[{"data":1,"prerenderedAt":753},["ShallowReactive",2],{"uc-flight-disruption-and-rebooking-agent":3,"uc-regulations":548},{"useCase":4,"evidence":222,"blitsAiDeployments":403,"benchmarks":404,"indicative":433,"related":436,"indexability":546,"includeUnpublished":228},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":17,"functions":19,"patterns":22,"channels":27,"audience":34,"autonomy":35,"adoptionStage":36,"problem":37,"problemStats":38,"howItWorks":39,"valueDrivers":40,"kpis":46,"indicativeValue":54,"macroEstimates":96,"feasibility":97,"implementation":112,"risk":159,"blitsAi":196,"faq":198,"related":211,"datePublished":217,"dateModified":217,"lastVerified":217,"changelog":218,"slug":221},"AI agent for flight disruption and rebooking","Flight disruption and rebooking","AI agents for flight disruption and rebooking","An AI agent that explains flight disruptions and lets passengers rebook or get a refund in one chat. Delta and Lufthansa Group already run rebooking agents.","published","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.",[12,13,14,15,16],"airline rebooking chatbot","irregular operations assistant","IROPS self service agent","flight cancellation assistant","airline disruption assistant",[18],"travel-and-hospitality",[20,21],"customer-service","operations",[23,24,25,26],"conversational-agent","voice-agent","agentic-workflow","content-generation",[28,29,30,31,32,33],"mobile-app","web-chat","sms","whatsapp","email","voice","customer-facing","supervised-agent","early-adopters","Disruption is when an airline's service is tested hardest. A storm, a strike or an air traffic\ncontrol restriction can cancel many flights at once, and large numbers of passengers then call,\nqueue at transfer desks and post on social media at the same time, most asking the same three questions:\nwhat happened, what are my options, and what am I entitled to. Contact centres are sized for a\nnormal day, so waiting times explode exactly when anxiety is highest, and the passengers who\nmost need a person (families, passengers with reduced mobility, long haul connections) wait\nbehind everyone else.\n\nMost of the work is rule bound. The airline already knows which passengers are affected, which\nalternative flights have seats, what the fare rules allow and, in many markets, what care and\ncompensation the law requires. First generation chatbots could only point to a web page. The\nstep change is an agent that is connected to the reservation and departure control systems, can\npresent and confirm real options, issue a refund or voucher, and explain the reason in plain\nlanguage, while staying inside the airline's reaccommodation policy and passenger rights rules.",[],"1. **Detect and notify.** When operations change a flight, the agent (or staff drafting with\n   AI, as at United) sends a message by app, SMS or email that explains what changed and why,\n   before the passenger has to ask.\n2. **Authenticate and load the trip.** The passenger opens the conversation from the message or\n   the app; the agent identifies the booking, the connections and the loyalty status, so nobody\n   has to search for a reservation.\n3. **Offer real options.** The agent pulls the airline's reaccommodation offer and alternatives\n   with confirmed seats, standby options, a refund or an eCredit, and explains the fare rules\n   and the care the passenger is entitled to (meals, hotel, transport).\n4. **Act through approved tools.** The passenger picks an option; the agent confirms the new\n   flight, issues the refund request, voucher or eCredit and shows where the bags are, through a\n   small allow list of reservation, ticketing and baggage actions.\n5. **Hand over well.** Complex itineraries, group bookings, passengers needing assistance, codeshare\n   and interline cases, and anyone who asks for a person go to a human agent with a summary and\n   the options already shown, so the passenger does not start again.",[41,42,43,44,45],"customer-experience","cost-to-serve","speed","employee-productivity","inclusion-and-access",[47,48,49,50,51,52,53],"containment-rate","automation-rate","interactions-handled","hours-saved","customer-satisfaction","customer-satisfaction-uplift","response-time-reduction",{"referenceOrg":55,"inputs":56,"formula":91,"currency":92,"period":93,"resultLabel":94,"caveat":95},"An airline carrying 20 million passengers a year",[57,63,70,77,84],{"key":58,"label":59,"low":60,"high":60,"unit":61,"note":62},"passengers","Passengers per year",20000000,"passengers per year","The reference airline.",{"key":64,"label":65,"low":66,"high":67,"unit":68,"note":69},"disruptedShare","Share of passengers whose trip is cancelled, misconnected or significantly delayed",0.02,0.05,"fraction of passengers","Editorial assumption; replace with your own irregular operations data.",{"key":71,"label":72,"low":73,"high":74,"unit":75,"note":76},"contactsPerDisrupted","Assisted contacts per disrupted passenger",0.5,1,"contacts per disrupted passenger","Editorial assumption; many passengers accept the automatic reaccommodation, others contact more than