[{"data":1,"prerenderedAt":616},["ShallowReactive",2],{"uc-employee-onboarding-assistant":3,"uc-regulations":408},{"useCase":4,"evidence":200,"blitsAiDeployments":296,"benchmarks":297,"indicative":304,"related":307,"indexability":406,"includeUnpublished":206},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":17,"functions":22,"patterns":25,"channels":29,"audience":34,"autonomy":35,"adoptionStage":36,"problem":37,"problemStats":38,"howItWorks":39,"valueDrivers":40,"kpis":45,"indicativeValue":51,"macroEstimates":86,"feasibility":87,"implementation":101,"risk":147,"blitsAi":177,"faq":179,"related":189,"datePublished":195,"dateModified":195,"lastVerified":195,"changelog":196,"slug":199},"AI assistant for employee onboarding","Employee onboarding assistant","AI employee onboarding assistant for new hires","An AI onboarding assistant answers new hire questions, tracks the checklist and chases paperwork, access and training. Value model, evidence and EU AI Act risk.","published","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.",[12,13,14,15,16],"new hire assistant","onboarding chatbot","AI onboarding buddy","preboarding assistant","new joiner assistant",[18,19,20,21],"cross-industry","government","professional-services","healthcare",[23,24],"human-resources","knowledge-management",[26,27,28],"conversational-agent","rag-knowledge-assistant","agentic-workflow",[30,31,32,33],"microsoft-teams","internal-tools","mobile-app","email","employee-facing","supervised-agent","early-adopters","Onboarding is where an employer makes its first impression on someone it has already paid to\nrecruit, and it is usually a patchwork. Tasks sit with HR, IT, facilities, payroll, security and\nthe manager, each with its own system and checklist. New hires do not know whom to ask, so they ask\neveryone, or nobody. Laptops arrive late, access requests wait for approval, mandatory training is\nmissed, and managers spend the first weeks answering the same questions every new starter has.\n\nThe cost is real: slower time to productivity, early attrition among people who leave in their\nfirst months, and compliance gaps when a mandatory step is skipped. An assistant helps in two ways.\nIt answers questions from the organization's own onboarding content at any hour, in the new\nhire's language, and it orchestrates the checklist, starting and chasing steps in the owning\nsystems so that nothing depends on memory. It does not replace the manager's welcome or the buddy;\nit frees them for it.",[],"1. **Start at signature.** When the hire is confirmed in the HR system, the assistant creates a\n   personal onboarding plan based on role, location, contract type and start date.\n2. **Preboard.** Before day one it collects documents and details through the HR system's own\n   forms, explains what to expect and answers questions about the first day.\n3. **Trigger the provisioning.** It opens the requests for equipment, accounts, access and badges\n   in IT and facilities systems, following the normal approvals, and tracks them.\n4. **Answer from approved content.** Questions about policies, tools, benefits and \"how do I\" are\n   answered from onboarding and HR content, with links, and routed to a person when the answer is\n   not there or the topic is sensitive.\n5. **Keep the plan moving.** It reminds the new hire of mandatory training and tasks, nudges owners\n   of overdue steps and gives the manager a view of what is complete.\n6. **Check in and hand over.** At set points it asks how things are going, passes concerns to HR or\n   the manager, and hands over to the general HR and IT assistants once onboarding ends.",[41,42,43,44],"employee-productivity","speed","cost-to-serve","compliance",[46,47,48,49,50],"cycle-time-days","contact-deflection","time-saved-per-task","employee-adoption","containment-rate",{"referenceOrg":52,"inputs":53,"formula":81,"currency":82,"period":83,"resultLabel":84,"caveat":85},"An organization that onboards 2,000 new employees a year",[54,60,67,74],{"key":55,"label":56,"low":57,"high":57,"unit":58,"note":59},"newHires","New hires per year",2000,"hires per year","The reference organization.",{"key":61,"label":62,"low":63,"high":64,"unit":65,"note":66},"supportHoursPerHire","HR, IT and manager hours spent per hire on onboarding questions and chasing",4,8,"hours per hire","Editorial assumption. Replace with a time study of your own onboarding.",{"key":68,"label":69,"low":70,"high":71,"unit":72,"note":73},"shareSaved","Share of those hours the assistant takes over",0.2,0.4,"fraction of hours","Editorial assumption for the whole range, replace with your own measurement. No cited source measures the share of onboarding support hours an assistant takes over; the low end assumes it handles routine questions, the high end adds time spent chasing provisioning steps.",{"key":75,"label":76,"low":77,"high":78,"unit":79,"note":80},"hourlyCost","Blended hourly cost of HR, IT and managers",45,70,"USD per hour","Editorial assumption, replace with your own.","newHires * supportHoursPerHire * shareSaved * hourlyCost","USD","per year","Onboarding support time released","Counts only support time. It leaves out faster time to productivity for the new hire, lower early attrition and fewer missed compliance steps, which you should estimate separately, and the cost of the platform and integrations.",[],{"complexity":88,"complexityNote":89,"dataPrerequisites":90,"integrations":95},"medium","Answering onboarding questions is quick to build. Orchestrating the checklist across HR, IT and facilities systems, with the right approvals and a plan per role and country, is where the effort goes.",[91,92,93,94],"Current onboarding content per country and role, with owners","The onboarding checklist per role, location and contract type, with the owner of each step","Start date, role and manager data from the HR system","The list of topics that must go to a person",[96,97,98,99,100],"HR information system (for example Workday or SAP SuccessFactors)","IT service management for equipment, accounts and access requests","Identity provider for account creation and single sign on","Learning management system for mandatory training","Collaboration tools where employees work, such as Microsoft Teams",{"steps":102,"guardrails":121,"humanInTheLoop":127,"kpisToInstrument":128,"failureModes":134},[103,106,109,112,115,118],{"title":104,"detail":105},"Map the journey and its owners","List every onboarding step from signature to the end of probation, who owns it, which system records it and what usually goes wrong. Fix obviously broken steps before automating them.",{"title":107,"detail":108},"Launch the question answering first","Load current onboarding content, filtered by country and role, and let new hires ask questions from before day one. Measure what they ask to find gaps in the content.",{"title":110,"detail":111},"Connect the checklist","Create the plan from the HR system and open requests in IT and facilities systems through their normal workflows and approvals, one step type at a time.",{"title":113,"detail":114},"Give managers a view","Show the manager what is complete and what is overdue, and send nudges to step owners rather than to the new hire.",{"title":116,"detail":117},"Design the human moments","Decide where a person must be present (welcome, first one to one, sensitive questions) and make the assistant route to them instead of trying to answer.",{"title":119,"detail":120},"Hand over and measure","At the end of onboarding, pass the employee to the general HR and IT assistants and measure time to productivity, early attrition and missed mandatory steps.",[122,123,124,125,126],"Answers only from approved onboarding content, with links, and a handover when the content has no answer","Provisioning through the owning systems and their approval workflows, never by direct changes","No evaluation of the new hire's performance or suitability; the assistant supports, managers assess","Sensitive topics (health, adjustments, grievances, pay disputes) routed to a person","Personal data read only through APIs scoped to the new hire and their manager","HR owns the content and the plan templates, IT and facilities approve provisioning in their own systems, and managers own the welcome, the check ins and every judgment about the new hire. HR reviews a sample of conversations each month for accuracy and for topics that should have been handed over.",[129,130,131,132,133],"Time from start date to equipment and access ready","Share of onboarding steps completed on time, per owner","Questions answered without a person, and handover reasons","New hire satisfaction with onboarding","Early attrition in the first 90 days, compared with before",[135,138,141,144],{"title":136,"detail":137},"Automating a broken process","The assistant faithfully chases steps that nobody owns. Map owners and fix broken steps before connecting them.",{"title":139,"detail":140},"One size fits all","A contractor in one country gets the plan for an employee in another. Build plans from role, location and contract type.",{"title":142,"detail":143},"Drift into evaluation","Check in answers or training completion are used to judge new hires. That changes the risk class and needs its own assessment and consultation.",{"title":145,"detail":146},"The assistant replaces the welcome","Managers leave onboarding to the bot. Keep the human moments in the plan and make them visible to the manager.",{"euAiAct":148,"regulations":151,"guidance":155,"controls":171,"incidents":176},{"tier":149,"basis":150},"context-dependent","Answering onboarding questions and orchestrating provisioning is limited risk: under Article 50(1) the assistant must be designed so that employees are told they are interacting with AI, unless that is obvious. It becomes high risk under Annex III point 4(b) if it is used to make decisions on the terms or termination of the work relationship, to allocate tasks based on individual behaviour or personal traits, or to monitor and evaluate new hires' performance or