[{"data":1,"prerenderedAt":669},["ShallowReactive",2],{"uc-store-associate-assistant":3,"uc-regulations":443},{"useCase":4,"evidence":191,"blitsAiDeployments":296,"benchmarks":297,"indicative":314,"related":317,"indexability":441,"includeUnpublished":197},{"title":5,"shortTitle":6,"seoTitle":5,"metaDescription":7,"status":8,"definition":9,"aliases":10,"industries":16,"functions":18,"patterns":22,"channels":25,"audience":28,"autonomy":29,"adoptionStage":30,"segment":31,"problem":32,"problemStats":33,"howItWorks":34,"valueDrivers":35,"kpis":39,"indicativeValue":44,"macroEstimates":93,"feasibility":94,"implementation":106,"risk":147,"blitsAi":171,"faq":173,"related":183,"datePublished":186,"dateModified":186,"lastVerified":186,"changelog":187,"slug":190},"AI assistant for retail store associates","Store associate assistant","Associate assistants answer product, process and stock questions on a handheld. Walmart's conversational AI has 900,000 weekly users; Lowe's covers 1,700 stores.","published","A store associate assistant is conversational AI on an associate's handheld or app, increasingly generative, that answers product, process, schedule and inventory questions in natural language while the associate works on the floor. The associate decides what to tell the customer and does the task; the assistant supplies the answer and its source.",[11,12,13,14,15],"retail associate AI assistant","store team member chatbot","frontline retail copilot","AI assistant for store employees","associate app conversational AI",[17],"retail-and-ecommerce",[19,20,21],"knowledge-management","customer-service","operations",[23,24],"rag-knowledge-assistant","conversational-agent",[26,27],"internal-tools","mobile-app","employee-facing","assist","early-adopters","store-operations","A store associate gets questions on thousands of products, projects and store procedures, and the\nanswer sits in a product catalog, a process guide, an inventory system or another colleague's\nhead. Lowe's says associate expertise is uniquely valuable for home improvement retailers because\ncustomers ask daily about a variety of complex projects and thousands of different products. A\nnew hire cannot know all of it, and an experienced associate asked about another department\ncannot either.\n\nThe cost shows up in two places. The customer waits while the associate looks for a manager or a\nterminal, and a new or seasonal hire takes longer to become useful. Process questions, such as\nhow to restart a register after a power outage or how to take back an item without a receipt,\nare examples that can hold up a queue.",[],"1. **Connect the sources.** The assistant is grounded in the retailer's own material: product\n   data, project guides, process documents and store procedures, and live inventory and schedule\n   lookups through the systems that hold them.\n2. **Put it where the associate works.** It runs as an app on the handheld devices or in the\n   associate app already in use, and accepts typed or spoken questions, as in Lowe's\n   voice to text for hands free use.\n3. **Answer from the sources.** The associate asks a question in plain language, for example how\n   to sign a guest up for a loyalty card. The assistant retrieves the relevant guide or record\n   and returns steps or facts in seconds, rather than inventing them.\n4. **Turn long guides into steps.** In June 2025 Walmart announced an upgrade to its associate\n   assistant, due to launch in the coming months, that would use generative AI to turn lengthy\n   process guides into clear step by step instructions, for questions such as processing a\n   return without a receipt. At that date it was an announcement, not a delivered capability.\n5. **Coach and escalate.** The assistant can act as a coach for new and seasonal hires, as\n   Target describes for Store Companion. A well designed one says when the sources do not cover\n   a question and points the associate to a manager or a specialist.",[36,37,38],"employee-productivity","customer-experience","cost-to-serve",[40,41,42,43],"users-served","interactions-handled","customer-satisfaction-uplift","time-to-proficiency-reduction",{"referenceOrg":45,"inputs":46,"formula":88,"currency":89,"period":90,"resultLabel":91,"caveat":92},"A home improvement or grocery chain with 300 stores",[47,53,60,67,74,81],{"key":48,"label":49,"low":50,"high":51,"unit":48,"note":52},"stores","Stores in the chain",250,350,"Illustrative chain size, well below the 1,700 Lowe's stores and the nearly 2,000 Target stores that Target's release names.",{"key":54,"label":55,"low":56,"high":57,"unit":58,"note":59},"associatesPerStore","Associates who use the assistant per store",50,70,"associates per store","Editorial assumption, replace with your own headcount of floor associates with a device.",{"key":61,"label":62,"low":63,"high":64,"unit":65,"note":66},"queriesPerAssociateDay","Questions an associate asks the assistant per working day",2.5,3.5,"questions per associate per day","Derived from Walmart's reported 3 million queries per day and 900,000 weekly users, about 3.3 per weekly user per day if every user asked daily. Walmart does not state the ratio itself, so the range is kept around it.",{"key":68,"label":69,"low":70,"high":71,"unit":72,"note":73},"minutesSavedPerQuestion","Minutes saved per question compared with finding the answer