once.",{"key":78,"label":79,"low":80,"high":81,"unit":82,"note":83},"containment","Share of disruption contacts the agent resolves",0.2,0.45,"fraction of disruption contacts","This range sits at or below the 45% containment rate ASAPP reports for JetBlue's virtual agent across general digital support, because disruption contacts include complex itineraries that need a person. Air India's 97% figure is an automation rate for handled queries, a different metric, and is not used as a containment benchmark here.",{"key":85,"label":86,"low":87,"high":88,"unit":89,"note":90},"costPerContact","Cost of a human handled contact",4,8,"USD per contact","Editorial assumption for a blended phone and messaging contact. Replace with your own fully loaded cost.","passengers * disruptedShare * contactsPerDisrupted * containment * costPerContact","USD","per year","Human handled disruption contact cost avoided","Gross avoided contact cost only. It leaves out the cost of running the AI and the integrations, the revenue kept by rebooking passengers instead of refunding them, the care and compensation costs (which the agent does not change) and the effect on loyalty and complaints.",[],{"complexity":98,"complexityNote":99,"dataPrerequisites":100,"integrations":105},"high","Answering \"where is my flight\" is easy. Rebooking is not: the agent needs read and write access to the passenger service system, inventory, ticketing and EMD issuing, fare rules, the reaccommodation engine and the notification platform, plus the legal rules for care and compensation per market. It must also survive peak load on the worst day of the year.",[101,102,103,104],"Reaccommodation and waiver policies per disruption type, in a form the agent can apply","Passenger rights rules per market (care, refund, compensation) with an owner and review date","Real time flight status, delay reasons and the operational reaccommodation offer per passenger","A catalog of disruption contact reasons with volumes from past irregular operations days",[106,107,108,109,110,111],"Passenger service system and departure control (bookings, seats, standby lists)","Ticketing, refunds, eCredits and vouchers (EMDs), and the payment service for fare differences","Reaccommodation or disruption management engine","Notification platform (app push, SMS, email, messaging)","Baggage tracking","Contact centre platform for handover with conversation context, and CRM for loyalty status",{"steps":113,"guardrails":132,"humanInTheLoop":138,"kpisToInstrument":139,"failureModes":146},[114,117,120,123,126,129],{"title":115,"detail":116},"Start with information, then add actions","First ship proactive, accurate delay and cancellation messages with the reason and the next step. Measure how many calls they prevent. Add actions (accept the new flight, refund, eCredit, voucher) one by one, each with its own tests and sign off.",{"title":118,"detail":119},"Encode the rules, not just the knowledge","Put reaccommodation policy, waivers and passenger rights in deterministic rules or a flow that the agent calls, so the offer a passenger sees is the offer the policy allows. Let the language model explain the options, never invent them.",{"title":121,"detail":122},"Rehearse the worst day","Load test the agent, the integrations and the handover queue at the volume of your largest irregular operations day, including the reservation system's rate limits. An agent that fails under peak load is worse than none.",{"title":124,"detail":125},"Design the handover for disruption","Route complex itineraries, groups, unaccompanied minors, passengers needing assistance and codeshare or interline tickets to people, with a summary and the options already shown. Give the priority phone line to the cases the agent cannot solve.",{"title":127,"detail":128},"Close the loop with operations","Feed contact reasons and failed rebookings back to the operations control centre and the reaccommodation team, so the automatic offer improves and the agent stops getting the same question.",{"title":130,"detail":131},"Test before passengers do","Build test conversations per disruption type (weather, crew, technical, strike) and per market rule, including attempts to get a refund or compensation the rules do not allow, and run them on every change.",[133,134,135,136,137],"The agent only presents options returned by the reaccommodation engine and fare rules, never options it generates itself","Refunds, compensation and vouchers above set limits need a human approval","Entitlement statements (care, refund, compensation) come only from approved, dated policy content, with a refusal and handover when the content does not cover the case","Automatic handover for passengers needing assistance, groups, complaints and repeated failure","Payment card data tokenized before it reaches the model, and personal data masked in logs","Humans own the exceptions: complex itineraries, passengers with reduced mobility, groups, compensation disputes and complaints. The disruption desk watches live volumes and handover reasons during irregular operations, and a policy owner signs off every change to entitlement content and every