[{"data":1,"prerenderedAt":625},["ShallowReactive",2],{"uc-ai-visitor-and-tour-guide":3,"uc-regulations":417},{"useCase":4,"evidence":206,"blitsAiDeployments":317,"benchmarks":318,"indicative":319,"related":322,"indexability":415,"includeUnpublished":212},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":17,"functions":21,"patterns":25,"channels":31,"audience":38,"autonomy":39,"adoptionStage":40,"problem":41,"problemStats":42,"howItWorks":48,"valueDrivers":49,"kpis":54,"indicativeValue":59,"macroEstimates":92,"feasibility":93,"implementation":108,"risk":154,"blitsAi":180,"faq":182,"related":195,"datePublished":200,"dateModified":200,"lastVerified":201,"changelog":202,"slug":205},"AI visitor and tour guide for cities, museums and events","Visitor and tour guide","AI tour guides for museums, cities and events","An AI guide tells visitors the story behind each artwork or place in their own language. See how National Gallery Singapore and Art Basel use one.","published","A location and context aware AI guide, often spoken, that tells visitors of cities, museums, heritage sites and events the stories behind what is around them and answers their questions in their own language, grounded in the organization's curated content and in the visitor's position or the object they scan.",[12,13,14,15,16],"AI tour guide","AI museum guide","AI docent","AI audio guide","virtual city guide",[18,19,20],"travel-and-hospitality","media-and-entertainment","government",[22,23,24],"customer-service","marketing","knowledge-management",[26,27,28,29,30],"rag-knowledge-assistant","conversational-agent","voice-agent","computer-vision","translation",[32,33,34,35,36,37],"mobile-app","web-chat","whatsapp","voice","kiosk","digital-human","customer-facing","autonomous","early-adopters","Museums, heritage sites, cities and events hold far more knowledge than a visitor ever sees. Wall\nlabels are short, recorded audio guides cover a fixed route in a handful of languages, and human\nguides are limited by schedules, group sizes and the languages they speak. Visitors who are\ncurious but not experts, who speak another language, or who cannot read small print or see the\nobject well get the thinnest experience. National Gallery Singapore puts it plainly: people\nwalking into a museum often feel lost or intimidated.\n\nUpdating guide content is slow as well. Every new exhibition, route or audience (children,\nspecialists, first time visitors) means rewriting and rerecording the same stories. Tourism\nboards face the same problem at city scale, with visitor questions arriving in dozens of languages\nand outside office hours. A generative guide changes the unit of work: curators maintain one body\nof approved content, and the guide tells it in the visitor's language, at the visitor's level,\nabout the thing in front of them.",[43],{"statement":44,"sourceTitle":45,"sourceUrl":46,"year":47},"UN Tourism estimates that 1.52 billion international tourists were recorded worldwide in 2025, almost 60 million more than in 2024.","UN Tourism World Tourism Barometer","https://www.unwto.org/un-tourism-world-tourism-barometer-data",2026,"1. **Know where the visitor is.** The guide receives context with each question: the room or\n   stop, a GPS position, a QR code or object number, or a photo of the artwork that is matched\n   against the collection (Art Basel's Lens returns artist and gallery details in about two\n   seconds).\n2. **Retrieve approved content.** It looks up the object or place in the collection database or\n   points of interest list and retrieves the curated texts, research and practical information\n   (opening hours, accessibility, routes) that belong to it.\n3. **Tell the story in the visitor's terms.** The model turns that content into a short spoken or\n   written answer in the visitor's language and at their level, and can connect it to interests the\n   visitor mentions, as National Gallery Singapore's G(ai)le does with pop culture references.\n4. **Answer follow up questions.** Visitors ask in their own words, by voice or text; the guide\n   stays within the approved content and says so when it does not know.\n5. **Suggest what next.** It recommends the next stop, event or exhibit based on the visitor's\n   position, time and interests.\n6. **Feed insight back.