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1、N a v i g a t i n g t h e A d o p t i o n o f G e n e r a t i v e A IS U K A MA L B A N E R J E EC h i e f E x e c u t i v e O f f i c e rA r t i f i c i a l I n t e l l i g e n c e (A I)h a s t r a n s f o r me d h o w e n t e r p r i s e s e n g a g e wi t h t e c h n o l o g y a n d d r i v e o r

2、 g a n i z a t i o n a l e f f i c i e n c i e s u s i n g ma c h i n e l e a r n i n g a n d i n t e l l i g e n t a u t o ma t i o n.A n d wh i l e t r a d i t i o n a l A I h a s a u g me n t e d h u ma n A n d wh i l e t r a d i t i o n a l A I h a s a u g me n t e d h u ma n i n g e n u i t y f

3、 o r t h e l a s t f e w y e a r s,g e n e r a t i v e A I n o w g o e s f u r t h e r t o a i d c r e a t i v e e n d e a v o r s a n d f o s t e r i n n o v a t i v e s o l u t i o n s.G e n A I c a n t r a n s f o r m t h e wa y b u s i n e s s e s o p e r a t e,ma k e d e c i s i o n s,a n d i n

4、 n o v a t e.I t c a n,t h e r e f o r e,e n h a n c e p r o d u c t i v i t y a n d a c h i e v e c o s t e f f i c i e n c i e s a c r o s s e n t e r p r i s e f u n c t i o n s.G e n A I wi l l a l s o s i g n i f i c a n t l y t r a n s f o r m t h e wa y G e n A I wi l l a l s o s i g n i f i

5、c a n t l y t r a n s f o r m t h e wa y p r o d u c t s a r e e n g i n e e r e d a n d t h e f e a t u r e s i n t e g r a t e d i n t o t h e m s i n c e i t wi l l h a v e a p r o f o u n d i mp a c t a c r o s s t h e s o f t wa r e l i f e c y c l e r a n g i n g f r o m i d e a t i o n t o d

6、e v e l o p me n t (i n c l u d i n g t h e i n c r e a s e d a d o p t i o n o f l o w-c o d e a n d n o-c o d e s o l u t i o n s)t o t e s t i n g a n d ma i n t e n a n c e.E n t e r p r i s e s a c r o s s t h e i n d u s t r y v e r t i c a l s i n c l u d i n g B F S I,h e a l t h c a r e,t e

7、 l e c o m,r e t a i l,a u t o mo t i v e,h i-t e c h,e t a l a r e n o w e x p l o r i n g o p p o r t u n i t i e s t o e mb r a c e g e n e r a t i v e A I t o o l s a n d t e c h n o l o g i e s a c r o s s t h e v a l u e c h a i n t o i n t r o d u c e i n n o v a t i v e a p p r o a c h e s t

8、 o r e s e a r c h a n d d e v e l o p me n t,o p e r a t i o n s,d a t a a n a l y s i s,a n d c u s t o me r e x p e r i e n c e.Wi t h g e n A I s r a p i d g r o wt h a n d r i s i n g c u s t o me r Wi t h g e n A I s r a p i d g r o wt h a n d r i s i n g c u s t o me r a n d s t a k e h o l d

9、 e r i n t e r e s t,e n t e r p r i s e s f i n d t h e ms e l v e s c o mp e l l e d t o e mb r a c e i t s a d o p t i o n a t a n a c c e l e r a t e d p a c e.H o we v e r,t h e a d o p t i o n o f g e n A I a l s o p r e s e n t s n e w c o mp l e x i t i e s a n d c h a l l e n g e s.T o u n

10、l o c k t h e f u l l p o t e n t i a l o f g e n A I a s we l l a s t o ma x i mi z e t h e i n v e s t me n t s o f s u c h t r a n s f o r ma t i o n i n i t i a t i v e s,e n t e r p r i s e s n e e d t o c a r e f u l l y e v a l u a t e a n d s t r a t e g i z e f o r t h e s u c c e s s f u l

11、 a d o p t i o n o f g e n A I wh e t h e r i t i s f o r o p t i mi z i n g c u s t o me r e x p e r i e n c e s,a u t o ma t i n g p r o c e s s e s,o r r e v o l u t i o n i z i n g d a t a a n a l y s i s.P r e f a c eR e c e n t l y,X o r i a n t l a u n c h e d i t s A I p l a t f o r m O R I

12、A N t h a t o f f e r s v a r i o u s u s e c a s e s a n d mo d e l s t o e n a b l e c l i e n t s t o s wi f t l y e mb r a c e A I a n d g e n A I i n t h e i r p r o c e s s e s t o d r i v e b u s i n e s s a n d o p e r a t i o n a l e f f i c i e n c i e s a n d t o r e ma i n c o mp e t i t

