[{"data":1,"prerenderedAt":666},["ShallowReactive",2],{"uc-hr-and-policy-assistant":3,"uc-regulations":461},{"useCase":4,"evidence":197,"blitsAiDeployments":337,"benchmarks":338,"indicative":367,"related":370,"indexability":459,"includeUnpublished":203},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":16,"functions":21,"patterns":24,"channels":28,"audience":32,"autonomy":33,"adoptionStage":34,"problem":35,"problemStats":36,"howItWorks":37,"valueDrivers":38,"kpis":42,"indicativeValue":48,"macroEstimates":82,"feasibility":83,"implementation":95,"risk":141,"blitsAi":174,"faq":176,"related":186,"datePublished":192,"dateModified":192,"lastVerified":192,"changelog":193,"slug":196},"AI assistant for HR and policy questions","HR and policy assistant","HR chatbot for employee policy questions","An HR assistant answers leave, pay and policy questions from the organization's own documents. IBM reports a 94% containment rate of common questions for AskHR.","published","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.",[12,13,14,15],"HR chatbot","HR virtual agent","employee self service assistant","policy assistant",[17,18,19,20],"cross-industry","banking","technology","healthcare",[22,23],"human-resources","knowledge-management",[25,26,27],"rag-knowledge-assistant","conversational-agent","agentic-workflow",[29,30,31],"microsoft-teams","internal-tools","web-chat","employee-facing","supervised-agent","early-adopters","HR shared services answer the same questions every day: how many days of leave do I have left,\nwhere is my payslip, does the policy cover this expense, what happens to my benefits if I move\ncountry. The answers exist, but they are spread across policy PDFs, intranet pages and HR\nsystems, differ by country, entity and grade, and change every year. Employees raise tickets or\nemail a business partner, and HR spends skilled time on lookups.\n\nA generic chatbot makes this worse if it gives one answer to everyone. The value comes from\nanswers grounded in the current policy that applies to this person, plus the ability to complete\nthe simple transaction behind the question. The risk is the opposite failure: HR data is among\nthe most sensitive an organization holds, and some conversations (grievances, misconduct,\nwellbeing) must reach a person, not a bot.",[],"1. **Know who is asking.** The assistant runs inside the employee's signed in session and reads\n   only that person's attributes that matter for policy: country, entity, grade, contract type.\n2. **Retrieve the applicable policy.** Retrieval is filtered to the documents that apply to\n   that population, and the answer cites the policy and section it came from.\n3. **Read personal data only through the HR system.** Leave balances or payslip locations come\n   from HR system APIs scoped to the requester, never from documents about other people.\n4. **Start simple transactions.** Leave requests, employment verification letters or address\n   changes go through the HR system's normal workflow and approvals.\n5. **Route sensitive topics to people.** Grievances, disciplinary matters, harassment, health and\n   wellbeing are detected and handed to HR or employee assistance, with the employee's consent.",[39,40,41],"cost-to-serve","employee-productivity","speed",[43,44,45,46,47],"containment-rate","interactions-handled","employee-adoption","cost-reduction","processing-time-reduction",{"referenceOrg":49,"inputs":50,"formula":77,"currency":78,"period":79,"resultLabel":80,"caveat":81},"An organization with 20,000 employees",[51,56,63,70],{"key":52,"label":53,"low":54,"high":54,"unit":52,"note":55},"employees","Employees",20000,"The reference organization.",{"key":57,"label":58,"low":59,"high":60,"unit":61,"note":62},"queriesPerEmployee","HR questions and requests per employee per year that reach HR today",2,4,"queries per employee per year","Editorial assumption, replace with your HR case volume.",{"key":64,"label":65,"low":66,"high":67,"unit":68,"note":69},"containment","Share resolved by the assistant without HR staff",0.4,0.7,"fraction of queries","Conservative against the benchmark on this page (IBM reports a 94% containment rate of common questions for AskHR after years of refinement).",{"key":71,"label":72,"low":73,"high":74,"unit":75,"note":76},"costPerQuery","Cost of an HR handled query",10,20,"USD per query","Editorial assumption for a shared services centre. Replace with your own cost.","employees * queriesPerEmployee * containment * costPerQuery","USD","per year","HR handling cost avoided","Gross handling cost only. It leaves out the platform and integration cost, employee time saved by faster answers, and the effect of fewer errors from outdated policy copies. Savings usually show as capacity redeployed within HR, not as headcount.",[],{"complexity":84,"complexityNote":85,"dataPrerequisites":86,"integrations":90},"medium","A policy question answerer is quick to build. Personalization by country and grade, access scoping to the individual, and transactions in the HR system are where the effort goes, along with keeping policy documents current.",[87,88,89],"Current HR policies per country and entity, each with an owner and effective date","Employee attributes that decide which policy applies (country, entity, grade, contract)","The list of topics that must always go to a person",[91,92,93,94],"HR information system (for example Workday or SAP SuccessFactors) for balances and transactions","Payroll and benefits portals for links and documents","Identity provider for single sign on","HR case management for handover",{"steps":96,"guardrails":115,"humanInTheLoop":121,"kpisToInstrument":122,"failureModes":128},[97,100,103,106,109,112],{"title":98,"detail":99},"Map the question volume","Pull a year of HR tickets and emails and group them. Most volume sits in a few topics: leave, pay, benefits, letters and expenses. Start there.",{"title":101,"detail":102},"Fix the source documents first","Remove duplicates and old versions, tag each policy with the population it applies to and an effective date. The assistant can only be as current as this library.",{"title":104,"detail":105},"Scope retrieval and data to the person","Filter retrieval by the employee's attributes and read personal data only through HR system APIs scoped to the requester. Test