[{"data":1,"prerenderedAt":701},["ShallowReactive",2],{"uc-travel-and-hotel-booking-concierge":3,"uc-regulations":498},{"useCase":4,"evidence":207,"blitsAiDeployments":361,"benchmarks":362,"indicative":384,"related":387,"indexability":496,"includeUnpublished":213},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":17,"functions":19,"patterns":22,"channels":27,"audience":32,"autonomy":33,"adoptionStage":34,"problem":35,"problemStats":36,"howItWorks":37,"valueDrivers":38,"kpis":43,"indicativeValue":51,"macroEstimates":86,"feasibility":87,"implementation":101,"risk":147,"blitsAi":183,"faq":185,"related":195,"datePublished":201,"dateModified":201,"lastVerified":202,"changelog":203,"slug":206},"AI travel and hotel booking concierge","Travel and hotel booking concierge","AI assistants for travel and hotel booking","An AI travel concierge searches live inventory, answers booking questions and handles changes. Airbnb resolves nearly 45% of its assistant's issues without a human.","published","A customer facing AI assistant that turns an open travel question into a concrete trip by searching live inventory for flights, hotels, rentals, cruises and activities, comparing options and answering questions about the property and the booking, then completes or hands off the booking and supports the traveller with changes and questions before and during the stay.",[12,13,14,15,16],"AI trip planner","AI travel assistant","hotel booking chatbot","travel concierge chatbot","virtual travel agent",[18],"travel-and-hospitality",[20,21],"sales","customer-service",[23,24,25,26],"conversational-agent","recommendation-and-personalization","rag-knowledge-assistant","agentic-workflow",[28,29,30,31],"mobile-app","web-chat","whatsapp","voice","customer-facing","supervised-agent","early-adopters","Planning a trip means comparing many options. Traditional online travel search, as Priceline\ndescribes it, requires navigating filters, tabs and separate browser windows. Search boxes work\nwhen the traveller already knows the destination and dates; they fail at the questions people\nactually have (\"where is warm in February with a direct flight\", \"which of these hotels is quiet\nand walkable\", \"can we bring the dog\"). On the service side, the same pre and post booking\nquestions come back again and again: when Booking.com widened access to its Booking Assistant\nservice chatbot in 2017, it listed payment, transportation, arrival and departure times, date\nchanges, cancellations, parking, extra beds, pet policies and WiFi among the most frequently asked\ntopics.\n\nA concierge that only chats about destinations adds little. The value comes when the assistant\nis grounded in live prices and availability, in the operator's own property content and\npolicies, and in the traveller's booking, so it can recommend, answer precisely, book or change,\nand hand the conversation to a human agent or the property when needed. Several companies on\nthis page, among them Priceline, Trip.com and Holland America Line, run one assistant for both\nplanning and service.",[],"1. **Understand the trip.** The assistant asks for or infers the essentials (who travels, dates\n   or flexibility, budget, what matters) in the traveller's own words and language.\n2. **Search live inventory.** It queries the booking engine or supplier APIs for flights, hotels,\n   rentals, cruises and activities with current prices and availability, never prices from\n   memory.\n3. **Compare and explain.** It shortlists options and explains the tradeoffs from property\n   content, reviews and policies, with links to each listing.\n4. **Book or hand off.** It builds the basket and passes the traveller to checkout, or books\n   within set limits, and hands group, complex or high value requests to a human travel agent.\n5. **Support the trip.** After booking, the same assistant answers questions about the\n   reservation, makes changes and cancellations within the policy, passes requests to the\n   property and hands complaints and exceptions to a person with the context.",[39,40,41,42],"revenue-growth","customer-experience","cost-to-serve","inclusion-and-access",[44,45,46,47,48,49,50],"containment-rate","automation-rate","cost-reduction","time-saved-per-task","conversion-rate-uplift","customer-satisfaction","users-served",{"referenceOrg":52,"inputs":53,"formula":81,"currency":82,"period":83,"resultLabel":84,"caveat":85},"An online travel company or hotel group with 2 million bookings a year",[54,60,67,74],{"key":55,"label":56,"low":57,"high":57,"unit":58,"note":59},"bookings","Bookings per year",2000000,"bookings per year","The reference organization.",{"key":61,"label":62,"low":63,"high":64,"unit":65,"note":66},"contactsPerBooking","Assisted service contacts per booking",0.2,0.4,"contacts per booking","Editorial assumption for pre and post booking questions and changes. Replace with your own contact rate.",{"key":68,"label":69,"low":70,"high":71,"unit":72,"note":73},"containment","Share of service contacts the assistant resolves",0.3,0.45,"fraction of contacts","The high end matches the benchmark on this page (Airbnb reports nearly 45% of issues that begin with its AI assistant resolved without a human agent in Q2 2026); the low end allows for a first year.",{"key":75,"label":76,"low":77,"high":78,"unit":79,"note":80},"costPerContact","Cost of a human handled contact",4,8,"USD per contact","Editorial assumption for a blended chat