** Anonymized questions show curators and marketing teams what visitors\n   actually want to know, and where the content has gaps.",[50,51,52,53],"customer-experience","inclusion-and-access","revenue-growth","employee-productivity",[55,56,57,58],"users-served","interactions-handled","customer-satisfaction","accuracy",{"referenceOrg":60,"inputs":61,"formula":87,"currency":88,"period":89,"resultLabel":90,"caveat":91},"A city museum with 1 million visitors a year and a guided route of about 150 stops",[62,68,74,80],{"key":63,"label":64,"low":65,"high":66,"unit":63,"note":67},"stops","Stops or objects with guide content",100,200,"Editorial assumption for a medium sized museum or city route. Replace with your own.",{"key":69,"label":70,"low":71,"high":72,"unit":69,"note":73},"languages","Additional languages offered",4,8,"Editorial assumption. For comparison, National Gallery Singapore's guide supports four languages in total. Replace with your own visitor language mix.",{"key":75,"label":76,"low":65,"high":77,"unit":78,"note":79},"costPerStopLanguage","Cost to write, translate and record one stop in one language",250,"USD per stop per language","Editorial assumption for professional translation and voice recording. Replace with your own agency rates.",{"key":81,"label":82,"low":83,"high":84,"unit":85,"note":86},"refreshShare","Share of stops rewritten or added each year",0.25,0.5,"fraction of stops per year","Editorial assumption covering new exhibitions, rotations and audience versions.","stops * languages * costPerStopLanguage * refreshShare","USD","per year","Multilingual guide content production cost avoided","Counts only the avoided cost of writing, translating and recording guide content in extra languages. It leaves out the cost of running the AI and curating the source content, any revenue from longer visits, return visits or bookings, and the accessibility benefit, which is the main reason many institutions build a guide.",[],{"complexity":94,"complexityNote":95,"dataPrerequisites":96,"integrations":102},"medium","The conversation is the easy part. The work is in the content: a clean collection or points of interest database with identifiers, approved texts per object, rights to use images and research, and a reliable way to know where the visitor is (QR codes, beacons, GPS or image matching). Spoken delivery in a noisy hall and accurate recognition of local names and accents need testing on site.",[97,98,99,100,101],"A collection management or points of interest database with stable identifiers per object or place","Approved, curated texts per object or place, with an owner and a review date","Practical visitor information (opening hours, routes, accessibility, events) from one source","A pronunciation list of names of artists, places and local terms for speech recognition and synthesis","For image recognition, reference photos of each object and the rights to use them",[103,104,105,106,107],"Collection management system or content management system","The organization's visitor app, website or kiosk software","Positioning (GPS, beacons, QR codes) or an image matching service","Ticketing and events calendar for recommendations and practical questions","Analytics for anonymized question and usage reporting",{"steps":109,"guardrails":128,"humanInTheLoop":134,"kpisToInstrument":135,"failureModes":141},[110,113,116,119,122,125],{"title":111,"detail":112},"Start from the content, not the model","Pick one gallery, route or district and bring its content into shape: an identifier per object or place, the approved texts, practical information and a short brief on tone. The quality of the guide will never exceed the quality of this content.",{"title":114,"detail":115},"Decide how the guide knows where the visitor is","QR codes or object numbers are the most reliable and cheapest. Image matching needs no codes on the wall, but it needs reference photos and tests in real lighting and angles; GPS works outdoors but not between rooms. Many deployments use two methods with a fallback.",{"title":117,"detail":118},"Write the voice of the guide","Agree with curators how the guide speaks, what it may interpret and what it must leave open. National Gallery Singapore spent a long time tuning prompts so its docent informs without imposing a single view of the art.",{"title":120,"detail":121},"Test with real visitors and real languages","Build a test set of questions per stop in every supported language, including names that are hard to pronounce and questions the content cannot answer, and run it on every content or model change. Then run a pilot on the floor and listen to what visitors ask.",{"title":123,"detail":124},"Design for access from day one","Offer audio only and large text modes, captions for spoken replies, and a way to use the guide without looking at the screen. These features serve visually impaired visitors