13、 i v e.T h e p l a t f o r m b r i n g s t o g e t h e r t u r n k e y i n d u s t r y s o l u t i o n s,a l a r g e p a r t n e r n e t wo r k,a c c e l e r a t o r s,a n d e t h i c a l d e s i g n f r a me wo r k s f o r b u s i n e s s-r e a d y i n d u s t r y s o l u t i o n s.T h i s r e p o

14、r t p r e s e n t s k e y i n s i g h t s a n d o f f e r s a T h i s r e p o r t p r e s e n t s k e y i n s i g h t s a n d o f f e r s a c o mp r e h e n s i v e r o a d ma p f o r e n t e r p r i s e s f o r g e n A I a d o p t i o n t o d r i v e me a n i n g f u l t r a n s f o r ma t i o n a

15、c r o s s f u n c t i o n s.G i v e n i t s wi d e r a n g e o f u s e-c a s e s a n d v a r y i n g a p p l i c a t i o n s a c r o s s i n d u s t r i e s,a me t i c u l o u s a d o p t i o n s t r a t e g y wi l l n o t o n l y e n a b l e b u s i n e s s e s t o f u l l y l e v e r a g e t h e b

16、 e n e f i t s o f g e n A I b u t a l s o mi t i g a t e p o t e n t i a l r i s k s a n d p i t f a l l s.R i g h t a t t h e s t a r t,i d e n t i f y i n g a n d p r i o r i t i z i n g s t r a t e g i c u s e-c a s e s t o r e a l i z e d o wn s t r e a m v a l u e R i g h t a t t h e s t a r t

17、,i d e n t i f y i n g a n d p r i o r i t i z i n g s t r a t e g i c u s e-c a s e s t o r e a l i z e d o wn s t r e a m v a l u e p e r g e n A I r e l e v a n c e a n d t h e i r b u s i n e s s i mp a c t e n a b l e s e n t e r p r i s e s t o a s s e s s h i g h-p o t e n t i a l o p p o r t

18、 u n i t i e s a r o u n d g e n A I.S i n c e d a t a s e r v e s a s t h e f o u n d a t i o n f o r a n i n t e l l i g e n t e n t e r p r i s e,i t i s a l s o i mp e r a t i v e f o r b u s i n e s s e s t o e n s u r e d a t a r e a d i n e s s f r o m i d e n t i f i c a t i o n o f d a t a

19、s o u r c e s t o d a t a c u r a t i o n t o d a t a g o v e r n a n c e a s we l l a s e x t e n s i v e&e x p e n s i v e r e s o u r c e s.T h e n o v e l t y o f g e n A I n e c e s s i t a t e s e n t e r p r i s e t o T h e n o v e l t y o f g e n A I n e c e s s i t a t e s e n t e r p r i s

20、 e t o c o n s i d e r s i g n i f i c a n t t a l e n t o v e r h a u l.H o we v e r,a p a r t f r o m n e t n e w h i r i n g,o r g a n i z a t i o n s wi l l a l s o n e e d t o u p s k i l l e x i s t i n g t a l e n t a n d s t a k e h o l d e r s t o u n l o c k t h e p o t e n t i a l o f g e

21、 n A I f o r t h e o r g a n i z a t i o n a s we l l a s l a y o u t a d e t a i l e d v i e w i n t o t h e t e c h n o l o g y s t a c k t h a t i n c l u d e s l a n g u a g e mo d e l s,ma c h i n e l e a r n i n g f r a me wo r k s,c l o u d c o mp u t i n g s e r v i c e s,d a t a p r o c e s

22、 s i n g s o l u t i o n s,e t a l.L a s t l y,o r g a n i z a t i o n s mu s t a l s o t a k e c o g n i z a n c e L a s t l y,o r g a n i z a t i o n s mu s t a l s o t a k e c o g n i z a n c e o f e t h i c a l c o n s i d e r a t i o n s a r o u n d d a t a s e t s a n d l a n g u a g e mo d e

23、l s a s we l l a s p r o a c t i v e l y s t a y v i g i l a n t a b o u t p r e v a l e n t r i s k s a n d c o mp l i a n c e c h a l l e n g e s.T h i s i s c r i t i c a l f o r l o n g-t e r m s u c c e s s.G e n A I i s h e r e a n d d e ma n d s o u r a t t e n t i o n.G e n A I i s h e r e a

24、 n d d e ma n d s o u r a t t e n t i o n.H o we v e r,g i v e n i t s e x p a n s e b u s i n e s s e s mu s t,t h e r e f o r e,c a r e f u l l y n a v i g a t e c r u c i a l c o n s i d e r a t i o n s a n d p r e r e q u i s i t e s t o e n s u r e s u c c e s s f u l d e p l o y me n t s t h a