and phone contact. Replace with your own fully loaded cost.","bookings * contactsPerBooking * containment * costPerContact","USD","per year","Human handled service contact cost avoided","Service cost only. It leaves out the revenue effect of better conversion (the most important and least published benefit), the cost of running the AI and the integrations, and any change in cancellations or complaints.",[],{"complexity":88,"complexityNote":89,"dataPrerequisites":90,"integrations":95},"medium","A planning chatbot on public content is quick to build. A concierge that quotes real prices, books and changes reservations needs live access to inventory, pricing and the booking system, authentication for post booking changes, and strict rules so it never states a price or policy it did not retrieve.",[91,92,93,94],"Live availability and pricing through the booking engine or supplier APIs","Structured property, cabin or room content (amenities, accessibility, parking, pets) with an owner","Booking, change and cancellation policies per rate and product","Contact reasons and search logs to choose the first intents",[96,97,98,99,100],"Booking engine, central reservation system or GDS and supplier APIs","Customer account and loyalty system for authentication and personalization","Payment service for checkout, deposits and change fees","Property management system or messaging to pass requests to the hotel or host","Contact centre platform for handover with the conversation context",{"steps":102,"guardrails":121,"humanInTheLoop":127,"kpisToInstrument":128,"failureModes":134},[103,106,109,112,115,118],{"title":104,"detail":105},"Start where the booking already exists","Post booking questions (parking, check in times, what is included, change a date) are frequent, well defined and measurable. Launch there first, prove containment and satisfaction, then move up the funnel into planning and search.",{"title":107,"detail":108},"Ground every price and fact","Let the assistant quote prices, availability and policies only from live tool calls and approved content, and show where the answer came from. A fluent but invented price or policy costs more than no answer.",{"title":110,"detail":111},"Keep checkout deterministic","Let the model build the basket, but run payment, terms acceptance and confirmation in a fixed flow, with the price and cancellation conditions shown exactly as the booking engine returns them.",{"title":113,"detail":114},"Roll out in waves","Follow the Holland America Line pattern: internal agents first, then employees, then a small share of website visitors, widening only when resolution and satisfaction hold.",{"title":116,"detail":117},"Measure revenue, not just deflection","Run the assistant against a control group and measure conversion, basket value and cancellations, not only contained conversations. Priceline reports higher conversion and fewer support contacts for Penny users, Trip.com reports growth in orders assisted by TripGenie, and Airbnb reports service effects only.",{"title":119,"detail":120},"Test before travellers do","Keep a regression set of planning and service conversations per market and language, including requests for prices the rate does not allow and attempts to change someone else's booking, and run it on every change.",[122,123,124,125,126],"Prices, availability and policies only from live tool results and approved content, never from the model's memory","Authentication before showing or changing a booking; changes only through an allow list of actions with limits","Checkout, payment and terms acceptance in a deterministic flow with card data tokenized","Handover for complaints, accessibility needs, groups and high value or complex itineraries","Recommendations free of undisclosed paid placement, with sponsored results labelled","Human travel agents handle complex, group and high value trips, complaints and exceptions to policy. A content owner approves property and policy content, and a team reviews a weekly sample of conversations for wrong prices, wrong policies and unfair recommendations.",[129,130,131,132,133],"Conversion and basket value for assistant users versus a control group","Containment on post booking contacts, counting repeat contacts within seven days as not contained","Share of answers with a price or policy that did not match the booking engine, on a sampled review","Handover rate and reasons","Customer satisfaction on assistant conversations versus human handled ones",[135,138,141,144],{"title":136,"detail":137},"Invented prices and policies","The assistant states a price, fee or refund rule from memory, and the company is held responsible for it, as in the Air Canada tribunal case. Retrieve every fact and refuse when retrieval finds nothing.",{"title":139,"detail":140},"A planner nobody books from","Engagement grows but conversion does not, because the assistant is not connected to live inventory and checkout. Measure bookings, not conversations.",{"title":142,"detail":143},"Steering that breaks consumer law","Recommendations favour higher commission options without disclosure, or hide fees until checkout. Label sponsored results and show the full price early.",{"title":145,"detail":146},"Handover without context","The traveller has to repeat the trip details to a human agent. Pass the summary, the booking and the options already shown.",{"euAiAct":148,"regulations":151,"guidance":156,"controls":172,"incidents":178},{"tier":149,"basis":150},"limited","A