[{"data":1,"prerenderedAt":640},["ShallowReactive",2],{"uc-training-content-generation":3,"uc-regulations":431},{"useCase":4,"evidence":192,"blitsAiDeployments":325,"benchmarks":326,"indicative":343,"related":346,"indexability":429,"includeUnpublished":198},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":17,"functions":22,"patterns":25,"channels":29,"audience":31,"autonomy":32,"adoptionStage":33,"problem":34,"problemStats":35,"howItWorks":36,"valueDrivers":37,"kpis":42,"indicativeValue":47,"macroEstimates":82,"feasibility":83,"implementation":96,"risk":139,"blitsAi":170,"faq":172,"related":182,"datePublished":187,"dateModified":187,"lastVerified":187,"changelog":188,"slug":191},"AI for creating employee training and eLearning content","Training content creation","AI for employee training content creation","Generative AI drafts course outlines, quizzes, narration and avatar videos for staff training, as used by Zoom and the Veterans Benefits Administration.","published","Generative AI that helps learning and development teams turn source material such as procedures, product documentation and policies into training: course outlines, lesson text, quizzes, narration, avatar videos and translations, which instructional designers and subject matter experts review before publishing.",[12,13,14,15,16],"AI course creation","AI eLearning authoring","AI training video generation","AI instructional design assistant","generative AI for learning and development",[18,19,20,21],"cross-industry","government","technology","manufacturing",[23,24],"human-resources","knowledge-management",[26,27,28],"content-generation","translation","summarization",[30],"internal-tools","employee-facing","copilot","early-adopters","Training content is expensive to make and quickly out of date. A single eLearning module takes an\ninstructional designer many hours of scripting, storyboarding, question writing and production,\nand subject matter experts lose days recording themselves: a senior instructional designer at Zoom\ndescribes experts and designers spending an entire day recording to get about 15 minutes of video. When the product, the\nprocedure or the regulation changes, the video has to be reshot, so outdated training stays in\ncirculation.\n\nNew systems, compliance topics and multilingual workforces all need material, often in several\nlanguages and in accessible formats: Carlsberg, for example, used to hire a second agency to\ntranslate each eLearning. Public bodies feel the pressure too. The Veterans Benefits\nAdministration uses an AI assistant to reduce instructor and instructional design burden amid\ndecreased hiring abilities, and to cut classroom time, and the IRS turned to AI voices when return\nto office mandates meant it could no longer record narration with employees.",[],"1. **Start from approved sources.** The designer uploads the procedure, product documentation or\n   policy the course must teach, and defines the audience and learning objectives.\n2. **Draft the structure.** The AI proposes an outline, lesson text and knowledge checks (quizzes\n   and scenarios) mapped to the objectives.\n3. **Produce media.** Narration is generated from the script with synthetic voices, and short\n   videos can use AI avatars instead of filmed presenters; images and sounds are generated or\n   selected.\n4. **Localise.** Text, narration and subtitles are translated into the languages each market\n   needs, as Carlsberg does for supply chain training.\n5. **Review and publish.** A subject matter expert checks accuracy, the designer assembles the\n   module in the authoring tool, and the course is published to the learning platform.\n6. **Update cheaply.** When the source changes, the script is edited and the media regenerated\n   instead of reshot.",[38,39,40,41],"employee-productivity","speed","cost-to-serve","inclusion-and-access",[43,44,45,46],"processing-time-reduction","productivity-gain","hours-saved","cost-savings",{"referenceOrg":48,"inputs":49,"formula":77,"currency":78,"period":79,"resultLabel":80,"caveat":81},"A learning and development team that builds or updates 200 eLearning modules a year",[50,56,63,70],{"key":51,"label":52,"low":53,"high":53,"unit":54,"note":55},"modules","Modules built or substantially updated per year",200,"modules per year","The reference team. Replace with your own volumes.",{"key":57,"label":58,"low":59,"high":60,"unit":61,"note":62},"hoursPerModule","Design and production hours per module today",40,80,"hours per module","Editorial assumption covering scripting, questions, media and assembly; replace with your own.",{"key":64,"label":65,"low":66,"high":67,"unit":68,"note":69},"timeSaved","Share of those hours saved with AI drafting and media generation",0.2,0.4,"fraction of hours","Conservative against the vendor reported 90% time savings