another way",0.5,1.5,"minutes","Editorial assumption, replace with your own time study of how long a lookup, a call to a colleague or a walk to a terminal takes today.",{"key":75,"label":76,"low":77,"high":78,"unit":79,"note":80},"workingDays","Working days per associate per year",210,230,"days","Editorial assumption for a mix of full time and part time associates.",{"key":82,"label":83,"low":84,"high":85,"unit":86,"note":87},"hourlyCost","Fully loaded cost of an associate hour",16,22,"USD per hour","Editorial assumption, replace with your own fully loaded wage cost.","stores * associatesPerStore * queriesPerAssociateDay * minutesSavedPerQuestion \u002F 60 * workingDays * hourlyCost","USD","per year","Value of associate time saved on lookups","The result is time that associates can spend with customers, not cash that leaves the payroll. It leaves out the cost of building and running the assistant, any change in sales or satisfaction (Lowe's CEO is reported to have said customer satisfaction is about 2% higher when associates use its tool, without describing the comparison), and the faster onboarding of new hires, which needs its own estimate.",[],{"complexity":95,"complexityNote":96,"dataPrerequisites":97,"integrations":101},"medium","The build starts with the content: product data, project and process documents, each with an owner who keeps it current, and read access to inventory and schedule systems. Store handhelds or an associate app need single sign on and a place for a chat panel, and the retailer needs a feedback loop from associates to correct wrong answers.",[98,99,100],"Current process guides, store procedures and training material in a form that can be indexed","Product and project content, including regional or banner differences","Read access to inventory, location and schedule data for the associate's own store",[102,103,104,105],"Associate app or handheld device software, with single sign on","Inventory and product information systems","Workforce or schedule system, if schedule questions are in scope","Document or content management system that holds the process guides",{"steps":107,"guardrails":123,"humanInTheLoop":128,"kpisToInstrument":129,"failureModes":134},[108,111,114,117,120],{"title":109,"detail":110},"Start with one question type and one department","Pick the questions that hold up the floor most often, such as register procedures or returns rules, and launch in a few stores. Target piloted Store Companion in about 400 stores before its chainwide rollout.",{"title":112,"detail":113},"Ground every answer in a named source","Show the guide or record behind each answer so the associate can check it and a content owner can fix it. An answer without a source on a process question is a risk at the register.",{"title":115,"detail":116},"Give content owners a correction path","Let associates flag a wrong or stale answer from the answer itself, and route the flag to the person who owns that document, with a deadline.",{"title":118,"detail":119},"Add live data once static answers hold","Add inventory, location and schedule lookups after the document answers are reliable, because a wrong stock count costs more trust than a missing one.",{"title":121,"detail":122},"Measure use before claiming value","Track weekly users, questions, answers marked helpful and the share that end in an escalation, then compare customer satisfaction between stores or shifts with and without it.",[124,125,126,127],"Answers on pricing, returns, age restricted sales and safety procedures come only from approved documents","The assistant says when it has no source and points to a manager, instead of guessing","Question logs are kept for quality review under a stated retention period and are not used to rank individual associates","New or changed process documents are tested against a fixed set of questions before they go live","The associate stays the decision maker: the assistant informs, and the associate talks to the customer and carries out the task. Content owners review flagged answers, and store managers decide which procedures the assistant may explain.",[130,131,132,133],"Weekly active associates as a share of associates with a device","Questions per day, by topic, and the share answered from a source","Share of answers marked helpful or corrected by associates","Customer satisfaction in stores or shifts that use the assistant compared with those that do not",[135,138,141,144],{"title":136,"detail":137},"Stale process guides","A returns or promotion rule changes and the assistant keeps quoting the old guide. Give each document an owner and a review date, and retire guides that nobody maintains.",{"title":139,"detail":140},"Confident answers without a source","A fluent wrong answer on a procedure is more damaging than a slow right one. Require a retrieved source for every procedural answer and show it.",{"title":142,"detail":143},"Slow response on the floor","An answer that takes longer than asking a colleague will not be used. Test latency on the actual handheld and store network, and keep answers short.",{"title":145,"detail":146},"Usage read as value","High query counts show that associates open the tool, not that customers are served better. Pair usage with a satisfaction or conversion comparison, as Lowe's does with its satisfaction