25、 t d r i v e o r g a n i z a t i o n a l p r o d u c t i v i t y,o p e r a t i o n a l e f f i c i e n c y,a n d b u s i n e s s g r o wt h.A n a p t s t r a t e g i c a n a l y s i s s h o u l d b e d o n e t o a s s e s s i f t h e r e i s a r e a l i s t i c b e n e f i t r e a l i z a t i o n a

26、t t h e e n d o f t h e g e n A I j o u r n e y.O t h e r wi s e,s u c h i n v e s t me n t s -wi t h l i mi t e d i mp l e me n t a t i o n a n d p r o h i b i t i v e c o s t s t h r o u g h t h e e n t i r e l i f e c y c l e -mi g h t n o t b e a g o o d b e t.A n o t h e r k e y d i me n s i o

27、n wh i c h n e e d s t o b e k e p t i n A n o t h e r k e y d i me n s i o n wh i c h n e e d s t o b e k e p t i n mi n d i s t h e s p e e d o f g e n A I e v o l u t i o n.Wo u l d a s s u mp t i o n s a n d c o n c l u s i o n s t o d a y h o l d g o o d i n s i x mo n t h s.T h e r e i s a f a

28、 i r c h a n c e t h e a n s we r i s n o.T h e r e f o r e,a t X o r i a n t,we c r e a t e a g e n A I s t r a t e g y T h e r e f o r e,a t X o r i a n t,we c r e a t e a g e n A I s t r a t e g y i n a c c o r d a n c e wi t h t h e o r g a n i z a t i o n s b u s i n e s s p r i o r i t i e s a

29、 n d i t s c u r r e n t I T p o s t u r e.F o r u s,A I f o r ms t h e c e n t e r o f X o r i a n t;a n d we a i m F o r u s,A I f o r ms t h e c e n t e r o f X o r i a n t;a n d we a i m t o p o we r p h e n o me n a l o u t c o me s a n d d r i v e v a l u e f o r o u r c l i e n t s wi t h O R

30、 I A N s t r a n s f o r ma t i v e c a p a b i l i t i e s,wh i l e e n s u r i n g r e s p o n s i b l e p r a c t i c e s.Copyright 2023,Everest Global,Inc.All rights This document has been licensed to XoriantNavigating the Adoption of Generative AIKey Factors for a Successful JourneyAkshat Vaid,

31、PartnerMayank Maria,Vice PresidentManjul Kapoor,Senior AnalystC|EGR-2023-X-V-XXXXIntroduction03What is generative AI?04Impact of gen AI on software engineering functions05Use cases of gen AI across industries06Gen AI adoption roadmap for enterprises08C|this document has been licensed to Xoriant3NAVI

32、GATING THE ADOPTION OF GENERATIVE AIArtificial Intelligence(AI)has revolutionized our lives,transforming how we interact with technology and accomplish tasks.Its goal is to replicate human intelligence it can perform complex activities such as speech recognition and language translation that were on

33、ce the exclusive domain of humans.However,traditional AI has struggled with human creativity,hindering its ability to generate original content in areas such as creative writing,music,and art.The introduction of generative AI(gen AI)marks a significant turning point,bridging the gap and enabling AI

34、to engage in creative endeavors as well.As enterprises embrace gen AI tools and technologies,its impact on engineering processes is increasingly significant.From idea generation and prototyping to algorithm optimization and design pattern proposals,gen AI is redefining traditional approaches and int

35、roducing innovative solutions.Along with its transformative benefits,the introduction of gen AI in engineering also presents new complexities and challenges for enterprises around use case and technology choices,integration with existing systems,data availability and quality,and more.Decision explai

36、nability is also a significant concern.These factors demand meticulous planning and careful navigation by enterprises adopting gen AI.In this report,we provide insights and guidance to enterprises on how to unlock gen AIs potential for transformative outcomes in operations and innovations.We explore

37、 gen AIs impact on key industries and engineering processes and offer key measures for enterprises to employ to overcome implementation hurdles and leverage this technology to its full potential.I|this document has been licensed to Xoriant4NAVIGATING THE ADOPTION OF GENERATIVE AIWhat is generative A

38、IGen AI,a subfield of artificial intelligence,can create new data,content,and designs by learning from existing patterns in large data sets.Through this process,AI models can generate new text,images,audio,and designs,tapping into the underlying structure and relationships within the data.This proce

39、ss unlocks creative potential and fosters innovative solutions.Gen AIs ability to generate new content is what differentiates it from discriminative AI,the more common form of AI.In contrast,discriminative AI focuses on classification and prediction tasks,aiming to learn decision functions that dist