behaviour, for example to judge probation.",[152,153,154],"eu-ai-act","gdpr","iso-42001",[156,162,166],{"title":157,"issuer":158,"region":159,"url":160,"note":161},"Annex III, high risk AI systems referred to in Article 6(2)","European Union","europe","https://artificialintelligenceact.eu/annex/3/","Point 4(b) covers AI used for decisions on the terms, promotion or termination of work relationships, to allocate tasks based on behaviour or personal traits, or to monitor and evaluate workers.",{"title":163,"issuer":158,"region":159,"url":164,"note":165},"Article 50, transparency obligations for providers and deployers of certain AI systems","https://artificialintelligenceact.eu/article/50/","Article 50(1) requires AI systems that interact directly with people to be designed so that they are told they are interacting with AI, unless this is obvious from the context.",{"title":167,"issuer":168,"region":159,"url":169,"note":170},"Employment practices and data protection: monitoring workers","UK Information Commissioner's Office","https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/employment/monitoring-workers/","UK guidance, under review after the Data (Use and Access) Act, on monitoring workers under the UK GDPR. Relevant to what the assistant logs about new hires and who may see it.",[172,173,174,175],"Data protection impact assessment covering what is logged about new hires","Content ownership and review dates for onboarding material per country","Consultation with employee representatives where required","Access control on onboarding progress data, limited to HR and the line manager",[],{"howToBuild":178},"On Blits.ai this is an **AI agent** in **Microsoft Teams** (or the **web chat** bubble on the\nintranet, a mobile app through the **API channel**, or **email**), grounded in a **knowledge base**\nof onboarding content with hybrid retrieval and document version control, with separate content\nwhere policies differ by country. An **agentic workflow** started\nfrom the HR system through an **API token** builds the plan and uses **custom functions** to open\nrequests in IT and facilities systems (the integration catalog includes Workday, ServiceNow and\nOkta), with **agentic tasks** that recheck overdue steps on a schedule and nudge their owners.\n\n**Human in the loop** approval holds actions above a threshold you set, a **flow** routes sensitive\ntopics to HR through **human handover**, and **guardrails** with **PII masking** keep personal data\nout of prompts. An **authentication** step in the flow confirms who the employee is,\n**multi language** support serves new hires in their own language, and **test suites** check\nanswers per country before content changes go live. The platform is model agnostic and can run in\nthe EU or UAE region.",[180,183,186],{"question":181,"answer":182},"What does an onboarding assistant change in practice?","It takes routine questions off managers and HR and keeps paperwork, access and training steps moving, but published outcome data for dedicated onboarding assistants is thin. Microsoft says KPMG designed its onboarding agent to reduce follow up calls by 20%, a stated aim without a reported result. American Addiction Centers says Gemini for Google Workspace, a general productivity suite rather than an onboarding assistant, helped cut employee onboarding from three days to 12 hours.",{"question":184,"answer":185},"Is this the same as an HR chatbot?","It overlaps, but onboarding is a time bound journey with a checklist across HR, IT and facilities, not only questions. It can run as a mode of the same HR assistant, which takes over once onboarding is complete.",{"question":187,"answer":188},"Is an onboarding assistant high risk under the EU AI Act?","Not when it answers questions and orchestrates tasks. It becomes high risk under Annex III point 4(b) if it is used to evaluate new hires or allocate work based on their behaviour or traits, for example to judge probation.",[190,191,192,193,194],"hr-and-policy-assistant","it-service-desk-resolution-agent","recruitment-screening-and-interview-scheduling","enterprise-knowledge-search","conversation-roleplay-training","2026-09-27",[197],{"date":195,"note":198},"First published","employee-onboarding-assistant",[201,234,263],{"title":202,"useCases":203,"organization":204,"vendors":209,"summary":213,"stage":214,"year":215,"channels":216,"languages":217,"metrics":219,"outcomeDisclosed":206,"sources":220,"verification":228,"grade":231,"id":232,"organizationSlug":233},"USDA Forest Service: generative AI New Hire Experience assistant in the service CRM",[199],{"name":205,"anonymized":206,"country":207,"region":208,"industry":19},"U.S. Department of Agriculture",false,"US","north-america",[210],{"name":211,"role":212},"Salesforce","platform","The Forest Service, within USDA's Natural Resources and Environment mission area, runs a generative AI New Hire Experience capability in its Salesforce customer relationship manager. It gives users, new hires by its name, text based