figure.",{"euAiAct":148,"regulations":151,"guidance":154,"controls":165,"incidents":170},{"tier":149,"basis":150},"context-dependent","An assistant that only answers product, process and inventory questions for employees is not listed in Annex III and is not a high risk system, with AI literacy duties for the deployer under Article 4. Article 50(1) transparency duties also reach systems that interact directly with people, employees included, unless it is obvious from the circumstances that they are dealing with AI. Annex III point 4(b) covers systems intended to allocate tasks based on individual behavior or personal traits or to monitor and evaluate worker performance and behavior. An associate app that also assigns tasks to individual associates or scores them falls to be assessed under that point, so the design decides the tier. Walmart's separate AI task tool, which recommends and prioritizes tasks for overnight stocking, shows how close the two categories sit, and the source does not say whether it allocates by individual behavior.",[152,153],"eu-ai-act","gdpr",[155,161],{"title":156,"issuer":157,"region":158,"url":159,"note":160},"Regulation (EU) 2024\u002F1689 (EU AI Act), Article 4 and Annex III point 4","European Union","europe","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2024\u002F1689\u002Foj","Article 4 requires AI literacy for staff who use AI systems; Annex III point 4 lists employment and worker management systems, which applies if the assistant is extended to task allocation or performance monitoring.",{"title":162,"issuer":157,"region":158,"url":163,"note":164},"Regulation (EU) 2016\u002F679 (GDPR)","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2016\u002F679\u002Foj","Question logs identify associates and can reveal their knowledge gaps, so purpose limitation, retention and transparency duties for employee data apply.",[166,167,168,169],"A named owner and review date for every document the assistant can quote","Logging of questions, retrieved sources and answers, with a retention period agreed with employee representatives","A visible way for associates to flag a wrong answer, with a tracked fix","A test set of procedure questions that must pass before a content change goes live",[],{"howToBuild":172},"Blits.ai does not replace the retailer's inventory or product systems; it adds the conversational\nlayer on top of them. An **AI agent** grounded in a **knowledge base** with **hybrid retrieval**\nover the retailer's process guides, product content and training material answers an associate's\nquestion with the passage it came from. **Custom functions** and **SQL knowledge bases** read\ninventory, location and schedule data from the systems that hold them, and **guardrails** keep\npricing and returns answers to approved documents.\n\nThe agent reaches the floor through the **REST API channel** or **WebSocket API channel** in the\nretailer's own associate app, or through **Microsoft Teams**, with **voice** input for hands free\nuse. **Human handover** passes a question the sources cannot answer to a manager, **test suites**\nrun a fixed set of procedure questions before each content change, and **analytics** show\nquestions by topic and the untrained ones that need new content. Because the platform is\n**model agnostic**, the retailer can choose the model per question type, and **EU and UAE data\nresidency** keeps associate question logs in region.",[174,177,180],{"question":175,"answer":176},"How is a store associate assistant different from a customer shopping assistant?","The associate assistant is employee facing, so the associate can judge an answer and correct it before passing it on, which makes errors easier to catch than with a customer facing bot. It does not guarantee they are caught, because an associate can still pass a wrong answer to the customer. Lowe's built Mylow Companion on the same foundation as its customer facing Mylow advisor, which shows the two can share models and content while serving different users. Assistants for telecom shops, including customer facing kiosks and digital humans, are covered on the retail store and kiosk assistant page.",{"question":178,"answer":179},"What results have retailers reported?","Walmart reports more than 900,000 weekly users and over 3 million queries per day on its associate conversational AI. That assistant has been in use for about five years and is not the generative upgrade Walmart announced in June 2025, so the figures do not measure generative AI. Digital Commerce 360 reports that Lowe's CEO said customer satisfaction scores are about 2% higher when employees use Mylow Companion, without describing the comparison. Target has disclosed no outcome figures for Store Companion. The figures are the retailers' own statements, not audits.",{"question":181,"answer":182},"How do we know whether a store associate assistant is working?","Usage shows that associates open the tool, not that customers are served better. Walmart reports weekly users and queries per day, and Lowe's reported a satisfaction difference without describing the comparison. Track weekly active associates, answers marked helpful or corrected, and the share that end in an escalation, then compare customer satisfaction between stores or shifts with and without the assistant.",[184,185],"retail-store-and-kiosk-assistant","conversational-shopping-assistant","2026-10-14",[188],{"date":186,"note":189},"First