40、inguish different input classes or make predictions based on observed features.The foundation of gen AIs abilities lies in Large Language Models(LLMs),which are capable of learning from vast data sets and can understand language and context,leading to human-like outputs.Exhibit 1 offers a snapshot o

41、f some of the top gen AI tools in the market.As enterprises embrace gen AI,the way products are engineered and the features integrated into them will transform significantly,as we discuss in the next two sections.EXHIBIT 1Top gen AI tools by use caseSource:Everest Group(2023)3D assets generationSynt

42、hetic data generationCode generationVideo generationAudio generationImage generationImage captioning Text generationRelative level of complexityLowHighPolyC|this document has been licensed to Xoriant5NAVIGATING THE ADOPTION OF GENERATIVE AIImpact of gen AI on software engineering functionsGen AI is

43、poised to have a profound impact on software engineering activities ranging from conceptualization and coding to testing and maintenance;exhibit 2 shows top gen AI use cases across the software lifecycle.EXHIBIT 2Top use cases of gen AI across the software lifecycleSource:Everest Group(2023)STAGE OF

44、 S/W LIFECYCLEIdeationDevelopmentTestingSupport&maintenanceRelative impact of gen AIDescriptionIn ideation,gen AI analyzes data for design and software ideas,enhancing creativity,speeding idea generation,and promoting innovation among engineers.In development,gen AI automates code generation,bug det

45、ection,refactoring,and UI design.In testing,gen AI automates test cases,verifying outputs,and predicting performance issues.In support&maintenance,it suggests solutions,provides 24/7 chatbot support,automates documentation,and simplifies code.Key use cases(in decreasing order of current traction)Gen

46、erating prototypes based on requirementsAutomated document generationUser story generationCreating design patternsFine-tuning algorithmsCode generationCode translationCreating code snippet suggestions for bug resolutionGenerating code refactoring suggestions Suggesting UI designsCode explanationRequ

47、irement-based test case creationGenerating reports for test casesSoftware output reports verificationRegression testing for code updates validationPerformance enhancements by reporting bottlenecksIssue diagnosis suggestionsChatbot supportAutomated document generationCreating tutorials for XR trainin

48、g supportCode summarizationLow HighIt(generative AI)is a super-powered assistant more profound than fire,electricity,or anything that we have done in the past.This is going to impact every product across every company.Sundar Pichai“|this document has been licensed to Xoriant6NAVIGATING THE ADOPTION

49、OF GENERATIVE AIAs exhibit 2 shows,gen AI can find diverse applications throughout the software engineering lifecycle and has the capability to revolutionize traditional approaches.However,even as gen AI finds wide-reaching applications in software engineering,human engineers expertise remains vital

50、 to assess its outputs alignment,feasibility,and correctness with project requirements,highlighting the necessity of human-machine collaboration for this technologys full potential.Gen AIs capabilities and applicability in software engineering has also led to increased adoption in Low-Code and No-Co

51、de(LC/NC)solutions.With gen AI,users can create software using natural language programming,going beyond drag-and-drop UI and pre-built components of code completion software such as GitHub Copilot.Several platforms are harnessing the power of gen AI to enhance the LC/NC development landscape and of

52、fer an improved user experience,including companies such as Bubble,K2 and Retool.Use cases of gen AI across industriesIn todays dynamic and rapidly evolving market,where enterprises seek efficiency and innovation,emerging technologies such as gen AI have become essential tools for achieving its goal

53、s.Gen AI holds the potential to address a spectrum of issues,including enhancing customer satisfaction,optimizing processes,and expanding revenue streams.Beyond its application in software engineering,generative AI has unlocked an expansive realm of industry-specific opportunities,harnessing its pot

54、ential to drive businesses toward excellence.From healthcare and finance to telecom and automotive,gen AI is transforming the way businesses operate,make decisions,and innovate.Exhibit 3(next page)highlights key gen AI use cases across various |this document has been licensed to Xoriant7NAVIGATING T

55、HE ADOPTION OF GENERATIVE AIEXHIBIT 3Key gen AI use cases across industries Source:Everest Group(2023)IndustryUse casesAdoption examplesBanking,Financial Services,and Insurance(BFSI)Asset allocation opportunities by analyzing market trends,helping minimize exposure to market risksPersonalized invest

56、ment recommendations based on individual needs and preferencesSynthetic data for predictive analysis in decision-making to mitigate financial risksSwedbank has trained Generative Adversarial Neural Networks(GANs)for fraud and money-laundering preventionMorgan Stanleys Wealth Management will use Open

57、AI tech for in-house servicesSouth State Bank has deployed Tate,a ChatGPT-powered AI chatbot,for customer info,risk analysis,and pricingHi-techInnovative semiconductor designs to improve performance and efficiencyOptimizing semiconductor manufacturing through data analysis for better yield,efficienc