self help on human resources, business and finance processes and procedures. The inventory describes it as deployed with an operational date of January 2024, classifies it as not high impact and states that it uses no personal data; no outcome figures are published.","production",2024,[31],[218],"en",[],[221,225],{"url":222,"title":223,"publisher":224},"https://github.com/ombegov/2025-Federal-Agency-AI-Use-Case-Inventory","2025 Federal Agency AI Use Case Inventory","Office of Management and Budget (GitHub)",{"url":226,"title":227,"publisher":224},"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 (entry USDA-168, NRE FS Customer Relationship Manager New Hire Experience)",{"level":229,"checkedAt":230},"source-verified","2026-09-26","B","usda-forest-service-new-hire-experience-assistant","u-s-department-of-agriculture",{"title":235,"useCases":236,"organization":237,"vendors":240,"summary":243,"stage":244,"year":245,"channels":246,"languages":247,"metrics":248,"outcomeDisclosed":206,"sources":249,"verification":259,"grade":260,"id":261,"organizationSlug":262},"KPMG: onboarding agent that guides new team members",[199],{"name":238,"anonymized":206,"region":239,"industry":20},"KPMG","global",[241],{"name":242,"role":212},"Microsoft","Microsoft reports that KPMG used Microsoft AI to develop a team member onboarding agent that guides new hires and gives them templates and historical references. Microsoft describes it as part of KPMG's AI strategy and says it is meant to speed up onboarding and reduce follow up calls by 20%; that figure is stated as an aim, with no period, baseline or measured result. The member firm, whether the agent is live and the number of users are not stated.","announced",2025,[31],[218],[],[250,255],{"url":251,"title":252,"publisher":253,"date":254},"https://www.microsoft.com/en-us/worklab/agents-of-change","Agents of change","Microsoft WorkLab","2025-03-05",{"url":256,"title":257,"publisher":242,"date":258},"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":229,"checkedAt":195},"C","kpmg-new-hire-onboarding-agent",null,{"title":264,"useCases":265,"organization":266,"vendors":268,"summary":271,"stage":214,"year":215,"channels":272,"languages":273,"metrics":274,"outcomeDisclosed":283,"sources":284,"verification":294,"grade":260,"id":295,"organizationSlug":262},"American Addiction Centers: generative AI to shorten employee onboarding",[199],{"name":267,"anonymized":206,"country":207,"region":208,"industry":21},"American Addiction Centers",[269],{"name":270,"role":212},"Google","American Addiction Centers, a provider of addiction treatment, cut employee onboarding from three days to 12 hours with Gemini for Google Workspace. Its CIO called Gemini \"a key driver\" of that reduction in a Google Workspace recap of Google Cloud Next 2024, and Google Cloud repeats the figure in its list of customer use cases. The sources name a general productivity suite, not an assistant that guides new hires or runs the onboarding checklist, and they do not describe how the process was changed or whether the three days were working or calendar days.",[31],[218],[275],{"kpi":46,"value":276,"unit":277,"qualifier":278,"baseline":279,"claimant":280,"quote":281,"sourceUrl":282},12,"hours","exact","3 days of employee onboarding before","organization","Gemini for Workspace was a key driver in reducing employee onboarding from 3 days to 12 hours.","https://workspace.google.com/blog/events/cloud-next-recap-20-ways-our-customers-outdo-themselves",true,[285,289],{"url":282,"title":286,"publisher":287,"date":288},"How 20 of our customers outdo themselves with Google Workspace","Google Workspace","2024-04-16",{"url":290,"title":291,"publisher":292,"archivedUrl":293},"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","https://web.archive.org/web/20241226092809/https://cloud.google.com/transform/101-real-world-generative-ai-use-cases-from-industry-leaders",{"level":229,"checkedAt":195},"american-addiction-centers-employee-onboarding",1,[298],{"kpi":46,"label":299,"unit":277,"aggregate":206,"higherIsBetter":206,"n":296,"nUpTo":300,"median":276,"min":276,"max":276,"byClaimant":301,"vendorOnly":206,"points":302},"Cycle time",0,{"organization":296,"vendor":300,"regulator":300,"independent":300},[303],{"evidenceId":295,"organization":267,"value":276,"qualifier":278,"claimant":280,"grade":260,"pooled":283},{"low":305,"high":306},72000,448000,[308,329,349,371,387],{"slug":190,"title":309,"shortTitle":310,"definition":311,"status":9,"industries":312,"functions":315,"patterns":316,"audience":34,"autonomy":35,"adoptionStage":36,"evidenceCount":317,"publicEvidenceCount":63,"organizations":318,"bestGrade":231,"headline":323,"lastVerified":195,"indexable":283},"AI assistant for HR and policy questions","HR and policy assistant","An employee self service assistant that answers questions on leave, pay and tax forms, benefits, expenses, travel and conduct policies from the organization's own HR documents, personalized to the employee's country and role, and starts simple