and everyone who wants to look at the object rather than a phone.",{"title":126,"detail":127},"Close the loop with curators","Review anonymized questions every month: frequent questions without a good answer become new content, and questions that show confusion feed back into labels and routes.",[129,130,131,132,133],"Answers only from the approved collection and visitor content, with a clear \"I do not know\" when the content is silent","Facts such as dates, attributions and prices are taken from the source record, never generated","Clear disclosure that the guide is an AI, and a way to reach staff for practical or safety questions","No identification of people in camera images; image matching limited to objects in the collection","Location and conversation data kept only as long as needed, anonymized for analytics","Curators and educators own the content and the tone of the guide, approve new stories before they go live, and review a sample of conversations each month for errors of fact and tone. Front of house staff handle anything practical the guide cannot, such as lost items, accessibility assistance and safety.",[136,137,138,139,140],"Share of visitors who use the guide, by language and entry point","Questions per session and share answered from content versus declined","Factual accuracy on a monthly sample reviewed by curators","Visitor satisfaction with the guide compared with the recorded audio guide or human tour","Speech recognition errors on names and local terms, per language",[142,145,148,151],{"title":143,"detail":144},"Confident but wrong stories","The guide invents a date, an attribution or an anecdote that sounds right. Prevent with retrieval from approved records, facts taken from structured fields and curator review of samples.",{"title":146,"detail":147},"Wrong object, wrong story","Image matching or positioning picks the neighbouring object and the guide tells the wrong story. Set a confidence threshold and ask the visitor to confirm or scan the code when unsure.",{"title":149,"detail":150},"A screen between visitor and art","Visitors stare at their phones instead of the object. Design audio first and short answers, as National Gallery Singapore did with its \"eyes up\" mode.",{"title":152,"detail":153},"Stale practical information","Opening hours, closed rooms or event times in the guide differ from reality. Pull practical information from one live source instead of copying it into the content.",{"euAiAct":155,"regulations":158,"guidance":161,"controls":173,"incidents":179},{"tier":156,"basis":157},"limited","A visitor facing assistant must make clear that people are interacting with AI (Article 50), and synthetic speech should be identifiable as AI generated. It is not high risk. It would change if the camera feature were used to identify or categorise visitors by biometric data, which a guide does not need: remote biometric identification, biometric categorisation and emotion recognition are high risk under Annex III point 1, and biometric categorisation that infers sensitive traits is prohibited under Article 5.",[159,160],"eu-ai-act","gdpr",[162,168],{"title":163,"issuer":164,"region":165,"url":166,"note":167},"Article 50, transparency obligations for providers and deployers of certain AI systems","European Union","europe","https://artificialintelligenceact.eu/article/50/","People must be informed that they are interacting with an AI system, and providers of systems that generate synthetic audio must mark it in a machine readable format as artificially generated.",{"title":169,"issuer":170,"region":165,"url":171,"note":172},"Guidelines 02/2021 on virtual voice assistants","European Data Protection Board","https://www.edpb.europa.eu/our-work-tools/our-documents/guidelines/guidelines-022021-virtual-voice-assistants_en","How GDPR applies to voice assistants, including transparency, purpose limitation and retention of voice recordings.",[174,175,176,177,178],"AI disclosure at the start of every session and on spoken replies","Content ownership per object or place, with review dates and a change log","Test set per stop and language, run before every content or model change","Data protection impact assessment covering location data, voice and camera images","Retention limits and anonymization for conversation logs used in analytics",[],{"howToBuild":181},"On Blits.ai the guide is an **AI agent** grounded in a **knowledge base** built from the\ncurated texts, documents and crawled pages of the organization, retrieved with hybrid search,\nplus a **SQL knowledge base** with the collection or points of interest records (identifier,\ntitle, location, opening hours). The organization's own app sends the visitor's stop, position\nor scanned object number with each message through the **REST or WebSocket API channel**, and\n**custom functions** call the collection system, ticketing or events calendar for live details.