58、y,and defect reduction suggestionsAnalyzing data and new semiconductor materials for experimental investigationCadences Virtuoso Studio has adopted gen AI for analog,RF,and custom silicon designsSiemens and Microsoft have collaborated on gen AI to boost innovation and efficiency in industrial compan

59、iesHealthcarePersonalized medicine suggestions by analyzing medical data and identifying patternsDrug discovery by analyzing data from clinical trials and diverse sources Generating diagnoses reports by analyzing data sets and patients conditionGoogle Cloud and Mayo Clinic have partnered on gen AI-d

60、riven healthcare data search with conversational featuresInsilico has used gen AI for each step of the preclinical drug discovery processZepp Health has integrated generative AI into wearables to enhance health managementCPG&retailWriting product descriptions for a retail platformDynamic pricing via

61、 competitor analysis,demand prediction,and targeted promotionsPersonalized recommendations by analyzing customer purchasing behaviorShopify has launched Shopify Magic,which automatically generates product descriptions Tesco is exploring gen AI for accurate demand predictions,promotions etc.Nestle ha

62、s leveraged AI assistants with OpenAI for business intelligence discoveryAutomotiveInnovative design via customer preferences,market trends,and performance analysisPersonalized route predictions and service suggestions enhance user experienceProducing synthetic data for simulations to expedite auton

63、omous vehicle researchBMW has implemented an AI-based system that incorporates generative design principlesFaraday Futures has created gen AI product stack personalizes driver experiences Haomo.AI has developed DriveGPT,an autonomous driving support platform TelecomOptimizing network performance thr

64、ough data analysis and pattern-based suggestionsGenerating personalized content for customer acquisition campaigns,boosting engagement and loyaltyPersonalized customer support through chatbots with issue resolution suggestionsAmdocs has launched amAIz,a telco gen AI framework with carrier-grade arch

65、itectureVerizon has utilized gen AI for lead scoring,personalization,and recommendations Together,South Korean operator KT and NVIDIA have developed a LLM for smart speakers and call |this document has been licensed to Xoriant8NAVIGATING THE ADOPTION OF GENERATIVE AIGen AI has the potential to trans

66、form how organizations across industries operate and innovate,whether through personalized customer experiences,optimized pricing strategies,accelerated drug discovery,or enhanced data analysis.With gen AIs rapid growth,enterprises find themselves compelled to embrace its adoption at an accelerated

67、pace.However,successful adoption requires enterprises to carefully navigate crucial considerations and prerequisites to ensure a fruitful implementation.In the following section,we explore best practices for the successful implementation of gen AI use cases.Gen AI adoption roadmap for enterprisesIn

68、this section,we present a comprehensive gen AI adoption roadmap for enterprises,offering step-by-step guidance on crucial steps to successful gen AI adoption.EXHIBIT 4Key steps to gen AI adoptionSource:Everest Group(2023)0102040305Assessing use case suitabilityEvaluating the amenability of the use c

69、ase in the context of business impact and gen AI relevanceEvaluating talent requirementsAssessing the talent strategy and key roles gaining relevance across various stages of gen AIGovernance and risk managementEvaluating key considerations to minimize risk and facilitate scaled adoptionEnsuring dat

70、a readinessEnsuring robust data readiness through data collection,curation,and governanceTools/technology considerationsEvaluating tools and technologies requirements to build and run gen AI |this document has been licensed to Xoriant9NAVIGATING THE ADOPTION OF GENERATIVE AIStep 1:Assessing use case

71、 suitabilityWith several competing priorities around technology adoption,diligent use case identification and prioritization is an indispensable step in realizing downstream value.To optimize resources and time,organizations must first strategically identify the most impactful use cases that align w

72、ith their business goals and can deliver tangible benefits.Use case suitability needs to be assessed along two key dimensions:Gen AI relevance:Assessing gen AIs ability to generate content for the intended use case,which involves reviewing the accuracy,relevance,and consistency of the produced conte

73、nt with its intended purpose.Business impact:Assessing gen AIs impact on various aspects of the organization,including processes and outcomes such as customer engagement,operational efficiency,cost savings,and innovation.By thoughtfully considering these factors,enterprises can make well-informed de

74、cisions when selecting use cases.Exhibit 5 offers an illustrative example of high-potential opportunities around gen AI within the Banking,Financial Services,and Insurance(BFSI)industry.EXHIBIT 5Relative amenability of select BFSI industry use cases to gen AISource:Everest Group(2023)Business Impact