published","store-associate-assistant",[192,240,270],{"title":193,"useCases":194,"organization":195,"vendors":201,"summary":205,"stage":206,"year":207,"channels":208,"languages":209,"metrics":211,"outcomeDisclosed":221,"sources":222,"verification":235,"grade":237,"id":238,"organizationSlug":239},"Lowe's: Mylow Companion assistant for store associates",[190],{"name":196,"anonymized":197,"country":198,"region":199,"industry":17,"wikidata":200},"Lowe's",false,"US","north-america","Q1373493",[202],{"name":203,"role":204},"OpenAI","model-provider","Lowe's launched Mylow Companion on 5 May 2025 to every associate across its more than 1,700 stores. The generative AI app runs on the handheld devices associates already carry on the sales floor and answers questions about product details, project advice and inventory in natural language, including by voice. Lowe's built it with OpenAI on the same foundation as Mylow, its customer facing advisor, and positions it as a way to speed up onboarding of new hires. On the third quarter 2025 earnings call, CEO Marvin Ellison said customer satisfaction scores were about 2% higher when employees use Mylow Companion in stores, a comparison Lowe's did not describe further.","scaled",2025,[26],[210],"en",[212],{"kpi":42,"value":213,"unit":214,"qualifier":215,"period":216,"baseline":217,"claimant":218,"quote":219,"sourceUrl":220},2,"percent","approximately","fiscal Q3 2025 earnings call of 19 November 2025, as reported by Digital Commerce 360 on 20 November 2025","interactions where associates do not use Mylow Companion (comparison group not described)","organization","Additionally, customer satisfaction scores are about 2% higher when employees use Mylow Companion to help consumers shop in stores, Ellison said.","https:\u002F\u002Fwww.digitalcommerce360.com\u002F2025\u002F11\u002F20\u002Flowes-online-sales-q3-fy25\u002Famp\u002F",true,[223,227,231],{"url":224,"title":225,"publisher":196,"date":226},"https:\u002F\u002Fcorporate.lowes.com\u002Fnewsroom\u002Fpress-releases\u002Flowes-deploys-first-scale-ai-assistant-retail-associates-05-05-25","Lowe's deploys first at-scale AI assistant for retail associates","2025-05-05",{"url":220,"title":228,"publisher":229,"date":230},"Lowe's grows online sales in Q3, plans for agentic commerce","Digital Commerce 360","2025-11-20",{"url":232,"title":233,"publisher":196,"date":234},"https:\u002F\u002Fcorporate.lowes.com\u002Fnewsroom\u002Fpress-releases\u002Flowes-reports-third-quarter-2025-sales-and-earnings-results-11-19-25","Lowe's Reports Third Quarter 2025 Sales and Earnings Results","2025-11-19",{"level":236,"checkedAt":186},"source-verified","B","lowes-mylow-companion-associate-assistant",null,{"title":241,"useCases":242,"organization":243,"vendors":246,"summary":249,"stage":206,"year":207,"channels":250,"languages":251,"metrics":252,"outcomeDisclosed":221,"sources":263,"verification":267,"grade":237,"id":268,"organizationSlug":269},"Walmart: conversational AI assistant in the associate app",[190],{"name":244,"anonymized":197,"country":198,"region":199,"industry":17,"wikidata":245},"Walmart","Q483551",[247],{"name":244,"role":248},"in-house","Walmart associates in the United States have used a conversational AI assistant in the Walmart associate app for about five years to ask where products are located, check their schedule and look up how to do tasks. On 24 June 2025 Walmart said the assistant has more than 900,000 weekly users and handles over 3 million queries per day, and announced a generative AI upgrade that turns long process guides into step by step instructions, for example how to process a return without a receipt. In the same announcement Walmart described a real time translation tool for associates and customers in 44 languages. Walmart gives no accuracy or time saving figure for the assistant itself.",[26,27],[210],[253,260],{"kpi":40,"value":254,"unit":255,"qualifier":256,"period":257,"claimant":218,"quote":258,"sourceUrl":259},900000,"count","at-least","per week, as of 24 June 2025","With more than 900,000 weekly users and over 3 million queries per day, Walmart’s conversational AI has become an essential resource for associates.","https:\u002F\u002Fcorporate.walmart.com\u002Fnews\u002F2025\u002F06\u002F24\u002Fwalmart-unveils-new-ai-powered-tools-to-empower-1-5-million-associates",{"kpi":41,"value":261,"unit":255,"qualifier":256,"period":262,"claimant":218,"quote":258,"sourceUrl":259},3000000,"per day, as of 24 June 2025",[264],{"url":259,"title":265,"publisher":244,"date":266},"Walmart Unveils New AI-Powered Tools To Empower 1.5 Million Associates","2025-06-24",{"level":236,"checkedAt":186},"walmart-associate-conversational-ai","walmart",{"title":271,"useCases":272,"organization":273,"vendors":276,"summary":279,"stage":280,"year":281,"channels":282,"languages":283,"metrics":284,"outcomeDisclosed":197,"sources":285,"verification":294,"grade":237,"id":295,"organizationSlug":239},"Target: Store Companion assistant for store team members",[190],{"name":274,"anonymized":197,"country":198,"region":199,"industry":17,"wikidata":275},"Target Corporation","Q1046951",[277],{"name":278,"role":248},"Target","Target announced Store Companion on 20 June 2024, a generative AI chatbot built by its own technology team that runs as an app on the handheld