on video creation at Zoom on this page, because video is only part of a module and expert review time does not shrink.",{"key":71,"label":72,"low":73,"high":74,"unit":75,"note":76},"hourlyCost","Blended instructional designer and expert hour",50,90,"USD per hour","Editorial assumption.","modules * hoursPerModule * timeSaved * hourlyCost","USD","per year","Course production time released","Counts internal production time only. It leaves out translation savings, the value of training that is current instead of outdated, licence costs and the effect on learning outcomes. Synthesia reports at least €30,000 a year in avoided agency fees at Carlsberg, which the model does not include. Synthesia's reported $1,000 to $1,500 a month per employee saving at Zoom is a vendor estimate of internal production efficiency, which overlaps with what this model already counts, so it is not additional value. None of the deployments on this page has published effects on learning outcomes.",[],{"complexity":84,"complexityNote":85,"dataPrerequisites":86,"integrations":91},"low","Authoring tools such as Articulate 360 and video tools such as Synthesia and TechSmith Camtasia already include these features, as the deployments on this page show, and the source material usually exists. The effort goes into review workflows, keeping content tied to approved sources, consent for any real person's likeness or voice, and accessibility.",[87,88,89,90],"Approved and current source material for each course","Learning objectives and assessment standards","Brand, tone and terminology guidelines, including approved translations","Written consent for any avatar or voice modelled on a real employee",[92,93,94,95],"eLearning authoring tools","Learning management system","Document management or knowledge base holding the source material","Translation memory and terminology tools",{"steps":97,"guardrails":113,"humanInTheLoop":119,"kpisToInstrument":120,"failureModes":126},[98,101,104,107,110],{"title":99,"detail":100},"Pick content that changes often","Start where reshooting and rewriting hurt most: product training, system training and procedures. Zoom uses it for sales enablement, where videos had to be recorded again whenever the training material changed.",{"title":102,"detail":103},"Ground drafts in approved sources","Generate from the procedure or documentation, not from the model's general knowledge, and keep a link from each lesson to its source so updates can be traced.",{"title":105,"detail":106},"Keep experts in the review, not the recording","Move subject matter experts from recording to reviewing scripts and quizzes. That is where their time is best spent and where errors are caught.",{"title":108,"detail":109},"Set rules for synthetic media","Decide which avatars and voices may be used, get written consent for any real person's likeness, label AI generated media, and check captions and transcripts for accessibility.",{"title":111,"detail":112},"Measure learning, not only production","Track completion, assessment results and learner feedback against earlier versions, so faster production does not come at the cost of learning.",[114,115,116,117,118],"Every course reviewed and approved by a named subject matter expert before publishing","Drafts generated from approved sources, with a link to the source version","AI generated video and audio labelled as such to learners","No avatar or cloned voice of a real person without written consent","Captions, transcripts and accessible formats checked before release","Instructional designers direct and assemble the course, subject matter experts approve the content, and learning owners sign off assessments, especially any that count towards certification or role decisions.",[121,122,123,124,125],"Hours from request to published module, before and after","Expert review hours per module","Errors found after publication per module","Assessment scores and completion rates versus earlier versions","Age of content (time since last update) across the catalogue",[127,130,133,136],{"title":128,"detail":129},"Confident errors in the content","The model fills gaps with plausible but wrong details. Generate from sources only and require expert sign off.",{"title":131,"detail":132},"More content, not better learning","Production gets cheaper and the catalogue grows, but nobody checks whether people learn. Track assessment results and retire unused content.",{"title":134,"detail":135},"Consent and likeness problems","An employee's face or voice is reused after they leave or without clear agreement. Keep consent records and prefer stock avatars.",{"title":137,"detail":138},"Uncanny or disengaging media","Avatar videos that feel artificial lose learners' attention. Test with learners and mix