75、Measures both positive and negative effects:positives include issues such as improved efficiency and enhanced customer experience;negatives include biased or unreliable outputs and other risksScalabilityMeasures the ability to scale the adoption of gen AI for a use case without sacrificing efficienc

76、y or accuracy,ensuring that it can adapt seamlessly as requirements growFeasibilityDetermines whether gen AI can be viably applied to a use cases considering data availability,computational resources,and ethical/regulatory factorsUse case-specific suitabilityEvaluates whether the use case can benefi

77、t from gen AI effectively,considering whether the gen AI output aligns well with the desired outcome for the use caseOrganizational impactAssessing the effectiveness and success of implementing gen AIGen AI relevanceMeasures its ability to effectively generate content that aligns with use caseHighLo

78、wWAITLowHighEVALUATEEDUCATEACCELERATESales&marketingCustomer servicePersonalized servicesFraud detectionRisk managementCompliance&monitoringLoan processingWealth managementTradingDynamic insurance |this document has been licensed to Xoriant10NAVIGATING THE ADOPTION OF GENERATIVE AIStep 2:Ensuring da

79、ta readinessOnce use case identification is complete,the next task is to identify and prepare relevant data sources,which is fundamental to effectively using gen AI.Data is the foundation for training and improving ML algorithms,enabling them to identify patterns,make precise predictions,and generat

80、e valuable content.To increase effectiveness,ML models are shifting from a model-centric to a data-centric approach,where ML models are treated as fixed components and the focus is on continuously improving the data to achieve better outcomes.The first step in data preparation is identifying the dat

81、a requirements for specific use cases,considering structured and unstructured sources such as text,images,audio,and sensors.Understanding use case complexity is crucial to pinpointing relevant data sources,often requiring specialized data sets for optimal results,such as varied text data for languag

82、e models or extensive annotated sets for visual models.Data Source identification is followed by data curation,which involves processes such as cleansing,annotating,and ensuring label quality.This step is the most crucial in ensuring data readiness and typically entails over 40%of the overall effort

83、 in enabling gen AI adoption.Meticulous data curation helps enterprises to form highly effective data sets,which,in turn,boosts the efficacy of gen AI models.Exhibit 6 shows the key data curation sub-steps.OpenAIs ChatGPT-3 was trained on a massive data set:45TB of text and 175 billion parameters.Th

84、e latest iteration,ChatGPT-4,has been trained on over a trillion parameters and significantly more data.EXHIBIT 6Key steps for data curationSource:Everest Group(2023)Data collectionData preparationData annotation and labelingAnnotation QCIn-house dataAcquired data Crowdsourcing Data studios Third pa

85、rty dataSynthetic dataData classification,verification,and randomizationData visualizationData cleansingDataset segregationData enrichmentPlatform deploymentManual annotation and labelingAI-assisted annotation and labelingManual QCAutomated QC |this document has been licensed to Xoriant11NAVIGATING

86、THE ADOPTION OF GENERATIVE AIStep 3:Talent considerations for gen AI adoptionThe novelty of gen AI necessitates any enterprise setting out to adopt it to consider a significant talent overhaul.While there are several traditional/existing skill sets that will be relevant in enabling gen AI adoption,e

87、nterprises will need to hire for or reskill/upskill their existing talent on many net-new skill sets as well.The talent base of specialists with expertise in algorithms,models,and AI techniques will have to be scaled up,while net-new hiring/training will be required around emerging roles such as pro

88、mpt engineers,AI trainers,AI data curators,AI deployment specialists,and AI strategy consultants.Exhibit 7 details the key talent requirements at various stages of enabling gen AI.Among all global companies that specialize in building AI-based solutions,less than 1%claim to have a holistic talent ba

89、se for building gen AI solutions.EXHIBIT 7Talent requirements across gen AI adoption stagesSource:Everest Group(2023)KEY STEPS INVOLVED IN BUILDING AND RUNNING GEN AI MODELSData preparationModel developmentModel training and testingModel deployment Model monitoringTraditional skillsNew skills gainin

90、g tractionFeedback loopTALENT REQUIREMENTS ACROSS EACH STEP(not exhaustive)AI strategist,AI ethicist,AI auditorData scientist,software engineerAI data curatorAI research scientistAI trainerAI deployment specialistSecurity specialistDatabase adminNLP specialistAI data curatorSecurity specialistData a

91、rchitectPrompt engineerData privacy specialistPrompt engineerBusiness analystCloud architectQA engineerCloud architectData integration specialistML engineerML engineerML engineerResearch scientistSystem |this document has been licensed to Xoriant12NAVIGATING THE ADOPTION OF GENERATIVE AICodegenerati

