为什么人工智能驱动的商店是零售业的未来

CONTENTSTwo Key Benefits Of Generative AI In Store OperationDrive cost and productivity improvementsFuel new growthUnlocking Generative AI Value In Stores EmpowersStaffAnd Builds MomentumEmpower everyoneBuild momentumGenerative AI Use Cases For Store AssociatesDaily associate tasksCustomer support assistantStore managementKnowledge assistantOnboarding and trainingInventory managment 44677788910111212 © Oliver WymanIn the dynamic world of retail,generative artificial intelligence(generative AI)is revolutionizing the game. But can it also revolutionizehow retail stores operate? In this article, we explore how generative AIcan serve as a catalyst for retailers to operate their stores leaner and morecost-efficiently, while providing store associates with enhanced knowledgeand decision support. Furthermore, we believe that generative AI has thepotential to fuel new growth for retailers, particularly by improving thecustomer shopping experience through hyper-personalized offers. Thisarticle delves into the impact of generative AI on store operations and theworkforce, showcasing accessible and ready-to-implement use cases thatcan generate high impact in these early stages of technology adoption. © Oliver WymanTWO KEY BENEFITS OF GENERATIVEAI IN STORE OPERATION1Oliver Wyman Forum Generative AI report with 25,000 global respondents across 19 countries including US, Canada,Mexico, BrazilThe adoption of generative AI in stores brings forth a twofold benefit: driving cost andproductivity improvements, and fueling new growth. Together, these benefits create avirtuous cycle that propels businesses forward.DRIVE COST AND PRODUCTIVITY IMPROVEMENTSImagine a store where 40% to 60% of human tasks are automated using AI. First-linemanagers (e.g., store managers, shift leaders) believe that 45% of their own jobs could beautomated by generative AI, which aligns with various expert views. In contrast, entry-levelblue-collar employees think only 36% of their jobs could be automated by AI. However,experts believe the potential for automation in these roles is much higher, in the rangeof 60% or more.1Generative AI acts as a catalyst for efficiency and effectiveness in store operations in thefollowing three areas.•Streamlining repetitive tasks of store associates.Generative AI can automaterecurring tasks, such as employee labor scheduling, predictive maintenance ofstore equipment, routine customer inquiries (for instance returns or exchanges),or onboarding of new colleagues, freeing up employees’ time to focus on higher-valueactivities like customer interaction and sales opportunities.•Enabling better and faster decision-makingby augmenting (not replacing) humanexpertise with generative AI “copilots.” For example, generative AI can support associatesin answering more complex customer questions or supporting inventory managementand production planning decisions.•Elevating the role of store managementby shifting focus from task executionto validation and action-taking. For example, generative AI can support store anddepartment managers through automated reporting analysis, summary of insights,and action planning based on multiple daily store and department performance reports,alerting compliance issues, flagging waste reduction opportunities, or detecting fraudin stores. © Oliver WymanEquipping store associates withgenerative AI allows associatesto shift from task-oriented rolesto more customer-facing roles,eventually driving higher sales andcustomer loyalty for the store © Oliver WymanFUEL NEW GROWTHFueling new growth is driven mainly by three types of generative AI solutions.•Solutions that supportstore associates in better serving customers, for example byusing generative AI copilots to help answer basic or more complex customer questions(for instance, “Help me find a healthy cereal option for kids under $5.”)•Reallocating time freed up by generative AI solutions, for example time savings fromautomating repetitive tasks and supporting decision-making can be invested in activitieshighly valued by customers.•End-customer-directedsales and profitability-driving generative AI solutions,for example:–Hyper-personalized customer outreach, such as promotions and productrecommendations, leveraging data at scale for improved relevance–Offering unique services like meal inspiration and planning through AIcopilots–Redirecting increased productivity toward innovation, particularly in merchandisingand marketing functionsSolutions in the last category are primarily driven by leveraging generative AI in upstreamfunctions, such as marketing and merchandizing, and are less prevalent in the hands ofstore operators. However, as we take an end-to-end view of the impact of generative AI onomni-channel shopping, we did not want to miss mentioning these opportunities in this article.Oliver Wyman’s most recent research shows that consumers’ interest in user-facingAI solutions is currently limited. This is particularly driven by concerns around datapriv