\n\nThe same agent runs in the embeddable **web chat**, **WhatsApp** and a **digital human** on a\nkiosk, and speaks through **text to speech** from many providers with custom voices, with **TTS\ncaching** so fixed stop narration plays instantly. **Multi language** support detects the\nvisitor's language and switches mid conversation. **Guardrails** keep answers inside the\napproved content, **analytics** show what visitors ask, **test suites** replay\nquestions per stop before each change, and the platform is **model agnostic**, with **EU and UAE\ndata residency**.",[183,186,189,192],{"question":184,"answer":185},"Does an AI guide replace human guides and docents?","In the deployments on this page, no. National Gallery Singapore describes its AI docent as a new teammate alongside the tours team, and uses it to draft tour versions that staff refine. The Gallery notes that in person tours are not always available in the language a visitor prefers, which is where the guide helps.",{"question":187,"answer":188},"How does the guide know which object or place the visitor means?","Through context sent with each question: a QR code or object number, GPS outdoors, or image recognition. Art Basel matches a photo of an artwork against its index and returns the artist and gallery in about two seconds. Codes are the most reliable; image matching needs reference photos and a confidence threshold.",{"question":190,"answer":191},"How do you stop the guide from making up facts about the collection?","Ground every answer in approved records, take hard facts such as dates and attributions from structured fields, make the guide say when the content is silent, and have curators review a sample of conversations every month.",{"question":193,"answer":194},"Is an AI tour guide high risk under the EU AI Act?","Not as described here. It carries the Article 50 transparency duties: visitors must know it is an AI, and synthetic speech must be identifiable. Location, voice and camera data still fall under the GDPR, so a data protection impact assessment is advisable. Using the camera to identify or categorise visitors would change the assessment.",[196,197,198,199],"travel-and-hotel-booking-concierge","citizen-information-assistant","public-service-translation","retail-store-and-kiosk-assistant","2026-09-27","2026-09-26",[203],{"date":200,"note":204},"First published","ai-visitor-and-tour-guide",[207,242,269,291],{"title":208,"useCases":209,"organization":210,"vendors":215,"summary":224,"stage":225,"year":226,"channels":227,"languages":228,"metrics":230,"outcomeDisclosed":212,"sources":231,"verification":237,"grade":239,"id":240,"organizationSlug":241},"Art Basel: AI companion and Art Basel Lens artwork recognition for fair visitors",[205],{"name":211,"anonymized":212,"country":213,"region":214,"industry":19},"Art Basel",false,"CH","global",[216,219,222],{"name":217,"role":218},"Microsoft (Azure AI Foundry, Azure OpenAI)","platform",{"name":220,"role":221},"UIC Digital","integrator",{"name":223,"role":221},"Valorem Reply","Art Basel's Companion app combines a conversational AI companion, grounded in gallery, artwork, dining and lodging information for its fairs in five cities, with the Art Basel Lens: a visitor photographs an artwork and receives artist and gallery details in about two seconds, matched by image embeddings against a vector index. Art Basel reports more engagement, return visits and time in the app, without publishing figures, and is exploring wayfinding and restaurant bookings.","production",2025,[32],[229],"en",[],[232],{"url":233,"title":234,"publisher":235,"date":236},"https://www.microsoft.com/en/customers/story/24324-art-basel-azure-ai-foundry","Art Basel bridges physical and digital worlds, drives engagement with Azure AI Foundry","Microsoft Customer Stories","2025-06-06",{"level":238,"checkedAt":201},"source-verified","C","art-basel-companion-app-and-lens",null,{"title":243,"useCases":244,"organization":245,"vendors":249,"summary":255,"stage":225,"year":226,"channels":256,"languages":257,"metrics":261,"outcomeDisclosed":212,"sources":262,"verification":267,"grade":239,"id":268,"organizationSlug":241},"National Gallery Singapore: G(ai)le AI docent for museum visitors",[205],{"name":246,"anonymized":212,"country":247,"region":248,"industry":20},"National