new action before it goes live.",[140,141,142,143,144,145],"Share of disrupted passengers who rebook or accept an option without a human, per disruption type","Handover rate and handover reasons on irregular operations days","Repeat contacts within seven days on the same booking","Accuracy of entitlement answers on a weekly reviewed sample","Time from disruption notice to a confirmed new itinerary","Complaints and chargebacks that mention the assistant",[147,150,153,156],{"title":148,"detail":149},"Wrong entitlement answers","The agent promises a refund, compensation or discount the policy does not give, and the airline is held to it, as in the Air Canada tribunal case. Keep entitlement answers in approved content with an owner and review date, and hand over when unsure.",{"title":151,"detail":152},"Collapse under peak load","The agent or the reservation integration times out on the busiest day, and passengers are pushed back to a full phone queue. Load test, cache flight status and queue writes.",{"title":154,"detail":155},"Options that are not real","The agent shows flights that no longer have seats or that the fare rules do not allow, and rebooking fails at confirmation. Only show options from live inventory and confirm before telling the passenger they are rebooked.",{"title":157,"detail":158},"Containment that is really abandonment","Passengers give up and go to the airport desk or book another airline, which looks like containment. Count repeat contacts and measure satisfaction on disruption days separately.",{"euAiAct":160,"regulations":163,"guidance":169,"controls":185,"incidents":191},{"tier":161,"basis":162},"limited","A customer facing assistant must tell people they are interacting with AI (Article 50). It is not a high risk use under Annex III: it applies the airline's reaccommodation rules and does not decide on access to an essential public service or on creditworthiness.",[164,165,166,167,168],"eu-ai-act","gdpr","uk-gdpr","pci-dss","eu-accessibility-act",[170,176,180],{"title":171,"issuer":172,"region":173,"url":174,"note":175},"Article 50, transparency obligations for providers and deployers of certain AI systems","European Union","europe","https://artificialintelligenceact.eu/article/50/","Passengers must be informed that they are interacting with an AI system unless this is obvious from the context.",{"title":177,"issuer":172,"region":173,"url":178,"note":179},"Air passenger rights (Your Europe)","https://europa.eu/youreurope/citizens/travel/passenger-rights/air/index_en.htm","Summary of the EU rules on reimbursement, rerouting, care and compensation for cancelled, delayed and overbooked flights; the agent's entitlement answers must match them for flights in scope.",{"title":181,"issuer":182,"region":173,"url":183,"note":184},"Flight delays and cancellations","UK Civil Aviation Authority","https://www.caa.co.uk/air-passengers/travel-problems-and-rights/flight-delays-and-cancellations/","UK passenger rights guidance for delays and cancellations, the reference for entitlement content on UK flights.",[186,187,188,189,190],"AI disclosure at the start of every conversation and in AI drafted disruption messages where required","Entitlement and policy content versioned, owned and reviewed after every regulatory or policy change","Immutable audit trail of every rebooking, refund, voucher and eCredit the agent issued","Limits per action (refund value, voucher value, number of changes) with human approval above them","Peak load and failover plan for irregular operations days",[192],{"title":193,"url":194,"note":195},"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 chatbot's wrong statement about a bereavement fare refund (Moffatt v. Air Canada) and ordered it to pay damages. An airline cannot disclaim what its assistant tells passengers about refunds and entitlements.",{"howToBuild":197},"On Blits.ai this is an **AI agent** with **custom functions** that call the airline's\nreservation, reaccommodation, ticketing and baggage APIs, combined with a **knowledge base**\nthat holds only approved policy and passenger rights content, retrieved with hybrid search.\nThe rebooking and refund journeys run as **flows** with deterministic steps and an\nauthentication block, so the offer shown is the offer the rules allow; the agent explains the\noptions and answers open questions. **Agentic workflows** with **human in the loop** approval\nhandle refunds or vouchers above a threshold, and the **payment** service collects fare\ndifferences with card tokenization.