92、onSynthetic data generationTextgenerationFinancial risk mitigationInnovative designs for chipsDrug discoveryDynamic pricingApplication layerModel layerData layerInfrastructure layerNet-new hiring around gen AI will be time-consuming and expensive,so enterprises must maximize the use of existing tale

93、nt to meet gen AI talent requirements by investing in comprehensive training programs across gen AI principles,data engineering,and prompt engineering,among other areas.Big-tech companies such as Google,IBM,AWS,and Microsoft are already providing certification and training programs in gen AI;it will

94、 be key to select a certification program that aligns with the enterprises gen AI technology choices.In addition,domain-specific certifications from platforms such as Deeplearning.AI will be beneficial for specific industry contexts.Embracing continuous learning and collaboration by participating in

95、 events and engaging in online communities will also be crucial to stay up to date on the gen AI advances.Last,it will be important for enterprises to identify suitable partners technology vendors,academia,and/or service providers that can help them scale up their gen AI capabilities rapidly,keep th

96、e skill sets updated,and optimize the costs incurred for scaling up and training.Step 4:Tool and technology requirements for gen AIGen AI adoption needs a comprehensive toolkit for model development,training,and deployment.A complete toolkit includes cutting-edge machine learning frameworks,cloud co

97、mputing services,data processing tools,test environments,and underlying hardware that come together and enable AI models to understand and generate human-like content.Exhibit 8 depicts the technology stack for gen AI.EXHIBIT 8Technology stack for gen AISource:Everest Group(2023)Horizontal use cases3

98、D asset generationVertical use casesAPI integrationData warehouse centralized repository for storing and managing data Data engineering collecting,preparing,and transforming raw data into a format suitable for analysis and modelingTokenizationData transformationData sourcesData integrationCloud comp

99、uting and storageHardware infrastructure MedNLPLLaMaMusicGenChatGlmLLM APIsTrainable modelsEnterprise buildingproprietary LLMFeature extractionData |this document has been licensed to Xoriant13NAVIGATING THE ADOPTION OF GENERATIVE AIAs enterprises assess their gen AI tool and technology requirements

100、,they need to make a few significant choices in the context of their prioritized use cases,which can have a significant bearing on the costs and effort involved in enabling the overall technology stack.We describe several examples below.Build vs.buy vs.partnerBuilding a gen AI solution from scratch

101、offers advantages such as bespoke customization and undisputed control over development,integration,and intellectual property ownership.However,it demands extensive investments in infrastructure and talent,and calls for availability of abundant proprietary data to be able to train the gen AI models.

102、In addition,the need for periodic retraining of models will also need ongoing investments.This approach may not be required by most enterprises unless they are considering building a dedicated offering/business around gen AI.Opting to buy and integrate existing gen AI models can prove advantageous f

103、or businesses lacking extensive technical knowledge or resources and will be a suitable approach for most use cases.This approach enables rapid introduction of new digital solutions to the market and allows allocation of resources toward distinct innovation endeavors.Enterprises can still invest in

104、fine-tuning the third-party gen AI models using their proprietary data to better fit their business context.We also expect enterprises to take a partnership route(with technology companies and even competitors).The ecosystem will facilitate sharing of insights,skill sets,best practices,and most impo

105、rtantly,data,for accelerating the time-to-market for gen AI solutions.However,thorough diligence around common objectives and complementing capabilities will be vital for the success of any such partnership.On-cloud vs.on-premises solutionsThe choice between on-premises and cloud depends on an enter

106、prises specific needs,data privacy concerns,and available resources.In many scenarios,on-premises models may struggle to compete with cloud solutions due to the cost and technological advantages offered by the cloud.Cloud platforms now also offer the additional benefit of access to the latest pre-tr

107、ained LLMs,offering easy deployment and scalability.The benefits of on-premises solutions around greater control over data and infrastructure may be beneficial in highly regulated industries such as BFSI and healthcare.However,running LLMs locally comes with operational overhead and maintenance chal

108、lenges.Thus,for these regulated use cases,a hybrid approach wherein,the data is stored and processed in-house and the cloud is leveraged for computational purposes will be suitable.Step 5:Governance and risk managementTo reduce challenges in gen AI adoption,organizations must address ethical conside

109、rations and comply with relevant regulations,in addition to navigating the technical complexities.By proactively addressing these issues,businesses can fully leverage the benefits of gen AI while mitigating potential risks.Exhibit 9 offers a framework to identify and assess key risks involved AI in

110、|this document has been licensed to Xoriant14NAVIGATING THE ADOPTION OF GENERATIVE AIEXHIBIT 9Gen AI risk assessment framework Source:Everest Group(2023)Trigger stageImpact on business continuityMagnitude of Impact01Data security and privacyConfidentiality using confidential data for model trainingD