HR transactions such as leave requests or employment letters in the HR system.",[18,313,314,21],"banking","technology",[23,24],[27,26,28],5,[319,320,321,322],"Bank of America","IBM","Turing","Vituity",{"kpi":49,"label":324,"unit":325,"n":326,"nUpTo":300,"kind":327,"value":328,"qualifier":278,"claimant":280,"organization":320,"vendorReported":206},"Employee adoption","percent",2,"reported",99,{"slug":191,"title":330,"shortTitle":331,"definition":332,"status":9,"industries":333,"functions":335,"patterns":338,"audience":34,"autonomy":35,"adoptionStage":340,"evidenceCount":64,"publicEvidenceCount":341,"organizations":342,"bestGrade":231,"headline":346,"lastVerified":195,"indexable":283},"AI agent for IT service desk resolution","IT service desk resolution","An AI agent in Microsoft Teams, Slack or the intranet that takes the high volume IT support queue, such as password and MFA resets, account unlocks, VPN, device and software requests, and resolves common requests by acting in the identity and IT service management systems, handing the rest to the right resolver group with the context attached.",[18,313,314,334,21],"retail-and-ecommerce",[336,337],"it-and-engineering","operations",[26,28,27,339],"classification-and-routing","mainstream",6,[343,319,344,320,345,322],"7-Eleven Vietnam","Equinix","Mercari US",{"kpi":49,"label":324,"unit":325,"n":326,"nUpTo":300,"kind":327,"value":347,"qualifier":278,"claimant":348,"organization":345,"vendorReported":283},94,"vendor",{"slug":192,"title":350,"shortTitle":351,"definition":352,"status":9,"industries":353,"functions":355,"patterns":356,"audience":358,"autonomy":359,"adoptionStage":36,"evidenceCount":317,"publicEvidenceCount":317,"organizations":360,"bestGrade":231,"headline":366,"lastVerified":195,"indexable":283},"AI for recruitment screening and interview scheduling","Recruitment screening and scheduling","AI that answers candidates' questions, collects applications in conversation, schedules interviews and, where the organization chooses, assesses applications against the job requirements for a recruiter, who makes every selection decision. In the EU, the screening part is a high risk AI system under Annex III point 4 of the AI Act.",[18,19,354,20],"travel-and-hospitality",[23],[26,339,357,28],"prediction-and-scoring","customer-facing","copilot",[361,362,363,364,365],"Chipotle Mexican Grill","Gojob","U.S. Immigration and Customs Enforcement","Mastercard","Trace3",{"kpi":367,"label":368,"unit":325,"n":296,"nUpTo":300,"kind":327,"value":369,"qualifier":370,"claimant":280,"organization":364,"vendorReported":206},"processing-time-reduction","Cycle time reduction",90,"approximately",{"slug":193,"title":372,"shortTitle":373,"definition":374,"status":9,"industries":375,"functions":378,"patterns":380,"audience":34,"autonomy":382,"adoptionStage":340,"evidenceCount":63,"publicEvidenceCount":63,"organizations":383,"bestGrade":231,"headline":262,"lastVerified":195,"indexable":283},"AI enterprise knowledge search for employees","Enterprise knowledge search","An assistant that lets any employee ask a question in plain language and get a synthesized answer from the organization's own policies, procedures, product manuals and research, with citations to the source documents and only from documents the employee is allowed to see.",[18,313,376,377,19,20],"wealth-and-asset-management","insurance",[24,337,379],"customer-service",[27,26,381],"summarization","assist",[319,384,385,386],"Morgan Stanley","SIGNAL IDUNA","Wells Fargo",{"slug":194,"title":388,"shortTitle":389,"definition":390,"status":9,"industries":391,"functions":393,"patterns":395,"audience":34,"autonomy":382,"adoptionStage":36,"evidenceCount":398,"publicEvidenceCount":398,"organizations":399,"bestGrade":231,"headline":402,"lastVerified":230,"indexable":283},"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.",[18,313,377,392,19,21],"telecommunications",[23,379,394],"sales",[26,396,397],"voice-agent","content-generation",3,[319,400,401],"GoHealth","U.S. Department of Veterans Affairs",{"kpi":403,"label":404,"unit":325,"n":296,"nUpTo":300,"kind":327,"value":405,"qualifier":278,"claimant":348,"organization":400,"vendorReported":283},"conversion-rate-uplift","Conversion uplift",21,{"indexable":283,"reasons":407},[],[409,414,419,425,432,438,445,452,460,467,474,480,487,494,500,505,512,517,523,529,535,541,547,552,557,564,570,575,580,587,593,599,605,610],{"id":152,"label":410,"issuer":158,"region":159,"url":411,"description":412,"useCases":413,"indexable":283},"EU AI Act","https://eur-lex.europa.eu/eli/reg/2024/1689/oj","Regulation (EU) 2024/1689: risk based rules for AI systems, with obligations for high risk systems listed in Annex III and transparency duties under Article 50.",197,{"id":153,"label":415,"issuer":158,"region":159,"url":416,"description":417,"useCases":418,"indexable":283},"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":154,"label":420,"issuer":421,"region":239,"url":422,"description":423,"useCases":424,"indexable":283},"ISO/IEC 