\n\nThe same agent serves **web chat, WhatsApp, SMS and voice**, and the airline's own app through\nthe **API channel**, with\nstreaming speech on the phone for passengers who call. **Guardrails** and **PII masking** check\nevery turn, **human handover** passes the summary and the options already offered to the\ncontact centre, **test suites** replay disruption scenarios per market before every change, and\n**monitors** run scheduled health checks against the live agent. **Analytics** show\ninteractions, satisfaction and top intents per channel, custom dashboard widgets can track\nhandovers per disruption type, and the platform is model agnostic, with EU and UAE data\nresidency options.",[199,202,205,208],{"question":200,"answer":201},"What share of disruption contacts can an AI agent resolve?","No airline on this page publishes a rate for disruption contacts alone, and it depends on whether the agent can act. Across general digital support, ASAPP reports a 45% containment rate for JetBlue's virtual agent in May 2023, and Microsoft reports that 97% of nearly 4 million queries to Air India's AI.g were handled with full automation. Disruption days are harder than average, because more itineraries are complex, so plan for a lower rate and a strong handover.",{"question":203,"answer":204},"Can an airline be held to what its chatbot says?","Yes. In Moffatt v. Air Canada (2024) a Canadian tribunal held the airline responsible for its chatbot's wrong answer about a bereavement refund. Keep entitlement answers in approved, dated content and hand over when the content does not cover the case.",{"question":206,"answer":207},"Should the agent decide what a passenger is entitled to?","No. Care, refunds and compensation should come from the airline's rules engine and approved policy content, applied the same way to every passenger. The agent explains the options and completes the chosen one; disputes and exceptions go to a person.",{"question":209,"answer":210},"Is this only for airlines?","The public deployments on this page are airlines. The same pattern applies to rail and ferry operators and tour operators, wherever a disruption triggers mass rebooking and rule based entitlements.",[212,213,214,215,216],"travel-and-hotel-booking-concierge","travel-insurance-claims-and-assistance-agent","outbound-reminder-and-confirmation-agent","complaints-handling-agent","first-line-contact-centre-agent","2026-09-27",[219],{"date":217,"note":220},"First published","flight-disruption-and-rebooking-agent",[223,254,280,313,344,368],{"title":224,"useCases":225,"organization":226,"vendors":231,"summary":232,"stage":233,"year":234,"channels":235,"languages":236,"metrics":237,"outcomeDisclosed":228,"sources":238,"verification":248,"grade":251,"id":252,"organizationSlug":253},"Delta Air Lines: Delta Concierge AI assistant for disruptions, cancellations and bags",[221],{"name":227,"anonymized":228,"country":229,"region":230,"industry":18},"Delta Air Lines",false,"US","north-america",[],"Delta Concierge is an AI powered assistant inside the Delta app for SkyMiles Members. It authenticates the member, recognizes the nearest upcoming trip, explains what changed when a flight is disrupted and helps find alternative flights, cancels eligible flights and submits a refund request or issues an eCredit in real time, and summarizes bag status. It launched in beta to selected members from October 2025, was expanded in phases and became available to all SkyMiles Members in August 2026, with a handoff to Delta staff when it cannot help.","scaled",2025,[28],[],[],[239,244],{"url":240,"title":241,"publisher":242,"date":243},"https://news.delta.com/more-control-fewer-taps-delta-concierge-expands-all-skymiles-members","More control, fewer taps: Delta Concierge expands to all SkyMiles Members","Delta News Hub","2026-08-07",{"url":245,"title":246,"publisher":242,"date":247},"https://news.delta.com/smarter-journeys-start-here-delta-concierge-now-beta-rollout","Smarter journeys start here: Delta Concierge now in beta rollout","2025-10-29",{"level":249,"checkedAt":250},"source-verified","2026-09-26","B","delta-concierge-ai-assistant",null,{"title":255,"useCases":256,"organization":257,"vendors":259,"summary":260,"stage":233,"year":261,"channels":262,"languages":263,"metrics":264,"outcomeDisclosed":228,"sources":265,"verification":278,"grade":251,"id":279,"organizationSlug":253},"United Airlines: generative AI delay messages, automatic rebooking and ConnectionSaver",[221],{"name":258,"anonymized":228,"country":229,"region":230,"industry":18},"United Airlines",[],"Customer service teams in United's network operations centre use generative AI to review flight data and write the text and email messages that explain why a flight is delayed or changed, including links to live radar maps during weather delays. When a flight is delayed or cancelled, United's self service tools automatically present personalized rebooking options, bag tracking and meal and hotel vouchers when eligible. Its AI powered ConnectionSaver tool identifies departing flights that can be held for connecting customers without delaying the on time arrival of those already on board; United says it has saved more than 3.3 million customer connections since launching in 2019. That tool works on the operation, not in conversations with passengers.",2024,[30,32,28],[],[],[266,270,274],{"url":267,"title":268,"publisher":258,"date":269},"https://united.mediaroom.com/2024-07-03-United-Now-Texts-Live-Radar-Maps-and-Uses-AI-to-Keep-Travelers-Informed-During-Weather-Delays","United Now Texts Live Radar Maps and Uses AI to Keep Travelers Informed During Weather