devices of store team members. It answers process and procedure questions, for example how to restart a cash register after a power outage or how to sign a guest up for a Target Circle Card, and acts as a coach for new and seasonal team members. Target's release names nearly 2,000 stores for the rollout. The team trained it on real frequently asked questions and process documents from stores, went from first tests to planned rollout in six months and piloted it in about 400 stores before the chainwide launch planned for August 2024. A trade report in June 2025 states that Target rolled out Store Companion the year before. Target disclosed no usage or outcome figures.","production",2024,[26],[210],[],[286,290],{"url":287,"title":288,"publisher":274,"date":289},"https:\u002F\u002Fcorporate.target.com\u002Fpress\u002Frelease\u002F2024\u002F06\u002Ftarget-to-roll-out-transformative-genai-technology-to-its-store-team-members-chainwide","Target to Roll Out Transformative GenAI Technology to its Store Team Members Chainwide","2024-06-20",{"url":291,"title":292,"publisher":293},"https:\u002F\u002Fwww.hrdive.com\u002Fnews\u002Fwalmarts-ai-feature-aims-to-help-associates-overcome-language-barri\u002F751578\u002F","Walmart's latest AI feature aims to help associates overcome language barriers","HR Dive",{"level":236,"checkedAt":186},"target-store-companion-genai-chatbot",0,[298,304,309],{"kpi":41,"label":299,"unit":255,"aggregate":197,"higherIsBetter":221,"n":300,"nUpTo":296,"median":261,"min":261,"max":261,"byClaimant":301,"vendorOnly":197,"points":302},"Interactions handled",1,{"organization":300,"vendor":296,"regulator":296,"independent":296},[303],{"evidenceId":268,"organization":244,"value":261,"qualifier":256,"claimant":218,"grade":237,"pooled":221},{"kpi":42,"label":305,"unit":214,"aggregate":221,"higherIsBetter":221,"n":300,"nUpTo":296,"median":213,"min":213,"max":213,"byClaimant":306,"vendorOnly":197,"points":307},"Satisfaction uplift",{"organization":300,"vendor":296,"regulator":296,"independent":296},[308],{"evidenceId":238,"organization":196,"value":213,"qualifier":215,"claimant":218,"grade":237,"pooled":221},{"kpi":40,"label":310,"unit":255,"aggregate":197,"higherIsBetter":221,"n":300,"nUpTo":296,"median":254,"min":254,"max":254,"byClaimant":311,"vendorOnly":197,"points":312},"Users served",{"organization":300,"vendor":296,"regulator":296,"independent":296},[313],{"evidenceId":268,"organization":244,"value":254,"qualifier":256,"claimant":218,"grade":237,"pooled":221},{"low":315,"high":316},875000.0000000001,10847375,[318,346,377,414],{"slug":184,"title":319,"shortTitle":320,"definition":321,"status":8,"industries":322,"functions":324,"patterns":326,"audience":28,"autonomy":29,"adoptionStage":30,"segment":329,"evidenceCount":330,"publicEvidenceCount":330,"organizations":331,"bestGrade":237,"headline":338,"lastVerified":345,"indexable":221},"AI assistant for telecom retail stores, from associate copilot to digital human kiosk","Retail store and kiosk assistant","A retail store and kiosk assistant is AI for telecom shops that gives store associates quick, sourced answers on plans, promotions, devices and the customer's account during the conversation. It can also greet and serve customers directly on an in store screen or kiosk, sometimes as a digital human, handing them to an associate when they are ready to buy or need help.",[323],"telecommunications",[325,20,19],"sales",[23,327,24,328],"digital-human","recommendation-and-personalization","front-office",6,[332,333,334,335,336,337],"Bouygues Telecom","Deutsche Telekom","Orange Slovakia","Singtel","T-Mobile","Vodafone New Zealand",{"kpi":339,"label":340,"unit":214,"n":300,"nUpTo":296,"kind":341,"value":342,"qualifier":343,"claimant":344,"organization":332,"vendorReported":221},"accuracy","Accuracy","reported",95,"exact","vendor","2026-09-27",{"slug":185,"title":347,"shortTitle":348,"definition":349,"status":8,"industries":350,"functions":352,"patterns":354,"audience":356,"autonomy":357,"adoptionStage":30,"evidenceCount":358,"publicEvidenceCount":359,"organizations":360,"bestGrade":237,"headline":371,"lastVerified":345,"indexable":221},"AI shopping assistant for product discovery and recommendations","Conversational shopping assistant","An AI conversational shopping assistant answers product questions and recommends items from a retailer's own catalog, for a need, project or occasion a shopper describes. It works on the retailer's site or app, compares items grounded in the retailer's product data, reviews and stock, and hands the shopper to a basket, a store or a human expert.",[351,17],"cross-industry",[325,353,20],"marketing",[24,328,23,355],"agentic-workflow","customer-facing","autonomous",17,12,[361,362,363,364,365,196,366,367,368,369,244,370],"Albertsons Companies","Amazon","Carrefour","The Home Depot","Instacart","Michaels","Omoda","Pick n Pay","Sun & Ski Sports","Zalando",{"kpi":372,"label":373,"unit":214,"n":374,"nUpTo":296,"kind":375,"value":376,"qualifier":343,"claimant":218,"organization":239,"vendorReported":197},"conversion-rate-uplift","Conversion uplift",3,"median",100,{"slug":378,"title":379,"shortTitle":380,"definition":381,"status":8,"industries":382,"functions":388,"patterns":389,"audience":28,"autonomy":29,"adoptionStage":391,"evidenceCount":358,"publicEvidenceCount":358,"organizations":392,"bestGrade":237,"headline":410,"lastVerified":345,"indexable":221},"enterprise-knowledge-search","AI