42001","ISO and IEC","https://www.iso.org/standard/81230.html","The international management system standard for AI.",110,{"id":426,"label":427,"issuer":428,"region":208,"url":429,"description":430,"useCases":431,"indexable":283},"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":433,"label":434,"issuer":158,"region":159,"url":435,"description":436,"useCases":437,"indexable":283},"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":439,"label":440,"issuer":441,"region":159,"url":442,"description":443,"useCases":444,"indexable":283},"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":446,"label":447,"issuer":448,"region":159,"url":449,"description":450,"useCases":451,"indexable":283},"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":453,"label":454,"issuer":455,"region":456,"url":457,"description":458,"useCases":459,"indexable":283},"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":461,"label":462,"issuer":463,"region":456,"url":464,"description":465,"useCases":466,"indexable":283},"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":468,"label":469,"issuer":470,"region":239,"url":471,"description":472,"useCases":473,"indexable":283},"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":475,"label":476,"issuer":477,"region":208,"url":478,"description":479,"useCases":473,"indexable":283},"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":481,"label":482,"issuer":483,"region":159,"url":484,"description":485,"useCases":486,"indexable":283},"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":488,"label":489,"issuer":490,"region":239,"url":491,"description":492,"useCases":493,"indexable":283},"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":495,"label":496,"issuer":158,"region":159,"url":497,"description":498,"useCases":499,"indexable":283},"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":501,"label":502,"issuer":158,"region":159,"url":503,"description":504,"useCases":499,"indexable":283},"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":506,"label":507,"issuer":508,"region":208,"url":509,"description":510,"useCases":511,"indexable":283},"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":513,"label":514,"issuer":158,"region":159,"url":515,"description":516,"useCases":276,"indexable":283},"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.",{"id":518,"label":519,"issuer":520,"region":208,"url":521,"description":522,"useCases":276,"indexable":283},"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":524,"label":525,"issuer":526,"region":239,"url":527,"description":528,"useCases":276,"indexable":283},"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":530,"label":531,"issuer":158,"region":159,"url":532,"description":533,"useCases":534,"indexable":283},"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":536,"label":537,"issuer":538,"region":208,"url":539,"description":540,"useCases":534,"indexable":283},"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":542,"label":543,"issuer":455,"region":456,"url":544,"description":545,"useCases":546,"indexable":283},"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":548,"label":549,"issuer":158,"region":159,"url":550,"description":551,"useCases":546,"indexable":283},"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":553,"label":554,"issuer":158,"region":159,"url":555,"description":556,"useCases":546,"indexable":283},"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":558,"label":559,"issuer":560,"region":159,"url":561,"description":562,"useCases":563,"indexable":283},"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":565,"label":566,"issuer":567,"region":208,"url":568,"description":569,"useCases":64,"indexable":283},"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":571,"label":572,"issuer":158,"region":159,"url":573,"description":574,"useCases":64,"indexable":283},"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":576,"label":577,"issuer":158,"region":159,"url":578,"description":579,"useCases":341,"indexable":283},"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":581,"label":582,"issuer":583,"region":584,"url":585,"description":586,"useCases":317,"indexable":283},"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":588,"label":589,"issuer":590,"region":159,"url":591,"description":592,"useCases":63,"indexable":283},"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":594,"label":595,"issuer":596,"region":159,"url":597,"description":598,"useCases":63,"indexable":283},"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":600,"label":601,"issuer":602,"region":456,"url":603,"description":604,"useCases":398,"indexable":283},"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":606,"label":607,"issuer":158,"region":159,"url":608,"description":609,"useCases":398,"indexable":283},"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":611,"label":612,"issuer":613,"region":208,"url":614,"description":615,"useCases":398,"indexable":283},"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.",1790598296806]