customer facing assistant must tell people they are interacting with AI unless that is obvious from the context (Article 50(1), applicable from 2 August 2026). Recommending and booking travel is not listed in Annex III, so it is not high risk; consumer protection law on price transparency and fair commercial practices still applies to what it says.",[152,153,154,155],"eu-ai-act","gdpr","pci-dss","eu-accessibility-act",[157,163,167],{"title":158,"issuer":159,"region":160,"url":161,"note":162},"Article 50, transparency obligations for providers and deployers of certain AI systems","European Union","europe","https://artificialintelligenceact.eu/article/50/","Travellers must be informed that they are interacting with an AI system unless this is obvious from the context.",{"title":164,"issuer":159,"region":160,"url":165,"note":166},"Package travel, package holidays and linked travel arrangements in the EU (Your Europe)","https://europa.eu/youreurope/citizens/travel/holidays/package-travel/index_en.htm","When an assistant combines flights, hotels and other services, the combination can become a package or linked travel arrangement with information duties and traveller rights.",{"title":168,"issuer":169,"region":160,"url":170,"note":171},"Unfair commercial practices directive","European Commission","https://commission.europa.eu/law/law-topic/consumer-protection-law/unfair-commercial-practices-law/unfair-commercial-practices-directive_en","Rules against misleading information and practices, relevant to how an assistant presents prices, fees, rankings and sponsored results.",[173,174,175,176,177],"AI disclosure at the start of every conversation","Price and policy statements logged with the tool result they came from","Versioned property and policy content with an owner and review date","Labelling of sponsored or commission based recommendations","Change control and regression tests for every new market, language or action",[179],{"title":180,"url":181,"note":182},"Incident 639: Air Canada Chatbot Reportedly Provides Inaccurate Bereavement Fare Information, Leading to Customer Overpayment","https://incidentdatabase.ai/cite/639/","A Canadian small claims tribunal held Air Canada responsible in 2024 for its website chatbot's wrong statement about bereavement fare eligibility and ordered it to pay damages, rejecting the argument that the chatbot was a separate legal entity. A company can be held responsible for what its assistant says about fares and refund rules.",{"howToBuild":184},"On Blits.ai this is an **AI agent** with **custom functions** that call the booking engine,\navailability and pricing APIs and the reservation system, and a **knowledge base** with\nproperty, room and policy content retrieved with hybrid search. **SQL knowledge bases** can\nhold structured property attributes for precise filtering. Checkout and booking changes run as\n**flows** with deterministic steps, and the **payment** service sends payment links with card\ntokenization; the agent recommends and explains, and **rich cards** for flights and hotels show\nthe options in the chat.\n\nThe same agent serves **web chat, WhatsApp and voice**, reaches a mobile app through the REST or\nWebSocket API channel, and can run as a **digital human** streamed to a browser, for example on\na lobby screen. It detects the traveller's language and answers in it. **Guardrails** and **PII\nmasking** check every turn, **human handover** passes the trip and the conversation to a travel\nagent, and **test suites** replay planning and service conversations per market before every\nchange. **Analytics** show interactions, satisfaction and sentiment per channel, conversation\nlogs show why travellers were handed over, and the platform is model agnostic.",[186,189,192],{"question":187,"answer":188},"Do AI travel assistants actually increase bookings?","Some operators report it, few publish numbers. Trip.com says TripGenie assisted order volume grew about 400% year on year, and Priceline says Penny users show higher conversion in early testing without giving a figure. Measure conversion against a control group before claiming revenue.",{"question":190,"answer":191},"How much service volume can the assistant take?","Airbnb reports that nearly 45% of issues that begin with its AI assistant were resolved without a human agent in Q2 2026, and that support cost per booking fell about 16% year on year, partly because of the assistant. Priceline estimates Penny users saved nearly ten minutes per trip compared with calling support.",{"question":193,"answer":194},"Should the assistant book on its own?","It can build the basket and handle simple changes within limits, but payment, terms and confirmation should run in a fixed flow with the exact price and conditions from the booking engine. Complex, group and high value trips belong with a human agent.",[196,197,198,199,200],"flight-disruption-and-rebooking-agent","conversational-shopping-assistant","personalized-marketing-at-scale","outbound-reminder-and-confirmation-agent","first-line-contact-centre-agent","2026-09-27","2026-09-26",[204],{"date":201,"note":205},"First published","travel-and-hotel-booking-concierge",[208,251,289,316,337],{"title":209,"useCases":210,"organization":211,"vendors":216,"summary":226,"stage":227,"year":228,"channels":229,"languages":230,"metrics":231,"outcomeDisclosed":240,"sources":241,"verification":246,"grade":248,"id":249,"organizationSlug":250},"Priceline: Penny agentic AI travel assistant",[206],{"name":212,"anonymized":213,"country":214,"region":215,"industry":18},"Priceline",false,"US","north-america",[217,220,222,224],{"name":218,"role":219},"Anthropic","model-provider",{"name":221,"role":219},"Google Cloud",{"name":223,"role":219},"OpenAI",{"name":212,"role":225},"in-house","Priceline put its AI assistant Penny in front of customers first at checkout and in customer care. In June 2026 it announced a fully agentic version that takes a trip idea, compares hotels, flights and rental cars on a live map with real time inventory and deals, and books without leaving the conversation. Penny runs as more than ten specialized agents on Priceline's own AI stack, with Claude models for conversational reasoning and planning, and Google Cloud and OpenAI supporting search and voice capabilities.","production",2026,[28,29],[],[232],{"kpi":47,"value":233,"unit":234,"qualifier":235,"period":236,"claimant":237,"quote":238,"sourceUrl":239},10,"minutes","approximately","per trip, Penny users versus customers who called support","organization","Priceline has estimated that travelers who used Penny saved an average of nearly ten minutes per trip compared with those who called customer support.","https://press.priceline.com/pricelines-penny-goes-fully-agentic/",true,[242],{"url":239,"title":243,"publisher":244,"date":245},"Priceline's Penny Goes Fully Agentic","Priceline Press Center","2026-06-03",{"level":247,"checkedAt":202},"source-verified","B","priceline-penny-agentic-travel-assistant",null,{"title":252,"useCases":253,"organization":254,"vendors":257,"summary":258,"stage":259,"year":260,"channels":261,"languages":262,"metrics":263,"outcomeDisclosed":240,"sources":275,"verification":287,"grade":248,"id":288,"organizationSlug":250},"Airbnb: AI assistant for guest and host support",[206,200],{"name":255,"anonymized":213,"country":214,"region":256,"industry":18},"Airbnb","global",[],"Airbnb runs an AI assistant as the first line of customer support for guests and hosts. It was expanded to all US users in 2025 and then rolled out to more countries and languages, reaching more than 50 languages by mid 2026. Airbnb reports the share of issues resolved without a human agent in each quarterly letter and links part of the fall in support cost per booking to the assistant; it plans an AI voice assistant.","scaled",2025,[28,29],[],[264,270],{"kpi":44,"value":265,"unit":266,"qualifier":235,"period":267,"claimant":237,"quote":268,"sourceUrl":269},45,"percent","Q2 2026, issues that begin with the AI assistant","Nearly 45 percent of issues that begin with our AI assistant are now resolved without a human agent, up from Q1, while delivering much faster resolution times.","https://news.airbnb.com/airbnb-q2-2026-financial-results/",{"kpi":46,"value":271,"unit":266,"qualifier":235,"period":272,"baseline":273,"claimant":237,"quote":274,"sourceUrl":269},16,"Q2 2026 year on year, customer support cost per booking","Q2 2025","In Q2, our customer support related cost per booking declined approximately 16 percent year-over-year, driven in part by improvements to our AI assistant.",[276,279,283],{"url":269,"title":277,"publisher":255,"date":278},"Airbnb Q2 2026 financial results","2026-08-06",{"url":280,"title":281,"publisher":255,"date":282},"https://news.airbnb.com/airbnb-q1-2026-financial-results/","Airbnb Q1 2026 financial results","2026-05-07",{"url":284,"title":285,"publisher":255,"date":286},"https://news.airbnb.com/airbnb-q2-2025-financial-results/","Airbnb Q2 2025 financial results","2025-08-06",{"level":247,"checkedAt":202},"airbnb-ai-customer-support-assistant",{"title":290,"useCases":291,"organization":292,"vendors":295,"summary":296,"stage":227,"year":260,"channels":297,"languages":298,"metrics":299,"outcomeDisclosed":240,"sources":306,"verification":314,"grade":248,"id":315,"organizationSlug":250},"Booking.com: AI Trip Support, AI Voice Support and AI Trip Planner",[206],{"name":293,"anonymized":213,"country":294,"region":256,"industry":18},"Booking.com","NL",[],"Booking.com has moved from a standalone AI Trip Planner to AI features embedded across the booking journey. AI Trip Support is a first point of contact around the clock that answers questions about a property (for example parking) and helps travellers change reservations, with a handover to a human for complex cases. AI Voice Support lets travellers manage or cancel a booking by phone in their own words, and connects to a human agent with the context when needed. An earlier generation, the Booking Assistant chatbot, answered stay related questions from 2017.",[28,29,31],[],[300],{"kpi":45,"value":301,"unit":266,"qualifier":302,"period":303,"claimant":237,"quote":304,"sourceUrl":305},30,"exact","December 2017, pilot version of the earlier generation Booking Assistant, English language bookings","The chatbot can currently respond to 30% of customers’ stay-related questions automatically in less than 5 minutes.","https://news.booking.com/bookingcom-expands-global-access-to-the-booking-assistant/",[307,311],{"url":308,"title":309,"publisher":293,"date":310},"https://news.booking.com/bookingcom-debuts-agentic-ai-innovations-adding-to-its-robust-suite-of-genai-tools-for-customers/","Booking.com Debuts Agentic AI Innovations, Adding to its Robust Suite of GenAI Tools for Customers","2025-10-09",{"url":305,"title":312,"publisher":293,"date":313},"Booking.com