Delays","2024-07-03",{"url":271,"title":272,"publisher":258,"date":273},"https://united.mediaroom.com/2025-06-25-United-Mobile-App-Now-Gives-People-More-Information-About-Their-Connecting-Flight","United Mobile App Now Gives People More Information About Their Connecting Flight","2025-06-25",{"url":275,"title":276,"publisher":258,"date":277},"https://united.mediaroom.com/2025-12-16-United-Adds-New-Features-to-Award-Winning-Mobile-App-Like-Virtual-Gate,-Club-Recommendation-Tool-and-Real-Time-Bag-Tracker","United Adds New Features to Award-Winning Mobile App Like Virtual Gate, Club Recommendation Tool and Real-Time Bag Tracker","2025-12-16",{"level":249,"checkedAt":250},"united-airlines-disruption-messaging-and-rebooking",{"title":281,"useCases":282,"organization":283,"vendors":286,"summary":290,"stage":291,"year":234,"channels":292,"languages":293,"metrics":294,"outcomeDisclosed":302,"sources":303,"verification":310,"grade":311,"id":312,"organizationSlug":253},"Pegasus Airlines: FlyBot generative AI virtual assistant",[221,216],{"name":284,"anonymized":228,"country":285,"region":173,"industry":18},"Pegasus Airlines","TR",[287],{"name":288,"role":289},"Microsoft","platform","Pegasus Airlines retrained FlyBot, the virtual assistant on its website, with Azure OpenAI and integrated it with internal systems, so customers can ask about flights, flight rules, baggage allowances and claims and reissue tickets in the same conversation. The airline reports that satisfaction with the virtual assistant doubled after the change.","production",[29],[],[295],{"kpi":52,"value":296,"unit":297,"qualifier":298,"claimant":299,"quote":300,"sourceUrl":301},100,"percent","exact","organization","“Since we integrated Azure AI Services into our FlyBot, customer satisfaction rates for our virtual assistant have doubled,” points out Bora.","https://www.microsoft.com/en/customers/story/23194-pegasus-airlines-azure-ai-services",true,[304,306],{"url":301,"title":305,"publisher":288},"Pegasus Airlines transforms bookings and services with Azure OpenAI, doubling customer satisfaction scores",{"url":307,"title":308,"publisher":288,"date":309},"https://www.microsoft.com/en-us/microsoft-cloud/blog/2025/07/24/ai-powered-success-with-1000-stories-of-customer-transformation-and-innovation/","AI-powered success, with more than 1,000 stories of customer transformation and innovation","2025-07-24",{"level":249,"checkedAt":250},"C","pegasus-airlines-flybot-virtual-assistant",{"title":314,"useCases":315,"organization":316,"vendors":320,"summary":322,"stage":233,"year":323,"channels":324,"languages":325,"metrics":326,"outcomeDisclosed":302,"sources":339,"verification":342,"grade":311,"id":343,"organizationSlug":253},"Air India: AI.g generative AI virtual assistant",[221,216],{"name":317,"anonymized":228,"country":318,"region":319,"industry":18},"Air India","IN","asia-pacific",[321],{"name":288,"role":289},"Air India launched AI.g in May 2023, a virtual assistant on Azure OpenAI that is integrated with the reservation system and answers questions across 1,300 topic areas including bookings, flight status, baggage, check in, frequent flyer awards and lounge access, and escalates automatically to contact centre staff when it detects the need. The airline says it has kept contact centre call volume flat while its passenger count doubled.",2023,[29,28],[],[327,333],{"kpi":48,"value":328,"unit":297,"qualifier":298,"period":329,"claimant":330,"quote":331,"sourceUrl":332},97,"cumulative, of nearly 4 million queries","vendor","To date, AI.g has successfully handled nearly 4 million customer queries, 97% of them with full automation.","https://customers.microsoft.com/en-us/story/1836108400811529412-airindia-azure-ai-search-travel-and-transportation-en-india",{"kpi":49,"value":334,"unit":335,"qualifier":336,"period":337,"claimant":299,"quote":338,"sourceUrl":332},10000,"count","approximately","per day","That's because AI.g is handling about 10,000 a day.",[340],{"url":332,"title":341,"publisher":288},"Air India elevates customer support while saving money with Azure AI, data, and apps",{"level":249,"checkedAt":250},"air-india-aig-virtual-assistant",{"title":345,"useCases":346,"organization":347,"vendors":350,"summary":353,"stage":233,"year":354,"channels":355,"languages":356,"metrics":357,"outcomeDisclosed":302,"sources":362,"verification":366,"grade":311,"id":367,"organizationSlug":253},"Lufthansa Group: self service AI agents for rebookings, refunds and alternative flights",[221,216],{"name":348,"anonymized":228,"country":349,"region":173,"industry":18},"Lufthansa Group","DE",[351],{"name":352,"role":289},"Cognigy (NiCE)","During the pandemic, when passengers flooded call centres to change or cancel flights, Lufthansa Group replaced its in house chatbot with a conversational AI platform and built self service AI agents that manage rebookings, check alternative flights, give travel information and process refunds. The agents run on the airline websites and through SMS links that open a self service chat, with multilingual support and real time translation, and are used to absorb peaks such as