formats.",{"euAiAct":140,"regulations":143,"guidance":147,"controls":164,"incidents":169},{"tier":141,"basis":142},"context-dependent","Generating training content is not listed in Annex III. Providers of tools that generate synthetic audio, image, video or text content must mark the output as AI generated (with an exception for assistive editing that does not substantially alter the source), and deployers must disclose deep fakes, such as an avatar or voice that resembles a real person and would falsely appear authentic (Article 50(2) and (4), with the definition in Article 3(60)). If the same system evaluates learning outcomes or decides access to training that affects a person's work, Annex III point 3 (education and vocational training) and point 4 (employment) must be checked, and those parts can be high risk.",[144,145,146],"eu-ai-act","gdpr","iso-42001",[148,154,158],{"title":149,"issuer":150,"region":151,"url":152,"note":153},"Article 50, transparency obligations for providers and deployers of certain AI systems","European Union","europe","https://artificialintelligenceact.eu/article/50/","Machine readable marking of synthetic audio, image, video and text content by providers, and disclosure of deep fakes (image, audio and video) by deployers.",{"title":155,"issuer":150,"region":151,"url":156,"note":157},"Annex III, high risk AI systems referred to in Article 6(2)","https://artificialintelligenceact.eu/annex/3/","Point 3 covers AI that evaluates learning outcomes or decides access in education and vocational training; point 4 covers employment decisions.",{"title":159,"issuer":160,"region":161,"url":162,"note":163},"Section508.gov","US General Services Administration","north-america","https://www.section508.gov/","Accessibility requirements for information and communication technology at US federal agencies, which cover their training content; cited as a goal in the US Marshals Service pilot. Organizations elsewhere follow their own accessibility rules.",[165,166,167,168],"Content ownership and review dates for every course","Register of avatars and voices in use, with consent records","Labelling policy for AI generated media","Accessibility check in the publishing workflow",[],{"howToBuild":171},"Blits.ai is not an eLearning authoring tool, but the drafting work behind a course can run on\nit. An **agentic workflow** takes the approved source documents from the **knowledge base**,\ndrafts an outline, lesson text and quiz questions against the stated objectives as **structured\noutput**, and waits for **human in the loop** approval by the subject matter expert before\nanything is exported, with a full audit trail per run. **Text to speech** across many providers,\nwith custom voices, produces narration audio, and **machine translation** and **multi language**\nsupport cover localisation.\n\nThe same knowledge base can power an **AI agent** that answers learners' follow up questions\nabout the course material in **Microsoft Teams** or web chat, or through a **digital human**\nwhere a face helps. The platform is **model agnostic**, and **test suites** with\nexpert written questions check that drafts and answers stay faithful to the source material.",[173,176,179],{"question":174,"answer":175},"How much faster is course production with AI?","For individual steps, much faster: Synthesia reports 90% time savings on training video creation by Zoom's instructional designers. For a whole module the saving is smaller, because experts still review the content. None of the deployments on this page has published effects on learning outcomes.",{"question":177,"answer":178},"Who uses it in the public sector?","The Veterans Benefits Administration uses an AI assistant in its authoring tool to build eLearning for claims processors, the IRS generates course narration with AI voices, and the US Marshals Service is piloting AI presenters and narration for training videos.",{"question":180,"answer":181},"Do we need to tell learners that a video uses an AI avatar?","Under the EU AI Act, providers must mark synthetic media as AI generated and deployers must disclose deep fakes, such as an avatar or voice that resembles a real person. Labelling all AI generated media is the simple policy.",[183,184,185,186],"conversation-roleplay-training","employee-onboarding-assistant","support-knowledge-article-generation","audio-and-video-transcription-and-captioning","2026-09-27",[189],{"date":187,"note":190},"First published","training-content-generation",[193,221,239,256,289],{"title":194,"useCases":195,"organization":196,"vendors":200,"summary":204,"stage":205,"year":206,"channels":207,"languages":208,"metrics":210,"outcomeDisclosed":198,"sources":211,"verification":216,"grade":218,"id":219,"organizationSlug":220},"US Marshals Service: AI presenters and narration for training videos (pilot)",[191],{"name":197,"anonymized":198,"country":199,"region":161,"industry":19},"U.S. Marshals