Expands Global Access to the Booking Assistant","2017-12-12",{"level":247,"checkedAt":202},"booking-com-ai-trip-support-and-voice",{"title":317,"useCases":318,"organization":319,"vendors":323,"summary":324,"stage":259,"year":325,"channels":326,"languages":327,"metrics":328,"outcomeDisclosed":213,"sources":329,"verification":335,"grade":248,"id":336,"organizationSlug":250},"Trip.com: TripGenie AI travel assistant",[206],{"name":320,"anonymized":213,"country":321,"region":322,"industry":18},"Trip.com","SG","asia-pacific",[],"TripGenie is the AI travel assistant in the Trip.com app and website. It helps travellers find inspiration, compare hotels and book hotels, flights and attractions, answers pre and post sales service questions, and during the trip offers menu help, live translation and questions about images. After three years of use, Trip.com reports that nearly 60% of TripGenie interactions are booking related, that service questions are about a quarter of interactions, and that TripGenie assisted order volume grew by around 400% year on year.",2023,[28,29],[],[],[330],{"url":331,"title":332,"publisher":333,"date":334},"https://www.prnewswire.com/news-releases/three-years-of-tripgenie-how-travellers-around-the-world-are-using-ai-differently-302713190.html","Three Years of TripGenie: How Travellers Around the World are Using AI Differently","Trip.com via PR Newswire","2026-03-15",{"level":247,"checkedAt":202},"trip-com-tripgenie-ai-travel-assistant",{"title":338,"useCases":339,"organization":340,"vendors":342,"summary":347,"stage":227,"year":348,"channels":349,"languages":350,"metrics":352,"outcomeDisclosed":213,"sources":353,"verification":358,"grade":359,"id":360,"organizationSlug":250},"Holland America Line: Anna digital concierge for cruise guests and travel advisors",[206],{"name":341,"anonymized":213,"country":214,"region":215,"industry":18},"Holland America Line",[343,346],{"name":344,"role":345},"Microsoft","platform",{"name":223,"role":219},"Holland America Line built Anna, a generative AI digital concierge on its website for new and existing cruise guests and the travel advisors who book for them. The first release supports booking new cruises, adding products and services to existing bookings and general questions, and connects to the CRM and reservation data. It was rolled out in waves (contact centre agents, employees, then 5%, 50% and 100% of website visitors) and runs in the United States, with more markets and languages planned.",2024,[29],[351],"en",[],[354],{"url":355,"title":356,"publisher":344,"archivedUrl":357},"https://www.microsoft.com/en/customers/story/19787-holland-america-dataverse","Holland America Line sees signs of more informed purchasing with Copilot Studio agent | Microsoft Customer Stories","https://web.archive.org/web/20250119055636/https://www.microsoft.com/en/customers/story/19787-holland-america-dataverse",{"level":247,"checkedAt":202},"C","holland-america-line-anna-digital-concierge",1,[363,369,374,379],{"kpi":45,"label":364,"unit":266,"aggregate":240,"higherIsBetter":240,"n":361,"nUpTo":365,"median":301,"min":301,"max":301,"byClaimant":366,"vendorOnly":213,"points":367},"Automation rate",0,{"organization":361,"vendor":365,"regulator":365,"independent":365},[368],{"evidenceId":315,"organization":293,"value":301,"qualifier":302,"claimant":237,"grade":248,"pooled":240},{"kpi":44,"label":370,"unit":266,"aggregate":240,"higherIsBetter":240,"n":361,"nUpTo":365,"median":265,"min":265,"max":265,"byClaimant":371,"vendorOnly":213,"points":372},"Containment rate",{"organization":361,"vendor":365,"regulator":365,"independent":365},[373],{"evidenceId":288,"organization":255,"value":265,"qualifier":235,"claimant":237,"grade":248,"pooled":240},{"kpi":46,"label":375,"unit":266,"aggregate":240,"higherIsBetter":240,"n":361,"nUpTo":365,"median":271,"min":271,"max":271,"byClaimant":376,"vendorOnly":213,"points":377},"Cost reduction",{"organization":361,"vendor":365,"regulator":365,"independent":365},[378],{"evidenceId":288,"organization":255,"value":271,"qualifier":235,"claimant":237,"grade":248,"pooled":240},{"kpi":47,"label":380,"unit":234,"aggregate":240,"higherIsBetter":240,"n":361,"nUpTo":365,"median":233,"min":233,"max":233,"byClaimant":381,"vendorOnly":213,"points":382},"Time saved per task",{"organization":361,"vendor":365,"regulator":365,"independent":365},[383],{"evidenceId":249,"organization":212,"value":233,"qualifier":235,"claimant":237,"grade":248,"pooled":240},{"low":385,"high":386},480000,2880000,[388,410,432,453,467],{"slug":196,"title":389,"shortTitle":390,"definition":391,"status":9,"industries":392,"functions":393,"patterns":395,"audience":32,"autonomy":33,"adoptionStage":34,"evidenceCount":398,"publicEvidenceCount":398,"organizations":399,"bestGrade":248,"headline":406,"lastVerified":201,"indexable":240},"AI agent for flight disruption and rebooking","Flight disruption and rebooking","An AI agent that tells passengers proactively when their flight is delayed, cancelled or misconnected, explains why, and lets them rebook, request a refund or voucher, or claim care such as meals and hotels in one conversation on app, messaging, web or phone, within the airline's reaccommodation rules and passenger rights, handing complex itineraries and upset customers to a human with the context attached.",[18],[21,394],"operations",[23,396,26,397],"voice-agent","content-generation",6,[400,401,402,403,404,405],"Air