GBS如何在客户体验中利用生成式人工智能

Introduction: A New Era for Customers andBusinesses AlikeThe Types of Generative AI Shaping Customer ExperienceHow Generative AI Can Overcome CommonCX ChallengesGetting AI Up and Running Effectively6 Ways to Track the Impact of Generative AI in CXUsing a Knowledge Base to Create Accurate BotsKey TakeawaysTable of ContentsEvan BeebeEditorSSON 81061214 © SSON 20232023 has been a year defined by the growth of artificialintelligence. The explosion of generative AI and largelanguage models such as ChatGPT have impacted howworkers work, students learn, businesses operate, andeverything else in between.While these solutions are not yet on the same level as HAL9000 from Stanley Kubrick’s “2001 Space Odessey,” theacceleration of AI capabilities are beginning to garnerinternational attention. This Fall, world leaders, computerscientists, and AI executives met in England to collectivelymanage the risk from AI and charter a safe way forward inhandling the rapidly evolving technology.Similar to the international community, Shared ServicesOrganizations (SSOs) and Global Business Services (GBS)are looking to mitigate technology risks while also seekingvalue-adding opportunities presented by generative AI.Data shows that GBS organizations have been cautious tolaunch generative AI technologies. According to a surveyfrom SSON Research & Analytics, as of October 2023, over50% of organizations have yet to complete any generative AIprojects, and an additional 30% have only completed one ortwo projects.Despite this slow rollout of generative AI projects, there is stilla widespread understanding among business leaders for howcritical generative AI will be for future business operations.When asked by SSON R&A, over half of GBS leaders saidgenerative AI was highly critical for their organization’ssuccess, while only 15% viewed the latest in AI as “slightlycritical” or “not critical at all.” Generative AI is so critical toGBS because it provides a new opportunity for GBS to reaffirmits value to the organization. By taking charge of generativeAI projects GBS can prove it is on the cutting-edge of newtechnologies, making itself invaluable to the business.Introduction:A New Era for Customers and Businesses Alike © SSON 2023What type of new SSO / GBS services do you plan to offer support by Generative Al?**Respondents could selcect multiple answersBusiness intelligence & analyticsKnowledge management & model curation as a serviceMarketing, content creation & communication supportEngineering - code generationcontinuedWith so many leaders viewing these solutions ascritical, it is imperative that GBS deliver a successfulROI on generative AI projects. In order to do so, manyorganizations are looking for quick wins in their generativeAI implementations. One of the places GBS is looking tobring in generative AI first is customer experience (CX).53% of SSOs/GBS told SSON R&A that improving thecustomer experience is one of the first use cases they arepursuing in generative AI, second only to analytics andinsights generation.CX is a critical component to the success of a business.According to PWC, after price and product quality,customers view their experience as the most important Customer serviceSales enablementLow code codingOtherProduct launch support factor in their purchasing decisions. And with over 40% ofSSOs/GBS playing a role in shaping their organizations CX,according to SSON R&A, creating a meaningful customerjourney is a very relevant topic to the shared servicesindustry. By deploying generative AI technologies into CX,shared services have the opportunity to provide benefitssuch as personalization, quicker response times, an easedworkload for service staff, and much more.Throughout this report, we will break down all the benefitsgenerative AI is offering CX, as well as risks implementationteams need to be aware of, but first, let’s take a step back tounderstand what generative AI is, and which specific aspectsof generative AI are helpful for CX. © SSON 2023The Types of Generative AI ShapingCustomer ExperienceThe SSON Glossary defines generative AI as “a type ofartificial intelligence that enables machines to generatenew content or data, such as text, images, or even entireapplications. Unlike other types of AI, such as predictive orprescriptive AI, which are based on existing data, generativeAI creates new data or content by learning patterns andrules from existing data.”Generative AI might appear similar to what businesseshave seen from machine learning in years past, andgenerative AI is in fact a subset of machine learning.However, generative AI is specifically focused on creatingmodels that can generate new, realistic data samples,while machine learning is more the development ofalgorithms and models that enable computers to learnfrom data and make predictions or decisions withoutbeing explicitly programmed.One of the most commonly used examples of generativeAI today is ChatGPT, a chatbot unlike any seen previously.ChatGPT