Service",false,"US",[201],{"name":202,"role":203},"TechSmith","platform","Training content creators at the US Marshals Service, part of the Department of Justice, have piloted TechSmith Camtasia and Audiate since September 2025 to generate on screen presenters and realistic narration from text, and to produce voice audio in a range of voices and tones without recording actors. The goals are to shorten the time to release training material, support Section 508 accessibility and improve the online learning experience. No outcome figures are published.","pilot",2025,[30],[209],"en",[],[212],{"url":213,"title":214,"publisher":215},"https://raw.githubusercontent.com/ombegov/2025-Federal-Agency-AI-Use-Case-Inventory/main/Data/2025_individually_reported_AI_use_cases.csv","2025 individually reported AI use cases (entries DOJ-0319 Camtasia and DOJ-0330 Audiate)","Office of Management and Budget (GitHub)",{"level":217,"checkedAt":187},"source-verified","B","us-marshals-service-ai-training-video-pilot",null,{"title":222,"useCases":223,"organization":224,"vendors":226,"summary":229,"stage":230,"year":206,"channels":231,"languages":232,"metrics":233,"outcomeDisclosed":198,"sources":234,"verification":237,"grade":218,"id":238,"organizationSlug":220},"Veterans Benefits Administration: AI assistant builds eLearning for claims processors",[191],{"name":225,"anonymized":198,"country":199,"region":161,"industry":19},"Veterans Benefits Administration",[227],{"name":228,"role":203},"Articulate","The Veterans Benefits Administration uses the AI Assistant in Articulate 360 to create interactive eLearning for its claims processors more efficiently. The assistant generates text to voice audio, images, outlines, polls, quizzes and sounds for courses. The inventory entry says engaging eLearning reduces instructor burden and classroom time, that efficient training development reduces instructional design burden amid decreased hiring abilities, and that the time saved in developing training brings cost savings, without a figure. The inventory lists it as deployed; no outcome figures are published.","production",[30],[209],[],[235],{"url":213,"title":236,"publisher":215},"2025 individually reported AI use cases (entry VA-25-1471, Articulate 360: AI Assistant)",{"level":217,"checkedAt":187},"vba-articulate-ai-assistant-elearning",{"title":240,"useCases":241,"organization":242,"vendors":244,"summary":245,"stage":230,"year":246,"channels":247,"languages":248,"metrics":249,"outcomeDisclosed":198,"sources":250,"verification":253,"grade":218,"id":254,"organizationSlug":255},"Internal Revenue Service: AI voiceover generation for eLearning courses",[191],{"name":243,"anonymized":198,"country":199,"region":161,"industry":19},"Internal Revenue Service",[],"IRS training developers used to record course narration with employees and microphone kits; with return to office mandates that was no longer possible. Since May 2024 they enter narration scripts into a web based AI voice tool that returns audio files for import into eLearning authoring applications. Scripts contain no personal or taxpayer information and use fictitious names and addresses. The IRS reports better quality, a wider choice of voices and much faster generation and revision of voiceovers, but publishes no figures.",2024,[30],[209],[],[251],{"url":213,"title":252,"publisher":215},"2025 individually reported AI use cases (entry TREAS-IRS-65, AI Voiceover Generation for eLearning Development)",{"level":217,"checkedAt":187},"irs-ai-voiceover-elearning","internal-revenue-service",{"title":257,"useCases":258,"organization":259,"vendors":263,"summary":266,"stage":230,"year":267,"channels":268,"languages":269,"metrics":270,"outcomeDisclosed":281,"sources":282,"verification":286,"grade":287,"id":288,"organizationSlug":220},"Carlsberg: supply chain training produced in house with AI video",[191],{"name":260,"anonymized":198,"country":261,"region":262,"industry":21},"Carlsberg Group","DK","global",[264],{"name":265,"role":203},"Synthesia","Since 2023, Carlsberg's Integrated Supply Chain Academy has built training in house with Synthesia instead of external video agencies, and use has spread to shop floor onboarding, one point safety lessons, procurement training and change management content. A document, usually a PDF, goes into the tool's AI Assistant, which scaffolds the structure; the video is built in a branded template, generated in English and translated for each market. Synthesia reports that more than 100 employees have built content in under two years, that three agency shoots a year (its conservative baseline, at least €30,000 in fees) no longer sit on Carlsberg's P&L, and that the second supplier once hired to translate each eLearning is no longer needed. These are vendor stated figures, not a