enterprise knowledge search for employees","Enterprise knowledge search","Enterprise knowledge search is an AI assistant that lets any employee ask a question in plain language and get a synthesized answer from the organization's own documents. It draws the answer from policies, procedures, product manuals and research, with citations to the source documents, and only from documents the employee is allowed to see.",[351,383,384,385,386,387],"banking","wealth-and-asset-management","insurance","government","professional-services",[19,21,20],[23,24,390],"summarization","mainstream",[393,394,395,396,397,398,399,400,401,402,403,404,405,406,407,408,409],"All Nippon Airways","Bank of America","Booking.com","Cathay Financial Holdings","DZ BANK AG","Insurance Australia Group","Ma'aden","Morgan Stanley","PLDT","Qatar Ministry of Municipality","Raiffeisen Bank International AG","Saudi Energy","SIGNAL IDUNA","Taiwan Business Bank","Wells Fargo","Zain Jordan","Zillow",{"kpi":411,"label":412,"unit":214,"n":374,"nUpTo":296,"kind":375,"value":413,"qualifier":343,"claimant":239,"organization":239,"vendorReported":197},"employee-adoption","Employee adoption",90,{"slug":415,"title":416,"shortTitle":417,"definition":418,"status":8,"industries":419,"functions":421,"patterns":422,"audience":356,"autonomy":424,"adoptionStage":391,"evidenceCount":425,"publicEvidenceCount":425,"organizations":426,"bestGrade":237,"headline":435,"lastVerified":440,"indexable":221},"order-status-and-returns-agent","AI agent for order status, delivery changes and returns","Order status and returns","An AI order status and returns agent answers \"where is my order\", changes delivery details and arranges returns, exchanges and refunds for online and omnichannel shoppers. It does this end to end, by reading and writing to the order, carrier and returns systems within the retailer's policy, and hands exceptions such as damaged goods, disputes and upset customers to a person.",[351,17,420],"payments",[20,21],[24,355,423,23],"voice-agent","supervised-agent",9,[427,428,429,430,431,432,369,433,434],"BARK","Best Buy","Klarna","Next","NOBULL","Nuuly","Vivid Seats","Woolworths Group",{"kpi":436,"label":437,"unit":214,"n":438,"nUpTo":296,"kind":375,"value":439,"qualifier":343,"claimant":344,"organization":239,"vendorReported":221},"customer-satisfaction","Customer satisfaction",4,92.5,"2026-09-26",{"indexable":221,"reasons":442},[],[444,448,452,460,467,474,480,487,495,502,508,514,520,527,534,540,546,552,558,565,570,575,581,587,594,599,604,610,617,622,629,636,641,647,653,658,663],{"id":152,"label":445,"issuer":157,"region":158,"url":159,"description":446,"useCases":447,"indexable":221},"EU AI Act","Regulation (EU) 2024\u002F1689: risk based rules for AI systems, with obligations for high risk systems listed in Annex III and transparency duties under Article 50.",295,{"id":153,"label":449,"issuer":157,"region":158,"url":163,"description":450,"useCases":451,"indexable":221},"GDPR","General Data Protection Regulation, including Article 22 on decisions based solely on automated processing.",265,{"id":453,"label":454,"issuer":455,"region":456,"url":457,"description":458,"useCases":459,"indexable":221},"iso-42001","ISO\u002FIEC 42001","ISO and IEC","global","https:\u002F\u002Fwww.iso.org\u002Fstandard\u002F81230.html","The international management system standard for AI.",148,{"id":461,"label":462,"issuer":463,"region":199,"url":464,"description":465,"useCases":466,"indexable":221},"nist-ai-rmf","NIST AI Risk Management Framework","NIST","https:\u002F\u002Fwww.nist.gov\u002Fitl\u002Fai-risk-management-framework","Voluntary US framework to map, measure, manage and govern AI risk, with a generative AI profile.",115,{"id":468,"label":469,"issuer":470,"region":158,"url":471,"description":472,"useCases":473,"indexable":221},"uk-gdpr","UK GDPR","Information Commissioner's Office","https:\u002F\u002Fico.org.uk\u002Ffor-organisations\u002Fuk-gdpr-guidance-and-resources\u002F","The UK's version of the GDPR, including rules on solely automated decisions.",84,{"id":475,"label":476,"issuer":157,"region":158,"url":477,"description":478,"useCases":479,"indexable":221},"dora","DORA","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2022\u002F2554\u002Foj","Digital Operational Resilience Act for financial entities: ICT risk, incident reporting and third party risk, including AI providers.",73,{"id":481,"label":482,"issuer":483,"region":158,"url":484,"description":485,"useCases":486,"indexable":221},"uk-consumer-duty","FCA Consumer Duty","Financial Conduct Authority","https:\u002F\u002Fwww.fca.org.uk\u002Ffirms\u002Fconsumer-duty","UK rules that require firms to deliver good outcomes for retail customers, including through automated channels.",53,{"id":488,"label":489,"issuer":490,"region":491,"url":492,"description":493,"useCases":494,"indexable":221},"mas-ai-risk-management","MAS AI risk management guidelines","Monetary Authority of Singapore","asia-pacific","https:\u002F\u002Fwww.mas.gov.sg\u002Fnews\u002Fmedia-releases\u002F2025\u002Fmas-guidelines-for-artificial-intelligence-risk-management","Singapore's supervisory expectations for AI risk management at financial institutions, building on the FEAT