111、ata leakage exposure of private informationData collection and storageExistential threatFinancial lossLegal implicationsReputational damageData reliability incorrect output02ExplainabilityTrustworthiness creating and spreading misinformationHallucinations false content due to limited training data s

112、etModel development and deploymentProduct/service level threatSocial impactReputational damageDeepfakes AI-generated content of people doing or saying things that not real03Ownership andresponsibilityCopyright ownership protecting IP generated by gen AIAccountability legal issues arising due to inco

113、rrect output or IP infringementPost deploymentProduct/service level threatLegal implicationsReputational damage04Bias and ethicalconsiderationsBiased outputUnethical responsesTraining data and model trainingLimited/no impactSocial impactLowMediumHighAs the field of gen AI continues to evolve,organiz

114、ations must stay vigilant and proactive in their risk and compliance efforts.By effectively addressing these challenges,organizations can confidently embrace gen AI while ensuring responsible and ethical |this document has been licensed to Xoriant15NAVIGATING THE ADOPTION OF GENERATIVE AIThe success

115、ful adoption and integration of gen AI also requires well-structured enterprise governance that enables ongoing innovation and scaled adoption of gen AI initiatives across the enterprise.Effective governance programs include items such as:A core team/steering committee that includes C-suite stakehol

116、der(s)and representatives from various relevant departments including IT,operations,finance,and legal,to centralize decision-making and resource allocation,ensure alignment with business strategies,provide clear accountability,and disseminate gen AI initiatives to the broader enterprise audience.Cha

117、nge management,which is crucial to ensure smooth adoption of gen AI given its potentially significant impact on workflows,roles,and processes.Organizations need to institutionalize robust processes to service specific aspects of communication,piloting,training,and feedback.Tracking impact of gen AI

118、is challenging,as benefits and returns may manifest in a variety of forms,including increased efficiency,improved decision-making,and enhanced user experience,among others.Organizations need to identify use case-specific Key Performance Indicators(KPIs)to measure the impact of gen AI implementation

119、on various aspects of the business.ConclusionGen AI has the potential to deliver significant benefits for enterprises be they building robust software,enhancing the features of product/service offerings,or delivering seamless customer experiences.These potential benefits have made it imperative for

120、enterprises across industries to experiment with,and eventually scale up,gen AI adoption to stay competitive.At the same time,scaling gen AI will be a gradual process requiring enterprises to make choices that will have long-term implications on their businesses.Gen AIs diverse applications,every on

121、e of which presents unique benefits along with associated requirements and challenges,necessitate a thoughtful customized selection of applications where gen AI capabilities best align with the business needs.Each also requires careful consideration around data,infrastructure,skilled talent,and risk

122、s mitigation and resolution.For enterprises to have access to all required gen AI skill sets and technological knowledge at scale,partnerships with technology vendors,service providers,and regulatory bodies,among others,will be inevitable.These collaborations will enable enterprises to navigate inte

123、gration complexities,access cutting-edge technologies,leverage expertise for effective deployment,and stay abreast of data protection and ethical standards.Knowledge sharing and best practices from industry peers will further accelerate gen AI initiatives.By fostering stakeholder partnerships,enterp

124、rises will be able to establish a strong foundation for successful gen AI adoption,maximizing benefits while mitigating NOTICE AND DISCLAIMERSIMPORTANT INFORMATION.PLEASE REVIEW THIS NOTICE CAREFULLY AND IN ITS ENTIRETY.THROUGH YOUR ACCESS,YOU AGREE TO EVEREST GROUPS TERMS OF USE.Everest Groups Term

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139、KX o r i a n t i s a S u n n y v a l e,C A h e a d q u a r t e r e d d i g i t a l e n g i n e e r i n g f i r m wi t h o f f i c e s i n t h e U S A,E u r o p e,a n d A s i a.F r o m s t a r t u p s t o F o r t u n e 1 0 0,we e n a b l e i n n o v a t i o n,a c c e l e r a t e t i me t o ma r k e t

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141、n we d e v e l o p b e n e f i t s f r o m o u r p r o d u c t e n g i n e e r i n g D N A a n d c u l t u r e o f i n n o v a t i o n.I t a l s o i n c l u d e s s u c c e s s f u l me t h o d o l o g i e s,f r a me wo r k c o mp o n e n t s,a n d a c c e l e r a t o r s f o r r a p i d l y s o l v i n g c r i t i c a l c l i e n t c h a l l e n g e s.F o r 3 0 y e a r s a n d c o u n t i n g,we h a v e t a k e n g r e a t p r i d e i n t h e l o n g-l a s t i n g,d e e p r e l a t i o n s h i p s we h a v e wi t h o u r c l i e n t s.2 0 2 3 X o r i a n t -A l l R i g h t s R e s e r v e d