measured saving net of licence costs.",2023,[30],[209],[271],{"kpi":272,"value":273,"unit":274,"qualifier":275,"period":276,"baseline":277,"claimant":278,"quote":279,"sourceUrl":280},"users-served",100,"count","at-least","in under two years","employees across the business who have built content in Synthesia (creators, not learners)","vendor","In under two years, more than 100 employees from across the business have built content in Synthesia, with adoption still growing.","https://www.synthesia.io/case-studies/carlsberg",true,[283],{"url":280,"title":284,"publisher":265,"date":285},"Carlsberg takes supply chain training in-house with AI video","2026-09-22",{"level":217,"checkedAt":187},"C","carlsberg-ai-video-supply-chain-training",{"title":290,"useCases":291,"organization":292,"vendors":294,"summary":296,"stage":230,"year":267,"channels":297,"languages":298,"metrics":299,"outcomeDisclosed":281,"sources":319,"verification":323,"grade":287,"id":324,"organizationSlug":220},"Zoom: AI avatar videos for sales enablement training",[191],{"name":293,"anonymized":198,"country":199,"region":161,"industry":20},"Zoom",[295],{"name":265,"role":203},"Zoom's instructional designers train more than 1,000 salespeople on selling its products. When training material changed, whole videos had to be recorded again, with subject matter experts spending a day in front of a camera for about 15 minutes of usable footage. The team now produces AI avatar videos with Synthesia and builds them into interactive modules in Rise 360 and Storyline. Synthesia reports 90% time savings on video creation, more than 200 micro videos from one designer in about six months, 15 to 20 hours a month freed for Zoom's subject matter experts who no longer record themselves (the page does not say whether this is per expert or in total), and monthly cost savings of $1,000 to $1,500 per employee previously spent on creating training videos.",[30],[209],[300,306,312],{"kpi":43,"value":74,"unit":301,"qualifier":302,"baseline":303,"claimant":278,"quote":304,"sourceUrl":305},"percent","exact","time to create a training video, from the page's headline figure; the body states it as \"90% faster than before, producing content in less than an hour\"","90% time savings","https://www.synthesia.io/case-studies/zoom",{"kpi":45,"value":307,"unit":308,"qualifier":275,"period":309,"baseline":310,"claimant":278,"quote":311,"sourceUrl":305},15,"hours","per month","15 to 20 hours a month that Zoom's subject matter experts no longer spend recording (the page does not say whether this is per expert or in total)","Time Saved for SMEs: Zoom's subject matter experts no longer need to record themselves, freeing up 15-20 hours each month to work on their actual job.",{"kpi":46,"value":313,"unit":314,"currency":78,"qualifier":315,"period":316,"baseline":317,"claimant":278,"quote":318,"sourceUrl":305},1500,"currency","up-to","per month, per employee","$1,000 to $1,500 a month per instructional designer or expert previously spent on creating training videos; vendor stated, method not given, not net of licence costs","Enhanced Productivity: Thanks to AI video, both IDs and SMEs can work more efficiently. This results in monthly cost savings of $1,000 - $1,500 per employee previously spent on creating training videos.",[320],{"url":305,"title":321,"publisher":265,"date":322},"How Zoom accelerated training video production by 90%","2023-09-13",{"level":217,"checkedAt":187},"zoom-ai-video-sales-training",0,[327,333,338],{"kpi":43,"label":328,"unit":301,"aggregate":281,"higherIsBetter":281,"n":329,"nUpTo":325,"median":74,"min":74,"max":74,"byClaimant":330,"vendorOnly":281,"points":331},"Cycle time reduction",1,{"organization":325,"vendor":329,"regulator":325,"independent":325},[332],{"evidenceId":324,"organization":293,"value":74,"qualifier":302,"claimant":278,"grade":287,"pooled":281},{"kpi":45,"label":334,"unit":308,"aggregate":198,"higherIsBetter":281,"n":329,"nUpTo":325,"median":307,"min":307,"max":307,"byClaimant":335,"vendorOnly":281,"points":336},"Hours saved",{"organization":325,"vendor":329,"regulator":325,"independent":325},[337],{"evidenceId":324,"organization":293,"value":307,"qualifier":275,"claimant":278,"grade":287,"pooled":281},{"kpi":46,"label":339,"unit":314,"currency":78,"aggregate":198,"higherIsBetter":281,"n":325,"nUpTo":329,"median":220,"min":220,"max":220,"byClaimant":340,"vendorOnly":198,"points":341},"Cost savings",{"organization":325,"vendor":325,"regulator":325,"independent":325},[342],{"evidenceId":324,"organization":293,"value":313,"qualifier":315,"claimant":278,"grade":287,"pooled":198},{"low":344,"high":345},80000,576000,[347,374,390,405],{"slug":183,"title":348,"shortTitle":349,"definition":350,"status":9,"industries":351,"functions":356,"patterns":359,"audience":31,"autonomy":362,"adoptionStage":33,"evidenceCount":363,"publicEvidenceCount":363,"organizations":364,"bestGrade":218,"headline":368,"lastVerified":373,"indexable":281},"AI