principles.",37,{"id":496,"label":497,"issuer":498,"region":491,"url":499,"description":500,"useCases":501,"indexable":221},"apra-cps-230","APRA CPS 230","Australian Prudential Regulation Authority","https:\u002F\u002Fwww.apra.gov.au\u002Foperational-risk-management","Australian operational risk standard covering critical operations and material service providers.",26,{"id":503,"label":504,"issuer":157,"region":158,"url":505,"description":506,"useCases":507,"indexable":221},"nis2","NIS2 Directive","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2022\u002F2555\u002Foj","Directive (EU) 2022\u002F2555 on cybersecurity for essential and important entities, including telecom networks, energy and public administration.",23,{"id":509,"label":510,"issuer":511,"region":456,"url":512,"description":513,"useCases":507,"indexable":221},"pci-dss","PCI DSS","PCI Security Standards Council","https:\u002F\u002Fwww.pcisecuritystandards.org\u002F","Security standard for any system that stores, processes or transmits cardholder data.",{"id":515,"label":516,"issuer":517,"region":199,"url":518,"description":519,"useCases":507,"indexable":221},"us-sr-11-7","SR 11-7 model risk management","Federal Reserve and OCC","https:\u002F\u002Fwww.federalreserve.gov\u002Fboarddocs\u002Fsrletters\u002F2011\u002Fsr1107.htm","US supervisory guidance on model risk management, applied by banks to AI and machine learning models.",{"id":521,"label":522,"issuer":523,"region":199,"url":524,"description":525,"useCases":526,"indexable":221},"hipaa","HIPAA","US Department of Health and Human Services","https:\u002F\u002Fwww.hhs.gov\u002Fhipaa\u002Findex.html","US rules for the privacy and security of protected health information.",20,{"id":528,"label":529,"issuer":530,"region":158,"url":531,"description":532,"useCases":533,"indexable":221},"uk-atrs","UK Algorithmic Transparency Recording Standard","UK Government","https:\u002F\u002Fwww.gov.uk\u002Fgovernment\u002Fcollections\u002Falgorithmic-transparency-recording-standard-hub","Mandatory transparency records for algorithmic tools used by UK central government.",18,{"id":535,"label":536,"issuer":157,"region":158,"url":537,"description":538,"useCases":539,"indexable":221},"eu-accessibility-act","European Accessibility Act","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2019\u002F882\u002Foj","Directive (EU) 2019\u002F882: accessibility requirements for banking services, ecommerce and other digital services, applicable since June 2025.",15,{"id":541,"label":542,"issuer":543,"region":456,"url":544,"description":545,"useCases":539,"indexable":221},"fatf-recommendations","FATF Recommendations","Financial Action Task Force","https:\u002F\u002Fwww.fatf-gafi.org\u002Fen\u002Fpublications\u002FFatfrecommendations\u002FFatf-recommendations.html","Global standards for anti money laundering and counter terrorist financing that national rules implement.",{"id":547,"label":548,"issuer":549,"region":199,"url":550,"description":551,"useCases":539,"indexable":221},"us-tcpa","Telephone Consumer Protection Act","Federal Communications Commission","https:\u002F\u002Fwww.fcc.gov\u002Fconsumers\u002Fguides\u002Fstop-unwanted-robocalls-and-texts","US consent rules for automated and prerecorded calls and texts; the FCC has confirmed AI generated voices count as artificial voices.",{"id":553,"label":554,"issuer":157,"region":158,"url":555,"description":556,"useCases":557,"indexable":221},"eu-amlr","EU Anti Money Laundering Regulation","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2024\u002F1624\u002Foj","Regulation (EU) 2024\u002F1624: the single EU rulebook for customer due diligence, beneficial ownership and suspicious transaction reporting.",14,{"id":559,"label":560,"issuer":561,"region":199,"url":562,"description":563,"useCases":564,"indexable":221},"us-bsa","Bank Secrecy Act","FinCEN","https:\u002F\u002Fwww.fincen.gov\u002Fresources\u002Fstatutes-and-regulations\u002Fbank-secrecy-act","US anti money laundering law: customer due diligence, suspicious activity reports and record keeping.",13,{"id":566,"label":567,"issuer":157,"region":158,"url":568,"description":569,"useCases":564,"indexable":221},"eu-psd2","PSD2","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2015\u002F2366\u002Foj","Payment Services Directive 2: strong customer authentication, transaction risk analysis exemptions and open banking access.",{"id":571,"label":572,"issuer":157,"region":158,"url":573,"description":574,"useCases":564,"indexable":221},"solvency-ii","Solvency II","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2009\u002F138\u002Foj","Directive 2009\u002F138\u002FEC: risk based capital, governance and model requirements for insurers.",{"id":576,"label":577,"issuer":578,"region":456,"url":579,"description":580,"useCases":564,"indexable":221},"telecom-consumer-rules","Telecom consumer protection rules","National telecom regulators","https:\u002F\u002Fwww.berec.europa.eu\u002F","National rules on telecom contracts, switching, billing disputes and marketing consent.",{"id":582,"label":583,"issuer":584,"region":199,"url":585,"description":586,"useCases":359,"indexable":221},"us-ecoa-reg-b","ECOA and Regulation B","Consumer Financial Protection Bureau","https:\u002F\u002Fwww.consumerfinance.gov\u002Frules-policy\u002Fregulations\u002F1002\u002F9\u002F","US fair lending rules, including specific reasons in adverse action notices, which also