Gallery Singapore","SG","asia-pacific",[250,253],{"name":251,"role":252},"Microsoft (Azure OpenAI)","model-provider",{"name":254,"role":221},"NCS","National Gallery Singapore built G(ai)le, an AI docent that searches the Gallery's archives and explains artworks to visitors in conversational language, in English, Mandarin, Malay and Tamil. It adapts its stories to interests a visitor mentions, offers an audio only mode and an \"eyes up\" mode, and gives the Gallery a view of what visitors ask about. Staff also use it to draft versions of tour content for different audiences, which writers then refine.",[],[229,258,259,260],"zh","ms","ta",[],[263],{"url":264,"title":265,"publisher":235,"date":266},"https://www.microsoft.com/en/customers/story/24629-national-gallery-singapore-azure-openai","National Gallery Singapore’s new virtual guide lets visitors engage with art in new ways, powered by Azure OpenAI","2025-07-04",{"level":238,"checkedAt":201},"national-gallery-singapore-gaile-ai-docent",{"title":270,"useCases":271,"organization":272,"vendors":275,"summary":278,"stage":225,"year":279,"channels":280,"languages":281,"metrics":282,"outcomeDisclosed":212,"sources":283,"verification":289,"grade":239,"id":290,"organizationSlug":241},"Bloomberg Connects: museum audio guides created with Gemini",[205],{"name":273,"anonymized":212,"country":274,"region":214,"industry":19},"Bloomberg Connects","US",[276],{"name":277,"role":252},"Google Cloud (Gemini)","Bloomberg Connects uses Gemini to help create immersive audio guides, with the stated aim of making museums more accessible to visually impaired visitors. Google Cloud's listing gives no detail on scale, languages or results.",2024,[32],[],[],[284],{"url":285,"title":286,"publisher":287,"date":288},"https://cloud.google.com/transform/101-real-world-generative-ai-use-cases-from-industry-leaders","Real world gen AI use cases from the world's leading organizations","Google Cloud","2024-04-12",{"level":238,"checkedAt":201},"bloomberg-connects-gemini-audio-guides",{"title":292,"useCases":293,"organization":294,"vendors":297,"summary":302,"stage":225,"year":279,"channels":303,"languages":304,"metrics":305,"outcomeDisclosed":212,"sources":306,"verification":315,"grade":239,"id":316,"organizationSlug":241},"City of Madrid (Madrid Destino): VisitMadridGPT multilingual visitor assistant",[198,197,205],{"name":295,"anonymized":212,"country":296,"region":165,"industry":20},"Madrid Destino","ES",[298,300],{"name":299,"role":221},"iUrban",{"name":301,"role":252},"Microsoft (Azure OpenAI Service)","Madrid Destino, the city's municipal tourism office, runs VisitMadridGPT, a virtual assistant that answers visitors in more than 95 languages from the city's official, expert curated tourism site, available when physical offices are closed. The city analyses the questions to find the most requested topics and adjust its website content. According to the story, Madrid attracted 10.6 million visitors in 2023.",[33],[],[],[307,310],{"url":308,"title":309,"publisher":235},"https://customers.microsoft.com/en-us/story/1831036907720807463-esmadrid-azure-openai-service-national-government-en-spain","Transforming tourism in Madrid with Azure OpenAI Service",{"url":311,"title":312,"publisher":313,"date":314},"https://www.eldiariodemadrid.es/articulo/madrid/visitmadridgpt-asistente-virtual-turistas-madrid/20240410141511074094.html","VisitMadridGPT, el asistente virtual para los turistas en Madrid","El Diario de Madrid","2024-04-10",{"level":238,"checkedAt":200},"madrid-destino-visitmadridgpt",0,[],{"low":320,"high":321},10000,200000,[323,353,378,396],{"slug":196,"title":324,"shortTitle":325,"definition":326,"status":9,"industries":327,"functions":328,"patterns":330,"audience":38,"autonomy":333,"adoptionStage":40,"evidenceCount":334,"publicEvidenceCount":335,"organizations":336,"bestGrade":342,"headline":343,"lastVerified":201,"indexable":352},"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],[329,22],"sales",[27,331,26,332],"recommendation-and-personalization","agentic-workflow","supervised-agent",6,5,[337,338,339,340,341],"Airbnb","Booking.com","Holland America Line","Priceline","Trip.com","B",{"kpi":344,"label":345,"unit":346,"n":347,"nUpTo":317,"kind":348,"value":349,"qualifier":350,"claimant":351,"organization":338,"vendorReported":212},"automation-rate","Automation rate","percent",1,"reported",30,"exact","organization",true,{"slug":197,"title":354,"shortTitle":355,"definition":356,"status":9,"industries":357,"functions":358,"patterns":360,"audience":38,"autonomy":333,"adoptionStage":362,"evidenceCount":363,"publicEvidenceCount":364,"organizations":365,"bestGrade":342,"headline":374,"lastVerified":200,"indexable":352},"AI