strikes.",2020,[29,30],[],[358],{"kpi":49,"value":359,"unit":335,"qualifier":336,"period":93,"claimant":330,"quote":360,"sourceUrl":361},16000000,"By leveraging AI-driven Self-Service Agents, the airline managed to significantly increase its interaction capacity, handling about 16 million conversations throughout the year with AI, with peak days seeing up to 375,000 interactions.","https://www.cognigy.com/en/case-study/lufthansa",[363],{"url":361,"title":364,"publisher":365},"Lufthansa | NiCE Cognigy","Cognigy",{"level":249,"checkedAt":250},"lufthansa-group-self-service-ai-agents",{"title":369,"useCases":370,"organization":371,"vendors":373,"summary":376,"stage":233,"year":377,"channels":378,"languages":380,"metrics":383,"outcomeDisclosed":302,"sources":394,"verification":401,"grade":311,"id":402,"organizationSlug":253},"JetBlue: AI virtual agent and digital messaging support",[221,216],{"name":372,"anonymized":228,"country":229,"region":230,"industry":18},"JetBlue",[374],{"name":375,"role":289},"ASAPP","JetBlue moved its customer support to an AI platform from late 2019, opening messaging channels (Apple Messages for Business, Google Business Messaging, web and app chat, WhatsApp) with Spanish language support, a virtual agent that resolves routine requests and AI assistance for the crewmembers who handle the rest. In a January 2026 conference session published by the vendor, a JetBlue customer support leader described weather disruptions, when passengers ask for their options, and said the conversations crewmembers now handle (rebooking, refunds, alternatives weeks away) are multifaceted, which is why the airline has looked at AI that orchestrates several workflows. The ASAPP speaker in the same session warned against reading containment gains without checking whether customers still have the option to escalate.",2019,[29,28,31,379],"social-messaging",[381,382],"en","es",[384,389],{"kpi":47,"value":385,"unit":297,"qualifier":298,"period":386,"claimant":330,"quote":387,"sourceUrl":388},45,"May 2023, virtual agent","The integration of virtual agent experiences facilitated streamlined interactions and contributed to a remarkable 36% year-over-year growth in containment, with a 45% containment rate achieved in May 2023.","https://www.asapp.com/case-studies/jetblue",{"kpi":50,"value":390,"unit":391,"qualifier":298,"period":392,"claimant":330,"quote":393,"sourceUrl":388},73000,"hours","Q1 2023 only (one quarter, not annualized)","In Q1 2023 alone, this AI-driven efficiency translated into significant savings of 73,000 workforce hours.",[395,397],{"url":388,"title":396,"publisher":375},"ASAPP X JetBlue | ASAPP",{"url":398,"title":399,"publisher":375,"date":400},"https://www.asapp.com/blog/what-airlines-like-jetblue-teach-us-about-building-agentic-customer-experience","What airlines like JetBlue teach us about building agentic customer experience","2026-03-10",{"level":249,"checkedAt":250},"jetblue-asapp-digital-customer-support",0,[405,413,418,423,428],{"kpi":49,"label":406,"unit":335,"aggregate":228,"higherIsBetter":302,"n":407,"nUpTo":403,"median":408,"min":334,"max":359,"byClaimant":409,"vendorOnly":228,"points":410},"Interactions handled",2,8005000,{"organization":74,"vendor":74,"regulator":403,"independent":403},[411,412],{"evidenceId":367,"organization":348,"value":359,"qualifier":336,"claimant":330,"grade":311,"pooled":302},{"evidenceId":343,"organization":317,"value":334,"qualifier":336,"claimant":299,"grade":311,"pooled":302},{"kpi":48,"label":414,"unit":297,"aggregate":302,"higherIsBetter":302,"n":74,"nUpTo":403,"median":328,"min":328,"max":328,"byClaimant":415,"vendorOnly":302,"points":416},"Automation rate",{"organization":403,"vendor":74,"regulator":403,"independent":403},[417],{"evidenceId":343,"organization":317,"value":328,"qualifier":298,"claimant":330,"grade":311,"pooled":302},{"kpi":47,"label":419,"unit":297,"aggregate":302,"higherIsBetter":302,"n":74,"nUpTo":403,"median":385,"min":385,"max":385,"byClaimant":420,"vendorOnly":302,"points":421},"Containment rate",{"organization":403,"vendor":74,"regulator":403,"independent":403},[422],{"evidenceId":402,"organization":372,"value":385,"qualifier":298,"claimant":330,"grade":311,"pooled":302},{"kpi":50,"label":424,"unit":391,"aggregate":228,"higherIsBetter":302,"n":74,"nUpTo":403,"median":390,"min":390,"max":390,"byClaimant":425,"vendorOnly":302,"points":426},"Hours saved",{"organization":403,"vendor":74,"regulator":403,"independent":403},[427],{"evidenceId":402,"organization":372,"value":390,"qualifier":298,"claimant":330,"grade":311,"pooled":302},{"kpi":52,"label":429,"unit":297,"aggregate":302,"higherIsBetter":302,"n":74,"nUpTo":403,"median":296,"min":296,"max":296,"byClaimant":430,"vendorOnly":228,"points":431},"Satisfaction uplift",{"organization":74,"vendor":403,"regulator":403,"independent":403},[432],{"evidenceId":312,"organization":284,"value":296,"qualifier":298,"claimant":299,"grade":311,"pooled":302},{"low":434,"high":435},160000,3600000,[437,458,477,493,517],{"slug":212,"title":438,"shortTitle":439,"definition":440,"status":9,"industries":441,"functions":442,"patterns":444,"audience":34,"autonomy":35,"adoptionStage":36,"evidenceCount":447,"publicEvidenceCount":448,"organizations":449,"bestGrade":251,"headline":455,"lastVerified":250,"indexable":302},"AI