apply when credit decisions use AI models.",{"id":588,"label":589,"issuer":590,"region":158,"url":591,"description":592,"useCases":593,"indexable":221},"eba-loan-origination","EBA Guidelines on loan origination and monitoring","European Banking Authority","https:\u002F\u002Fwww.eba.europa.eu\u002Fregulation-and-policy\u002Fcredit-risk\u002Fguidelines-on-loan-origination-and-monitoring","Expectations for credit decisioning, including the use of automated models.",11,{"id":595,"label":596,"issuer":157,"region":158,"url":597,"description":598,"useCases":593,"indexable":221},"eecc","European Electronic Communications Code","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2018\u002F1972\u002Foj","Directive (EU) 2018\u002F1972: consumer protection, contract, switching and security rules for telecom operators.",{"id":600,"label":601,"issuer":157,"region":158,"url":602,"description":603,"useCases":593,"indexable":221},"mifid-ii","MiFID II","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2014\u002F65\u002Foj","Directive 2014\u002F65\u002FEU on markets in financial instruments: suitability and appropriateness of advice, record keeping and product governance.",{"id":605,"label":606,"issuer":490,"region":491,"url":607,"description":608,"useCases":609,"indexable":221},"mas-notice-626","MAS Notice 626","https:\u002F\u002Fwww.mas.gov.sg\u002Fregulation\u002Fnotices\u002Fnotice-626","Singapore's anti money laundering and counter terrorism financing requirements for banks.",10,{"id":611,"label":612,"issuer":613,"region":199,"url":614,"description":615,"useCases":616,"indexable":221},"us-fcra","Fair Credit Reporting Act","Federal Trade Commission","https:\u002F\u002Fwww.ftc.gov\u002Flegal-library\u002Fbrowse\u002Fstatutes\u002Ffair-credit-reporting-act","US rules on consumer reports, their accuracy and permissible use, relevant to credit scoring and screening.",8,{"id":618,"label":619,"issuer":157,"region":158,"url":620,"description":621,"useCases":616,"indexable":221},"eu-idd","Insurance Distribution Directive","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2016\u002F97\u002Foj","Directive (EU) 2016\u002F97: conduct rules for selling insurance, including demands and needs testing and advice.",{"id":623,"label":624,"issuer":625,"region":626,"url":627,"description":628,"useCases":330,"indexable":221},"cbuae-ai-guidance","CBUAE guidance on AI and ML","Central Bank of the UAE","middle-east","https:\u002F\u002Fwww.centralbank.ae\u002F","UAE central bank expectations for the enabling technologies, AI and machine learning used by licensed financial institutions.",{"id":630,"label":631,"issuer":632,"region":158,"url":633,"description":634,"useCases":635,"indexable":221},"uk-psr-app-reimbursement","UK APP scam reimbursement rules","Payment Systems Regulator","https:\u002F\u002Fwww.psr.org.uk\u002Four-work\u002Fapp-scams\u002F","Mandatory reimbursement of authorised push payment scam victims by UK payment firms, which shifts scam losses onto banks.",5,{"id":637,"label":638,"issuer":157,"region":158,"url":639,"description":640,"useCases":438,"indexable":221},"eu-mortgage-credit-directive","EU Mortgage Credit Directive","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2014\u002F17\u002Foj","Directive 2014\u002F17\u002FEU: creditworthiness assessment, disclosure and advice rules for residential mortgage lending.",{"id":642,"label":643,"issuer":644,"region":158,"url":645,"description":646,"useCases":438,"indexable":221},"pra-ss1-23","PRA SS1\u002F23 model risk management","Prudential Regulation Authority","https:\u002F\u002Fwww.bankofengland.co.uk\u002Fprudential-regulation\u002Fpublication\u002F2023\u002Fmay\u002Fmodel-risk-management-principles-for-banks-ss","UK model risk management principles for banks, covering AI and machine learning models.",{"id":648,"label":649,"issuer":650,"region":491,"url":651,"description":652,"useCases":374,"indexable":221},"au-scams-prevention-framework","Australian Scams Prevention Framework","Australian Treasury","https:\u002F\u002Ftreasury.gov.au\u002Fconsultation\u002Fc2024-573813","Economy wide obligations for banks, telcos and digital platforms to prevent, detect, disrupt and respond to scams.",{"id":654,"label":655,"issuer":157,"region":158,"url":656,"description":657,"useCases":374,"indexable":221},"eu-mar","EU Market Abuse Regulation","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2014\u002F596\u002Foj","Regulation (EU) 596\u002F2014: insider dealing and market manipulation, including the duty to detect and report suspicious orders and transactions.",{"id":659,"label":660,"issuer":490,"region":491,"url":661,"description":662,"useCases":374,"indexable":221},"mas-shared-responsibility-framework","MAS Shared Responsibility Framework","https:\u002F\u002Fwww.mas.gov.sg\u002Fregulation\u002Fguidelines\u002Fguidelines-on-shared-responsibility-framework","Singapore's framework that assigns banks and telcos duties and loss sharing for phishing scams.",{"id":664,"label":665,"issuer":666,"region":199,"url":667,"description":668,"useCases":374,"indexable":221},"nyc-local-law-144","NYC Local Law 144","New York City","https:\u002F\u002Fwww.nyc.gov\u002Fsite\u002Fdca\u002Fabout\u002Fautomated-employment-decision-tools.page","Bias audits and notices for automated employment decision tools used in hiring and promotion in New York City.",1792049859540]