assistant for citizen information and government services","Citizen information assistant","An AI assistant that answers residents' and businesses' questions about government services in plain language, grounded only in official guidance with links to the source, points them to the right online service or office, and hands anything personal, urgent or outside its content to a human with the context attached.",[20],[359,22,24],"citizen-services",[26,27,28,361],"classification-and-routing","mainstream",11,9,[366,367,368,369,370,371,372,295,373],"Abu Dhabi Government (TAMM)","Driver and Vehicle Licensing Agency","Estonian Information System Authority (RIA)","Foreign, Commonwealth and Development Office","Gemeente Tilburg","Government Digital Service","Government of the City of Buenos Aires","Montgomery County Government",{"kpi":58,"label":375,"unit":346,"n":347,"nUpTo":317,"kind":348,"value":376,"qualifier":377,"claimant":351,"organization":369,"vendorReported":212},"Accuracy",76,"at-least",{"slug":198,"title":379,"shortTitle":380,"definition":381,"status":9,"industries":382,"functions":383,"patterns":385,"audience":38,"autonomy":388,"adoptionStage":40,"evidenceCount":72,"publicEvidenceCount":72,"organizations":389,"bestGrade":342,"headline":241,"lastVerified":201,"indexable":352},"AI translation and interpretation for multilingual public services","Public service translation","AI that translates government content, documents and conversations between officials and the public, in writing and in real time speech, so people can use public services in their own language, with human translators and interpreters reviewing what carries legal or safety weight.",[20],[359,22,384],"operations",[30,27,386,387],"speech-analytics","document-processing","copilot",[390,391,392,393,394,295,373,395],"Baltimore City 911 (Emergency Communications)","Delaware County","European Commission","Federal Emergency Management Agency","Internal Revenue Service","U.S. Department of State (Bureau of Consular Affairs)",{"slug":199,"title":397,"shortTitle":398,"definition":399,"status":9,"industries":400,"functions":402,"patterns":403,"audience":404,"autonomy":405,"adoptionStage":40,"segment":406,"evidenceCount":407,"publicEvidenceCount":407,"organizations":408,"bestGrade":239,"headline":412,"lastVerified":200,"indexable":352},"AI assistant for telecom retail stores, from associate copilot to digital human kiosk","Retail store and kiosk assistant","An AI assistant for telecom shops that gives store associates quick, sourced answers on plans, promotions, devices and the customer's account during the conversation, and that can also greet and serve customers directly on an in store screen or kiosk, sometimes as a digital human, handing them to an associate when they are ready to buy or need help.",[401],"telecommunications",[329,22,24],[26,37,27,331],"employee-facing","assist","front-office",3,[409,410,411],"Bouygues Telecom","Deutsche Telekom","T-Mobile",{"kpi":58,"label":375,"unit":346,"n":347,"nUpTo":317,"kind":348,"value":413,"qualifier":350,"claimant":414,"organization":409,"vendorReported":352},95,"vendor",{"indexable":352,"reasons":416},[],[418,423,428,435,443,449,456,463,470,477,484,490,497,504,510,515,522,528,534,540,545,551,557,562,567,573,579,584,589,596,602,608,614,619],{"id":159,"label":419,"issuer":164,"region":165,"url":420,"description":421,"useCases":422,"indexable":352},"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":160,"label":424,"issuer":164,"region":165,"url":425,"description":426,"useCases":427,"indexable":352},"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":429,"label":430,"issuer":431,"region":214,"url":432,"description":433,"useCases":434,"indexable":352},"iso-42001","ISO/IEC 42001","ISO and IEC","https://www.iso.org/standard/81230.html","The international management system standard for AI.",110,{"id":436,"label":437,"issuer":438,"region":439,"url":440,"description":441,"useCases":442,"indexable":352},"nist-ai-rmf","NIST AI Risk Management