India","Delta Air Lines","JetBlue","Lufthansa Group","Pegasus Airlines","United Airlines",{"kpi":45,"label":364,"unit":266,"n":361,"nUpTo":365,"kind":407,"value":408,"qualifier":302,"claimant":409,"organization":400,"vendorReported":240},"reported",97,"vendor",{"slug":197,"title":411,"shortTitle":412,"definition":413,"status":9,"industries":414,"functions":417,"patterns":419,"audience":32,"autonomy":420,"adoptionStage":34,"evidenceCount":233,"publicEvidenceCount":421,"organizations":422,"bestGrade":248,"headline":428,"lastVerified":201,"indexable":240},"AI shopping assistant for product discovery and recommendations","Conversational shopping assistant","A conversational assistant on a retailer's site or app that answers product questions, compares items and recommends products from the retailer's own catalog for a need, project or occasion described in the shopper's own words, grounded in product data, reviews and stock, and hands the shopper to a basket, a store or a human expert.",[415,416],"cross-industry","retail-and-ecommerce",[20,418,21],"marketing",[23,24,25,26],"autonomous",5,[423,424,425,426,427],"Amazon","Lowe's","Sun & Ski Sports","Walmart","Zalando",{"kpi":48,"label":429,"unit":430,"n":361,"nUpTo":365,"kind":407,"value":431,"qualifier":302,"claimant":409,"organization":425,"vendorReported":240},"Conversion uplift","multiplier",3,{"slug":198,"title":433,"shortTitle":434,"definition":435,"status":9,"industries":436,"functions":439,"patterns":440,"audience":442,"autonomy":33,"adoptionStage":443,"evidenceCount":78,"publicEvidenceCount":444,"organizations":445,"bestGrade":248,"headline":452,"lastVerified":201,"indexable":240},"AI marketing personalization at scale","Marketing personalization at scale","AI that runs marketing campaigns at the level of the individual: it decides for each customer which product, offer, message or content to show next across email, app, web and paid media, and generates the matching copy and creative variants within brand and compliance rules. It is the marketing team's engine across many campaigns and channels, not an agent that converses with the customer.",[415,18,437,416,438],"media-and-entertainment","banking",[418,20],[24,441,397],"prediction-and-scoring","back-office","mainstream",7,[423,446,447,448,449,450,451],"Catchtable","Commonwealth Bank of Australia","Radisson Hotel Group","Square Enix","Swarovski","Virgin Voyages",{"kpi":48,"label":429,"unit":266,"n":361,"nUpTo":365,"kind":407,"value":301,"qualifier":302,"claimant":409,"organization":446,"vendorReported":240},{"slug":199,"title":454,"shortTitle":455,"definition":456,"status":9,"industries":457,"functions":460,"patterns":461,"audience":32,"autonomy":33,"adoptionStage":34,"evidenceCount":421,"publicEvidenceCount":77,"organizations":462,"bestGrade":248,"headline":250,"lastVerified":202,"indexable":240},"AI agent for outbound reminders and confirmations by voice and messaging","Outbound reminders and confirmations","An AI agent that contacts customers about something they already booked or ordered (an appointment, a delivery, a reservation or a service visit) to remind them, confirm attendance and let them cancel or move it in the same conversation, by phone, SMS, WhatsApp or email. It is operational service outreach, not marketing: nothing is sold, and success is measured in kept appointments and reused slots, not in conversion.",[415,458,459],"healthcare","government",[21,394],[396,23,26,441],[463,464,465,466],"Sheffield Children's NHS Foundation Trust","University Hospitals Coventry and Warwickshire NHS Trust","U.S. Department of Veterans Affairs","WellSpan Health",{"slug":200,"title":468,"shortTitle":469,"definition":470,"status":9,"industries":471,"functions":475,"patterns":476,"audience":32,"autonomy":33,"adoptionStage":443,"segment":478,"evidenceCount":479,"publicEvidenceCount":480,"organizations":481,"bestGrade":248,"headline":493,"lastVerified":201,"indexable":240},"AI agent for first line contact centre service","First line contact centre","An AI agent that answers the first line of inbound customer contact on phone, chat and messaging, resolves general and routine questions end to end in the customer's own language, and routes everything complex, sensitive or regulated to the right human team with the context attached.",[415,438,472,473,18,416,474],"payments","telecommunications","wealth-and-asset-management",[21],[23,396,25,477],"classification-and-routing","front-office",25,18,[400,255,482,483,484,447,485,402,486,403,487,488,404,489,490,491,492],"Bank of America","Bank of the Philippine Islands","BT Group","Ingka Group","Klarna","Mobily","NatWest Group","Telkomsel","Together Credit Union","Vodafone Germany","Vodafone",{"kpi":44,"label":370,"unit":266,"n":444,"nUpTo":365,"kind":494,"value":495,"qualifier":302,"claimant":250,"organization":250,"vendorReported":213},"median",47,{"indexable":240,"reasons":497},[],[499,504,509,516,523,529,536,542,549,555,561,567,573,580,586,591,598,603,609,615,621,627,632,637,642,649,655,660,665,672,678,684,690,695],{"id":152,"label":500,"issuer":159,"region":160,"url":501,"description":502,"useCases":503,"indexable":240},"EU AI Act","https://eur-lex.europa.eu/eli/reg/2024/1689/oj","Regulation (EU) 2024/1689: risk based rules for AI systems, with obligations for high risk systems listed in Annex III and transparency duties under Article 