travel and hotel booking concierge","Travel and hotel booking concierge","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.",[18],[443,20],"sales",[23,445,446,25],"recommendation-and-personalization","rag-knowledge-assistant",6,5,[450,451,452,453,454],"Airbnb","Booking.com","Holland America Line","Priceline","Trip.com",{"kpi":48,"label":414,"unit":297,"n":74,"nUpTo":403,"kind":456,"value":457,"qualifier":298,"claimant":299,"organization":451,"vendorReported":228},"reported",30,{"slug":213,"title":459,"shortTitle":460,"definition":461,"status":9,"industries":462,"functions":464,"patterns":466,"audience":34,"autonomy":35,"adoptionStage":469,"segment":465,"evidenceCount":470,"publicEvidenceCount":407,"organizations":471,"bestGrade":251,"headline":474,"lastVerified":217,"indexable":302},"AI agent for travel insurance claims and assistance","Travel insurance claims and assistance","An AI agent that helps insured travellers around the clock and in their own language: it answers cover questions, takes claims for delays, cancellations, lost baggage and medical costs, reads the receipts and certificates they upload, settles simple claims within set limits, and connects medical emergencies and complex cases to the assistance team at once.",[463,18],"insurance",[465,20],"claims",[23,24,467,25,468],"document-processing","translation","emerging",3,[472,473],"Allianz Partners","General Insurance Association of Singapore",{"kpi":48,"label":414,"unit":297,"n":403,"nUpTo":74,"kind":456,"value":475,"qualifier":476,"claimant":299,"organization":472,"vendorReported":228},70,"up-to",{"slug":214,"title":478,"shortTitle":479,"definition":480,"status":9,"industries":481,"functions":485,"patterns":486,"audience":34,"autonomy":35,"adoptionStage":36,"evidenceCount":448,"publicEvidenceCount":87,"organizations":488,"bestGrade":251,"headline":253,"lastVerified":250,"indexable":302},"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.",[482,483,484],"cross-industry","healthcare","government",[20,21],[24,23,25,487],"prediction-and-scoring",[489,490,491,492],"Sheffield Children's NHS Foundation Trust","University Hospitals Coventry and Warwickshire NHS Trust","U.S. Department of Veterans Affairs","WellSpan Health",{"slug":215,"title":494,"shortTitle":495,"definition":496,"status":9,"industries":497,"functions":501,"patterns":504,"audience":507,"autonomy":508,"adoptionStage":36,"segment":509,"evidenceCount":407,"publicEvidenceCount":407,"organizations":510,"bestGrade":251,"headline":513,"lastVerified":217,"indexable":302},"AI agent for complaints recognition, investigation and response","Complaints handling","An AI agent that recognizes when a customer interaction is a complaint, logs it against the regulatory definition, classifies its root cause and severity, gathers the evidence, drafts the acknowledgement and the response for a human handler to approve, and tracks every statutory deadline until the case is closed.",[482,498,499,463,500],"banking","payments","telecommunications",[502,20,503],"case-management","regulatory-compliance",[505,506,26,25,446],"classification-and-routing","summarization","employee-facing","copilot","middle-office",[511,512],"Lloyds Banking Group","NatWest Group",{"kpi":514,"label":515,"unit":516,"n":74,"nUpTo":403,"kind":456,"value":448,"qualifier":336,"claimant":299,"organization":511,"vendorReported":228},"time-saved-per-task","Time saved per task","minutes",{"slug":216,"title":518,"shortTitle":519,"definition":520,"status":9,"industries":521,"functions":524,"patterns":525,"audience":34,"autonomy":35,"adoptionStage":526,"segment":527,"evidenceCount":528,"publicEvidenceCount":529,"organizations":530,"bestGrade":251,"headline":542,"lastVerified":217,"indexable":302},"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.",[482,498,499,500,18,522,523],"retail-and-ecommerce","wealth-and-asset-management",[20],[23,24,446,505],"mainstream","front-office",25,18,[317,450,531,532,533,534,535,372,536,348,537,512,284,538,539,540,541],"Bank of America","Bank of the Philippine Islands","BT Group","Commonwealth Bank of Australia","Ingka Group","Klarna","Mobily","Telkomsel","Together Credit Union","Vodafone Germany","Vodafone",{"kpi":47,"label":419,"unit":297,"n":543,"nUpTo":403,"kind":544,"value":545,"qualifier":298,"claimant":253,"organization":253,"vendorReported":228},7,"median",47,{"indexable":302,"reasons":547},[],[549,554,559,567,574,580,586,592,599,605,611,617,624,631,637,642,649,654,660,666,672,678,684,689,694,701,707,712,717,724,730,736,742,747],{"id":164,"label":550,"issuer":172,"region":173,"url":551,"description":552,"useCases":553,"indexable":302},"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":165,"label":555,"issuer":172,"region":173,"url":556,"description":557,"useCases":558,"indexable":302},"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":560,"label":561,"issuer":562,"region":563,"url":564,"description":565,"useCases":566,"indexable":302},"iso-42001","ISO/IEC 42001","ISO and IEC","global","https://www.iso.org/standard/81230.html","The