Framework","NIST","north-america","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":444,"label":445,"issuer":164,"region":165,"url":446,"description":447,"useCases":448,"indexable":352},"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":450,"label":451,"issuer":452,"region":165,"url":453,"description":454,"useCases":455,"indexable":352},"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":457,"label":458,"issuer":459,"region":165,"url":460,"description":461,"useCases":462,"indexable":352},"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.",47,{"id":464,"label":465,"issuer":466,"region":248,"url":467,"description":468,"useCases":469,"indexable":352},"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":471,"label":472,"issuer":473,"region":248,"url":474,"description":475,"useCases":476,"indexable":352},"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.",25,{"id":478,"label":479,"issuer":480,"region":214,"url":481,"description":482,"useCases":483,"indexable":352},"pci-dss","PCI DSS","PCI Security Standards Council","https://www.pcisecuritystandards.org/","Security standard for any system that stores, processes or transmits cardholder data.",20,{"id":485,"label":486,"issuer":487,"region":439,"url":488,"description":489,"useCases":483,"indexable":352},"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":491,"label":492,"issuer":493,"region":165,"url":494,"description":495,"useCases":496,"indexable":352},"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":498,"label":499,"issuer":500,"region":214,"url":501,"description":502,"useCases":503,"indexable":352},"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":505,"label":506,"issuer":164,"region":165,"url":507,"description":508,"useCases":509,"indexable":352},"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":511,"label":512,"issuer":164,"region":165,"url":513,"description":514,"useCases":509,"indexable":352},"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":516,"label":517,"issuer":518,"region":439,"url":519,"description":520,"useCases":521,"indexable":352},"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":523,"label":524,"issuer":164,"region":165,"url":525,"description":526,"useCases":527,"indexable":352},"eu-accessibility-act","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":529,"label":530,"issuer":531,"region":439,"url":532,"description":533,"useCases":527,"indexable":352},"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":535,"label":536,"issuer":537,"region":214,"url":538,"description":539,"useCases":527,"indexable":352},"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":541,"label":542,"issuer":164,"region":165,"url":543,"description":544,"useCases":363,"indexable":352},"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.",{"id":546,"label":547,"issuer":548,"region":439,"url":549,"description":550,"useCases":363,"indexable":352},"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":552,"label":553,"issuer":466,"region":248,"url":554,"description":555,"useCases":556,"indexable":352},"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":558,"label":559,"issuer":164,"region":165,"url":560,"description":561,"useCases":556,"indexable":352},"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":563,"label":564,"issuer":164,"region":165,"url":565,"description":566,"useCases":556,"indexable":352},"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":568,"label":569,"issuer":570,"region":165,"url":571,"description":572,"useCases":364,"indexable":352},"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.",{"id":574,"label":575,"issuer":576,"region":439,"url":577,"description":578,"useCases":72,"indexable":352},"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":580,"label":581,"issuer":164,"region":165,"url":582,"description":583,"useCases":72,"indexable":352},"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":585,"label":586,"issuer":164,"region":165,"url":587,"description":588,"useCases":334,"indexable":352},"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":590,"label":591,"issuer":592,"region":593,"url":594,"description":595,"useCases":335,"indexable":352},"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":597,"label":598,"issuer":599,"region":165,"url":600,"description":601,"useCases":71,"indexable":352},"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":603,"label":604,"issuer":605,"region":165,"url":606,"description":607,"useCases":71,"indexable":352},"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":609,"label":610,"issuer":611,"region":248,"url":612,"description":613,"useCases":407,"indexable":352},"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":615,"label":616,"issuer":164,"region":165,"url":617,"description":618,"useCases":407,"indexable":352},"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":620,"label":621,"issuer":622,"region":439,"url":623,"description":624,"useCases":407,"indexable":352},"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.",1790598307036]