50.",197,{"id":153,"label":505,"issuer":159,"region":160,"url":506,"description":507,"useCases":508,"indexable":240},"GDPR","https://eur-lex.europa.eu/eli/reg/2016/679/oj","General Data Protection Regulation, including Article 22 on decisions based solely on automated processing.",180,{"id":510,"label":511,"issuer":512,"region":256,"url":513,"description":514,"useCases":515,"indexable":240},"iso-42001","ISO/IEC 42001","ISO and IEC","https://www.iso.org/standard/81230.html","The international management system standard for AI.",110,{"id":517,"label":518,"issuer":519,"region":215,"url":520,"description":521,"useCases":522,"indexable":240},"nist-ai-rmf","NIST AI Risk Management Framework","NIST","https://www.nist.gov/itl/ai-risk-management-framework","Voluntary US framework to map, measure, manage and govern AI risk, with a generative AI profile.",83,{"id":524,"label":525,"issuer":159,"region":160,"url":526,"description":527,"useCases":528,"indexable":240},"dora","DORA","https://eur-lex.europa.eu/eli/reg/2022/2554/oj","Digital Operational Resilience Act for financial entities: ICT risk, incident reporting and third party risk, including AI providers.",66,{"id":530,"label":531,"issuer":532,"region":160,"url":533,"description":534,"useCases":535,"indexable":240},"uk-gdpr","UK GDPR","Information Commissioner's Office","https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/","The UK's version of the GDPR, including rules on solely automated decisions.",64,{"id":537,"label":538,"issuer":539,"region":160,"url":540,"description":541,"useCases":495,"indexable":240},"uk-consumer-duty","FCA Consumer Duty","Financial Conduct Authority","https://www.fca.org.uk/firms/consumer-duty","UK rules that require firms to deliver good outcomes for retail customers, including through automated channels.",{"id":543,"label":544,"issuer":545,"region":322,"url":546,"description":547,"useCases":548,"indexable":240},"mas-ai-risk-management","MAS AI risk management guidelines","Monetary Authority of Singapore","https://www.mas.gov.sg/news/media-releases/2025/mas-guidelines-for-artificial-intelligence-risk-management","Singapore's supervisory expectations for AI risk management at financial institutions, building on the FEAT principles.",36,{"id":550,"label":551,"issuer":552,"region":322,"url":553,"description":554,"useCases":479,"indexable":240},"apra-cps-230","APRA CPS 230","Australian Prudential Regulation Authority","https://www.apra.gov.au/operational-risk-management","Australian operational risk standard covering critical operations and material service providers.",{"id":154,"label":556,"issuer":557,"region":256,"url":558,"description":559,"useCases":560,"indexable":240},"PCI DSS","PCI Security Standards Council","https://www.pcisecuritystandards.org/","Security standard for any system that stores, processes or transmits cardholder data.",20,{"id":562,"label":563,"issuer":564,"region":215,"url":565,"description":566,"useCases":560,"indexable":240},"us-sr-11-7","SR 11-7 model risk management","Federal Reserve and OCC","https://www.federalreserve.gov/boarddocs/srletters/2011/sr1107.htm","US supervisory guidance on model risk management, applied by banks to AI and machine learning models.",{"id":568,"label":569,"issuer":570,"region":160,"url":571,"description":572,"useCases":271,"indexable":240},"uk-atrs","UK Algorithmic Transparency Recording Standard","UK Government","https://www.gov.uk/government/collections/algorithmic-transparency-recording-standard-hub","Mandatory transparency records for algorithmic tools used by UK central government.",{"id":574,"label":575,"issuer":576,"region":256,"url":577,"description":578,"useCases":579,"indexable":240},"fatf-recommendations","FATF Recommendations","Financial Action Task Force","https://www.fatf-gafi.org/en/publications/Fatfrecommendations/Fatf-recommendations.html","Global standards for anti money laundering and counter terrorist financing that national rules implement.",15,{"id":581,"label":582,"issuer":159,"region":160,"url":583,"description":584,"useCases":585,"indexable":240},"eu-amlr","EU Anti Money Laundering Regulation","https://eur-lex.europa.eu/eli/reg/2024/1624/oj","Regulation (EU) 2024/1624: the single EU rulebook for customer due diligence, beneficial ownership and suspicious transaction reporting.",14,{"id":587,"label":588,"issuer":159,"region":160,"url":589,"description":590,"useCases":585,"indexable":240},"nis2","NIS2 Directive","https://eur-lex.europa.eu/eli/dir/2022/2555/oj","Directive (EU) 2022/2555 on cybersecurity for essential and important entities, including telecom networks, energy and public administration.",{"id":592,"label":593,"issuer":594,"region":215,"url":595,"description":596,"useCases":597,"indexable":240},"us-bsa","Bank Secrecy Act","FinCEN","https://www.fincen.gov/resources/statutes-and-regulations/bank-secrecy-act","US anti money laundering law: customer due diligence, suspicious activity reports and record keeping.",13,{"id":155,"label":599,"issuer":159,"region":160,"url":600,"description":601,"useCases":602,"indexable":240},"European Accessibility Act","https://eur-lex.europa.eu/eli/dir/2019/882/oj","Directive (EU) 2019/882: accessibility requirements for banking services, ecommerce and other digital services, applicable since June 2025.",12,{"id":604,"label":605,"issuer":606,"region":215,"url":607,"description":608,"useCases":602,"indexable":240},"hipaa","HIPAA","US Department of Health and Human Services","https://www.hhs.gov/hipaa/index.html","US rules for the privacy