roleplay training for customer conversations","Conversation roleplay training","A training simulator in which generative AI plays a realistic customer, by voice or text, so service, sales and crisis staff can rehearse difficult conversations as often as they need before they handle live ones, and receive structured feedback against the organization's own standards.",[18,352,353,354,19,355],"banking","insurance","telecommunications","healthcare",[23,357,358],"customer-service","sales",[360,361,26],"conversational-agent","voice-agent","assist",3,[365,366,367],"Bank of America","GoHealth","U.S. Department of Veterans Affairs",{"kpi":369,"label":370,"unit":301,"n":329,"nUpTo":325,"kind":371,"value":372,"qualifier":302,"claimant":278,"organization":366,"vendorReported":281},"conversion-rate-uplift","Conversion uplift","reported",21,"2026-09-26",{"slug":184,"title":375,"shortTitle":376,"definition":377,"status":9,"industries":378,"functions":380,"patterns":381,"audience":31,"autonomy":384,"adoptionStage":33,"evidenceCount":385,"publicEvidenceCount":363,"organizations":386,"bestGrade":218,"headline":220,"lastVerified":187,"indexable":281},"AI assistant for employee onboarding","Employee onboarding assistant","An assistant that guides each new employee from signed contract through the first months: it answers first week questions in plain language, tracks the personal onboarding checklist, triggers the paperwork, equipment, access and training steps in the systems that own them, and keeps the manager and HR informed of what is still open.",[18,19,379,355],"professional-services",[23,24],[360,382,383],"rag-knowledge-assistant","agentic-workflow","supervised-agent",4,[387,388,389],"American Addiction Centers","KPMG","U.S. Department of Agriculture",{"slug":185,"title":391,"shortTitle":392,"definition":393,"status":9,"industries":394,"functions":396,"patterns":398,"audience":31,"autonomy":32,"adoptionStage":400,"evidenceCount":385,"publicEvidenceCount":385,"organizations":401,"bestGrade":218,"headline":220,"lastVerified":187,"indexable":281},"AI for support knowledge article generation and maintenance","Knowledge article generation","AI that drafts knowledge base articles from resolved tickets, cases and conversations, detects questions the knowledge base does not answer and articles that are outdated or contradict each other, and proposes new or revised articles for a knowledge owner to review and publish.",[18,19,395],"automotive",[24,357,397],"it-and-engineering",[26,28,399],"classification-and-routing","emerging",[402,243,403,404],"Centers for Disease Control and Prevention","U.S. National Science Foundation","Rivian",{"slug":186,"title":406,"shortTitle":407,"definition":408,"status":9,"industries":409,"functions":412,"patterns":414,"audience":416,"autonomy":32,"adoptionStage":417,"evidenceCount":418,"publicEvidenceCount":419,"organizations":420,"bestGrade":287,"headline":426,"lastVerified":373,"indexable":281},"AI transcription, subtitles and captions for audio and video","Transcription and captioning","AI that transcribes recorded audio and video, such as podcasts, broadcasts, lessons, interviews and hearings, in several languages, separates the speakers and produces timed transcripts, subtitles and captions for a human editor to check, delivered as files for publishing or the archive.",[410,411,18],"media-and-entertainment","education",[413,24],"operations",[415,27,26],"speech-analytics","back-office","mainstream",6,5,[421,422,423,424,425],"Ateme","Comeen","Pacers Sports & Entertainment","Sveriges Television (SVT)","Warner Bros. Discovery",{"kpi":427,"label":428,"unit":301,"n":329,"nUpTo":325,"kind":371,"value":73,"qualifier":302,"claimant":278,"organization":425,"vendorReported":281},"cost-reduction","Cost reduction",{"indexable":281,"reasons":430},[],[432,437,442,448,455,461,468,475,483,490,497,503,510,516,522,527,534,540,546,552,558,564,570,575,580,587,594,599,604,611,617,623,629,634],{"id":144,"label":433,"issuer":150,"region":151,"url":434,"description":435,"useCases":436,"indexable":281},"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":145,"label":438,"issuer":150,"region":151,"url":439,"description":440,"useCases":441,"indexable":281},"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":146,"label":443,"issuer":444,"region":262,"url":445,"description":446,"useCases":447,"indexable":281},"ISO/IEC 42001","ISO and IEC","https://www.iso.org/standard/81230.html","The international management system standard for