technology vendors can be slow,risky,and resource-intensive.Integrat

43、ion may not achieve the desired accuracy,and the evolving technology requires ongoing maintenance.Building generative AI requires investment in servers,databases,storage,and skilled engineers.These costs can quickly add up.Complexity and integration challengesDevelopment and maintenance costs12Best

44、Practices13Best Practices14Using large language models(LLMs)and retrieval augmented generation(RAG)approaches can be expensive,especially at scale.RAG solutions,like vector retrieval,require significant computational power.Cost of LLM and RAG3Building a generative AI solution takes time(many compani

45、es report six months or more),while commercial solutions enable faster deployment within weeks.Time to deployment4In-house generative AI solutions often fall short of expectations,with 61%of companies experiencing accuracy issues and only 17%rating their in-house solutions as excellent in overall pe

46、rformance.Quality of output5Integrating an LLM into an in-house solution raises data protection and compliance concerns.Security and compliance6In-house solutions may require additional investment in change management efforts,impacting ROI.Change management and adoption7Whether you decide to buy or

47、build your generative AI solution,youll need some internal support to manage the project.Consider whether your team is up to the task of handling ongoing maintenance and if you have the right expertise on board.When buying,its critical to choose a vendor that not only has a solid track record with b

48、usinesses like yours but also deeply understands the specific needs of your industry.Build vs.buy:Whats the best solution for your enterprise generative AI program?read moreCompare the options:full-stack platform vs point solutions onlyLets say youve decided that buying a solution is the way to go.Y

49、oull now need to decide on the kind of solution thatll work best for your organization.The two main types of generative AI solutions on the market today are full-stack platforms(like Writer)or stand-alone point solutions(think chat assistants like ChatGPT or use-case specific AI tools like Grammarly

50、).Best Practices15Lets weigh the pros and cons of each:Best Practices16Full-stack generative AI platform?Offers a centralized and scalable solution for implementing generative AI across multiple departments and use cases within an enterprise business?Provides a comprehensive set of tools and resourc

51、es for data management,model training,and app deployment?Enables collaboration and knowledge sharing among different teams and departments?Allows for customization and integration with existing systems and processes?May require a larger upfront investment,but can result in long-term cost savings and

52、 efficiency gains?Offers continuous support and updates from the platform provider.?Offer a more targeted and specific solution for a particular use case or department?Can be quicker and easier to implement compared to a platform approach?May lack the scalability and flexibility of a platform approa

53、ch?Can result in a fragmented and siloed approach to implementing generative AI within an enterprise business?May have a lower upfront cost,making them more accessible for smaller businesses or teams?May require multiple apps to be used together to cover all use cases,leading to higher costs and sec

54、urity risks in the long run.Point solutions and AI assistantsDISCO,a trailblazer in legal technology,embarked on integrating generative AI to enhance their e-discovery processes.E-discovery involves finding,collecting,and processing electronic data for legal cases.DISCO aimed to streamline this proc

55、ess,making it faster and more efficient through AI and retrieval augmented generation(RAG).DISCOs journey with generative AI:Insights for CIOs17watch the videoGet insights on generative AI solutions in the real-world with DISCOs Chief ArchitectDiscos Journey with Generative aiExperimentation and ini

56、tial challengesEngineering challenges DISCOs initial foray into generative AI began with exploring various large language models(LLMs).They recognized the potential of these models to transform their e-discovery services but faced significant challenges?Understanding AI capabilities:Grasping the uni

57、que capabilities of generative AI compared to traditional AI systems,particularly in handling natural language processing and generating relevant legal document summaries?Technological adaptation:Adapting existing systems to integrate new AI technologies while ensuring data security and operational

58、efficiency.Engineering a generative AI solution that met specific legal standards and operational needs was daunting.DISCO needed a solution that could?Handle sensitive data:Ensure the utmost security and privacy of sensitive legal data?Scale efficiently:Manage vast volumes of data without compromis

59、ing performance.1820Transformative vs.incremental valueLessons for CIOsJim Snyder,Chief Architect at DISCO,emphasizes the importance of seeking transformative value from AI investments.Key insights include?Look beyond incremental improvements:Focus on generative AI applications that offer significan

60、t leaps in productivity and decision-making,rather than just incremental improvements?Focus on strategic implementation:Ensure that AI tools are implemented strategically to address specific business challenges and enhance overall operational efficiency.When youre picking a generative AI solution,ma

61、ke sure it fits what your business really needs.Take a cue from DISCO they chose a platform that could securely manage tons of data and mesh well with their existing tech,which was crucial for their work in legal tech.19Discos Journey with Generative aiChoosing the right solutionAfter rigorous testi

62、ng and evaluation,DISCO chose a generative AI platform that excelled in security,performance,and cost-effectiveness.This decision was driven by?Data security:The chosen platform provided robust security features essential for handling sensitive legal information?Customization and integration:The pla

63、tforms ability to integrate seamlessly with existing systems and its adaptability to legal contexts made it the ideal choice.DISCOs experience with generative AI is a real playbook for CIOs wanting to bring this technology to their own organizations.By zeroing in on strategic use and truly transform

64、ative impacts,companies can weave AI into their operations in a way that meets their specific needs and drives serious business growth.Keep these tips in mind?Tailored solutions:Choose AI solutions that are specifically tailored to the industry and operational needs of the business?Comprehensive eva

65、luation:Thoroughly evaluate potential AI solutions focusing on long-term benefits and alignment with business goals?Aim for transformation:Dont settle for minor improvements choose AI that fundamentally enhances your business processes and decision-making capabilities,much like DISCO did by signific

66、antly reducing the effort required in e-discovery.20Discos Journey with Generative aiReducing the“human toil”of legal discovery with generative AI read moreChief ArchitectJim SnyderIf theres one piece of advice we can offer to CIOs,its this:dont wait to embrace AI in your organization.The truth is,y

67、our employees are likely already experimenting with AI technologies,even if theyve been told not to.Now is the time to empower them with a secure,full-stack AI platform like Writer.While building custom solutions may seem tempting,starting from scratch isnt necessary.There are various entry points,i

68、ncluding the developer-friendly Writer AI Studio,that can get you to solutions faster.Additionally,consider platforms that offer seamless integration with existing data sources and workflows.These platforms can be a significant accelerator for value creation.Dont miss out on the opportunities that A

69、I can bring to your business.Embrace it now by partnering with an enterprise-grade vendor like Writer and discover its potential for growth and innovation.The time is now to embrace enterprise-ready generative AI21Visit us at Writer is the full-stack generative AI platform for enterprises.We make it

70、 easy for organizations to deploy AI apps and workflows that deliver impactful ROI.Our integrated platform consists of our top-scoring Palmyra LLMs,our highly accurate graph-based RAG,AI guardrails to enforce brand and compliance rules,easy-to-use development tools,and a library of prebuilt apps,ext

71、ensions,and desktop experiences to get started quickly.With Writer,enterprises build highly-customized AI apps that accelerate growth,increase productivity,and ensure AI compliance.Our enterprise-grade platform can be deployed flexibly,keeps your data private,and adheres to global privacy laws and security standards.Leading enterprises choose Writer,such as Vanguard,Intuit,LOreal,Accenture,Dropbox,and Kenvue.