and security of protected health information.",{"id":610,"label":611,"issuer":612,"region":256,"url":613,"description":614,"useCases":602,"indexable":240},"telecom-consumer-rules","Telecom consumer protection rules","National telecom regulators","https://www.berec.europa.eu/","National rules on telecom contracts, switching, billing disputes and marketing consent.",{"id":616,"label":617,"issuer":159,"region":160,"url":618,"description":619,"useCases":620,"indexable":240},"eecc","European Electronic Communications Code","https://eur-lex.europa.eu/eli/dir/2018/1972/oj","Directive (EU) 2018/1972: consumer protection, contract, switching and security rules for telecom operators.",11,{"id":622,"label":623,"issuer":624,"region":215,"url":625,"description":626,"useCases":620,"indexable":240},"us-tcpa","Telephone Consumer Protection Act","Federal Communications Commission","https://www.fcc.gov/consumers/guides/stop-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":628,"label":629,"issuer":545,"region":322,"url":630,"description":631,"useCases":233,"indexable":240},"mas-notice-626","MAS Notice 626","https://www.mas.gov.sg/regulation/notices/notice-626","Singapore's anti money laundering and counter terrorism financing requirements for banks.",{"id":633,"label":634,"issuer":159,"region":160,"url":635,"description":636,"useCases":233,"indexable":240},"mifid-ii","MiFID II","https://eur-lex.europa.eu/eli/dir/2014/65/oj","Directive 2014/65/EU on markets in financial instruments: suitability and appropriateness of advice, record keeping and product governance.",{"id":638,"label":639,"issuer":159,"region":160,"url":640,"description":641,"useCases":233,"indexable":240},"eu-psd2","PSD2","https://eur-lex.europa.eu/eli/dir/2015/2366/oj","Payment Services Directive 2: strong customer authentication, transaction risk analysis exemptions and open banking access.",{"id":643,"label":644,"issuer":645,"region":160,"url":646,"description":647,"useCases":648,"indexable":240},"eba-loan-origination","EBA Guidelines on loan origination and monitoring","European Banking Authority","https://www.eba.europa.eu/regulation-and-policy/credit-risk/guidelines-on-loan-origination-and-monitoring","Expectations for credit decisioning, including the use of automated models.",9,{"id":650,"label":651,"issuer":652,"region":215,"url":653,"description":654,"useCases":78,"indexable":240},"us-ecoa-reg-b","ECOA and Regulation B","Consumer Financial Protection Bureau","https://www.consumerfinance.gov/rules-policy/regulations/1002/9/","US fair lending rules, including specific reasons in adverse action notices, which also apply when credit decisions use AI models.",{"id":656,"label":657,"issuer":159,"region":160,"url":658,"description":659,"useCases":78,"indexable":240},"solvency-ii","Solvency II","https://eur-lex.europa.eu/eli/dir/2009/138/oj","Directive 2009/138/EC: risk based capital, governance and model requirements for insurers.",{"id":661,"label":662,"issuer":159,"region":160,"url":663,"description":664,"useCases":398,"indexable":240},"eu-idd","Insurance Distribution Directive","https://eur-lex.europa.eu/eli/dir/2016/97/oj","Directive (EU) 2016/97: conduct rules for selling insurance, including demands and needs testing and advice.",{"id":666,"label":667,"issuer":668,"region":669,"url":670,"description":671,"useCases":421,"indexable":240},"cbuae-ai-guidance","CBUAE guidance on AI and ML","Central Bank of the UAE","middle-east","https://www.centralbank.ae/","UAE central bank expectations for the enabling technologies, AI and machine learning used by licensed financial institutions.",{"id":673,"label":674,"issuer":675,"region":160,"url":676,"description":677,"useCases":77,"indexable":240},"pra-ss1-23","PRA SS1/23 model risk management","Prudential Regulation Authority","https://www.bankofengland.co.uk/prudential-regulation/publication/2023/may/model-risk-management-principles-for-banks-ss","UK model risk management principles for banks, covering AI and machine learning models.",{"id":679,"label":680,"issuer":681,"region":160,"url":682,"description":683,"useCases":77,"indexable":240},"uk-psr-app-reimbursement","UK APP scam reimbursement rules","Payment Systems Regulator","https://www.psr.org.uk/our-work/app-scams/","Mandatory reimbursement of authorised push payment scam victims by UK payment firms, which shifts scam losses onto banks.",{"id":685,"label":686,"issuer":687,"region":322,"url":688,"description":689,"useCases":431,"indexable":240},"au-scams-prevention-framework","Australian Scams Prevention Framework","Australian Treasury","https://treasury.gov.au/consultation/c2024-573813","Economy wide obligations for banks, telcos and digital platforms to prevent, detect, disrupt and respond to scams.",{"id":691,"label":692,"issuer":159,"region":160,"url":693,"description":694,"useCases":431,"indexable":240},"eu-mar","EU Market Abuse Regulation","https://eur-lex.europa.eu/eli/reg/2014/596/oj","Regulation (EU) 596/2014: insider dealing and market manipulation, including the duty to detect and report suspicious orders and transactions.",{"id":696,"label":697,"issuer":698,"region":215,"url":699,"description":700,"useCases":431,"indexable":240},"us-fcra","Fair Credit Reporting Act","Federal Trade Commission","https://www.ftc.gov/legal-library/browse/statutes/fair-credit-reporting-act","US rules on consumer reports, their accuracy and permissible use, relevant to credit scoring and screening.",1790598306864]