AI.",110,{"id":449,"label":450,"issuer":451,"region":161,"url":452,"description":453,"useCases":454,"indexable":281},"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":456,"label":457,"issuer":150,"region":151,"url":458,"description":459,"useCases":460,"indexable":281},"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":462,"label":463,"issuer":464,"region":151,"url":465,"description":466,"useCases":467,"indexable":281},"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":469,"label":470,"issuer":471,"region":151,"url":472,"description":473,"useCases":474,"indexable":281},"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":476,"label":477,"issuer":478,"region":479,"url":480,"description":481,"useCases":482,"indexable":281},"mas-ai-risk-management","MAS AI risk management guidelines","Monetary Authority of Singapore","asia-pacific","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":484,"label":485,"issuer":486,"region":479,"url":487,"description":488,"useCases":489,"indexable":281},"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":491,"label":492,"issuer":493,"region":262,"url":494,"description":495,"useCases":496,"indexable":281},"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":498,"label":499,"issuer":500,"region":161,"url":501,"description":502,"useCases":496,"indexable":281},"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":504,"label":505,"issuer":506,"region":151,"url":507,"description":508,"useCases":509,"indexable":281},"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":511,"label":512,"issuer":513,"region":262,"url":514,"description":515,"useCases":307,"indexable":281},"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.",{"id":517,"label":518,"issuer":150,"region":151,"url":519,"description":520,"useCases":521,"indexable":281},"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":523,"label":524,"issuer":150,"region":151,"url":525,"description":526,"useCases":521,"indexable":281},"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":528,"label":529,"issuer":530,"region":161,"url":531,"description":532,"useCases":533,"indexable":281},"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":535,"label":536,"issuer":150,"region":151,"url":537,"description":538,"useCases":539,"indexable":281},"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":541,"label":542,"issuer":543,"region":161,"url":544,"description":545,"useCases":539,"indexable":281},"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":547,"label":548,"issuer":549,"region":262,"url":550,"description":551,"useCases":539,"indexable":281},"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":553,"label":554,"issuer":150,"region":151,"url":555,"description":556,"useCases":557,"indexable":281},"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":559,"label":560,"issuer":561,"region":161,"url":562,"description":563,"useCases":557,"indexable":281},"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":565,"label":566,"issuer":478,"region":479,"url":567,"description":568,"useCases":569,"indexable":281},"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":571,"label":572,"issuer":150,"region":151,"url":573,"description":574,"useCases":569,"indexable":281},"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":576,"label":577,"issuer":150,"region":151,"url":578,"description":579,"useCases":569,"indexable":281},"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":581,"label":582,"issuer":583,"region":151,"url":584,"description":585,"useCases":586,"indexable":281},"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":588,"label":589,"issuer":590,"region":161,"url":591,"description":592,"useCases":593,"indexable":281},"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.",8,{"id":595,"label":596,"issuer":150,"region":151,"url":597,"description":598,"useCases":593,"indexable":281},"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":600,"label":601,"issuer":150,"region":151,"url":602,"description":603,"useCases":418,"indexable":281},"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":605,"label":606,"issuer":607,"region":608,"url":609,"description":610,"useCases":419,"indexable":281},"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":612,"label":613,"issuer":614,"region":151,"url":615,"description":616,"useCases":385,"indexable":281},"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":618,"label":619,"issuer":620,"region":151,"url":621,"description":622,"useCases":385,"indexable":281},"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":624,"label":625,"issuer":626,"region":479,"url":627,"description":628,"useCases":363,"indexable":281},"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":630,"label":631,"issuer":150,"region":151,"url":632,"description":633,"useCases":363,"indexable":281},"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":635,"label":636,"issuer":637,"region":161,"url":638,"description":639,"useCases":363,"indexable":281},"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.",1790598299749]