international management system standard for AI.",110,{"id":568,"label":569,"issuer":570,"region":230,"url":571,"description":572,"useCases":573,"indexable":302},"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":575,"label":576,"issuer":172,"region":173,"url":577,"description":578,"useCases":579,"indexable":302},"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":166,"label":581,"issuer":582,"region":173,"url":583,"description":584,"useCases":585,"indexable":302},"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":587,"label":588,"issuer":589,"region":173,"url":590,"description":591,"useCases":545,"indexable":302},"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":593,"label":594,"issuer":595,"region":319,"url":596,"description":597,"useCases":598,"indexable":302},"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":600,"label":601,"issuer":602,"region":319,"url":603,"description":604,"useCases":528,"indexable":302},"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":167,"label":606,"issuer":607,"region":563,"url":608,"description":609,"useCases":610,"indexable":302},"PCI DSS","PCI Security Standards Council","https://www.pcisecuritystandards.org/","Security standard for any system that stores, processes or transmits cardholder data.",20,{"id":612,"label":613,"issuer":614,"region":230,"url":615,"description":616,"useCases":610,"indexable":302},"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":618,"label":619,"issuer":620,"region":173,"url":621,"description":622,"useCases":623,"indexable":302},"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.",16,{"id":625,"label":626,"issuer":627,"region":563,"url":628,"description":629,"useCases":630,"indexable":302},"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":632,"label":633,"issuer":172,"region":173,"url":634,"description":635,"useCases":636,"indexable":302},"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":638,"label":639,"issuer":172,"region":173,"url":640,"description":641,"useCases":636,"indexable":302},"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":643,"label":644,"issuer":645,"region":230,"url":646,"description":647,"useCases":648,"indexable":302},"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":168,"label":650,"issuer":172,"region":173,"url":651,"description":652,"useCases":653,"indexable":302},"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":655,"label":656,"issuer":657,"region":230,"url":658,"description":659,"useCases":653,"indexable":302},"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":661,"label":662,"issuer":663,"region":563,"url":664,"description":665,"useCases":653,"indexable":302},"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":667,"label":668,"issuer":172,"region":173,"url":669,"description":670,"useCases":671,"indexable":302},"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":673,"label":674,"issuer":675,"region":230,"url":676,"description":677,"useCases":671,"indexable":302},"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":679,"label":680,"issuer":595,"region":319,"url":681,"description":682,"useCases":683,"indexable":302},"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.",10,{"id":685,"label":686,"issuer":172,"region":173,"url":687,"description":688,"useCases":683,"indexable":302},"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":690,"label":691,"issuer":172,"region":173,"url":692,"description":693,"useCases":683,"indexable":302},"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":695,"label":696,"issuer":697,"region":173,"url":698,"description":699,"useCases":700,"indexable":302},"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":702,"label":703,"issuer":704,"region":230,"url":705,"description":706,"useCases":88,"indexable":302},"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":708,"label":709,"issuer":172,"region":173,"url":710,"description":711,"useCases":88,"indexable":302},"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":713,"label":714,"issuer":172,"region":173,"url":715,"description":716,"useCases":447,"indexable":302},"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":718,"label":719,"issuer":720,"region":721,"url":722,"description":723,"useCases":448,"indexable":302},"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":725,"label":726,"issuer":727,"region":173,"url":728,"description":729,"useCases":87,"indexable":302},"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":731,"label":732,"issuer":733,"region":173,"url":734,"description":735,"useCases":87,"indexable":302},"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":737,"label":738,"issuer":739,"region":319,"url":740,"description":741,"useCases":470,"indexable":302},"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":743,"label":744,"issuer":172,"region":173,"url":745,"description":746,"useCases":470,"indexable":302},"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":748,"label":749,"issuer":750,"region":230,"url":751,"description":752,"useCases":470,"indexable":302},"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.",1790598294907]