that no answer can reveal another employee's data.",{"title":107,"detail":108},"Define the human topics","Agree with HR, legal and employee representatives which topics always go to a person and how the handover works, including confidential routes.",{"title":110,"detail":111},"Add transactions one at a time","Start with letters and leave requests that already have approval workflows, and let the HR system enforce the rules rather than the assistant.",{"title":113,"detail":114},"Consult before launch","Where works councils or unions have a say in employee monitoring tools, involve them early and document what is and is not logged.",[116,117,118,119,120],"Answers cite the policy and section, and the assistant refuses when no applicable policy is found","Personal data only through APIs scoped to the signed in employee","Automatic handover for grievances, misconduct, harassment, health and wellbeing","No decisions on pay, performance, promotion or discipline; the assistant informs, HR decides","Conversation logs with restricted access and a defined retention period","HR owns the policy content, every sensitive topic and every decision about an individual. HR business partners review a weekly sample of answers per country, and policy owners approve changes before they reach the knowledge base.",[123,124,125,126,127],"Containment per topic, counting a follow up ticket within seven days as not contained","Answer accuracy on a monthly sample checked by HR per country","Employee adoption and satisfaction","Share of sensitive conversations correctly handed over","Time to complete letters and leave requests",[129,132,135,138],{"title":130,"detail":131},"The wrong country's policy","A correct answer for Germany given to an employee in Singapore. Filter retrieval by the employee's attributes and test each country separately.",{"title":133,"detail":134},"Leaking another employee's data","Documents or logs that contain personal data are retrieved for the wrong person. Keep personal data out of the document index and scope every lookup.",{"title":136,"detail":137},"Automating what needs empathy","A distressed employee gets a policy extract. Detect sensitive topics and route to a person.",{"title":139,"detail":140},"Drift into decisions","The assistant starts screening internal applications or ranking requests. That changes its risk class and needs its own assessment.",{"euAiAct":142,"regulations":145,"guidance":151,"controls":167,"incidents":173},{"tier":143,"basis":144},"context-dependent","Answering policy questions and starting routine requests is limited risk, with the Article 50 duty to disclose AI. It becomes high risk under Annex III point 4 if it is used to make or support decisions on recruitment, promotion, termination, allocating tasks based on individual behaviour or personal traits, or the monitoring and evaluation of workers; an employer deploying it then must also inform workers' representatives and the affected workers before use (Article 26(7)). Sensitive topic detection should work on what the employee writes: inferring emotions of people in the workplace from biometric data such as voice or facial expressions is prohibited under Article 5(1)(f), except for medical or safety reasons.",[146,147,148,149,150],"eu-ai-act","gdpr","uk-gdpr","iso-42001","nist-ai-rmf",[152,158,162],{"title":153,"issuer":154,"region":155,"url":156,"note":157},"Annex III, high risk AI systems referred to in Article 6(2)","European Union","europe","https://artificialintelligenceact.eu/annex/3/","Point 4 lists employment and worker management uses that would make an HR assistant high risk.",{"title":159,"issuer":154,"region":155,"url":160,"note":161},"Article 50, transparency obligations for providers and deployers of certain AI systems","https://artificialintelligenceact.eu/article/50/","Employees must know they are interacting with AI unless this is obvious from the context.",{"title":163,"issuer":164,"region":155,"url":165,"note":166},"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/","Relevant to how conversation logs about employees are kept, used and disclosed under UK GDPR. The ICO says the guidance is under review after the Data (Use and Access) Act.",[168,169,170,171,172],"Data protection impact assessment covering logs, retention and access to conversations","Inventory entry with an owner in HR and a documented list of topics routed to people","Access to conversation logs restricted and audited","Consultation with employee representatives where required","Periodic accuracy review per country and policy area",[],{"howToBuild":175},"On Blits.ai this is an **AI agent** in **Microsoft Teams** or the intranet, grounded in a\n**knowledge base** of HR policies with hybrid retrieval and document version control, so every\nanswer can cite the current version. **Custom functions** call the HR system's APIs (the\nintegration catalog includes Workday and SAP) for balances and transactions, passing only the\nrequesting employee's identifier so every lookup is scoped to that person.\n\nA **flow** detects sensitive topics and triggers **human handover** to HR, while **guardrails**\nand **PII masking** keep personal data out of prompts and logs. **Role based access control**\nlimits who can read conversation logs, and the GDPR toolkit covers retention and removal\nrequests. **Multi language** support serves employees in their own language, and **test\nsuites** check answers per country before every policy change goes live. The platform is model\nagnostic and can run in the EU or UAE region.",[177,180,183],{"question":178,"answer":179},"How much of HR's question volume can an assistant take?","A mature deployment takes most routine questions. IBM reports a 94% containment rate of common questions for AskHR, which recorded more than 11.5 million employee interactions in 2024, and says it helped contribute to a 40% reduction in HR operating costs over four years. That took several years of refinement; plan for lower rates at launch.",{"question":181,"answer":182},"Is an HR chatbot high risk under the EU AI Act?","Not when it answers policy questions and starts routine requests. It becomes high risk under Annex III point 4 if it is used for recruitment, promotion, termination, allocating tasks based on behaviour or personal traits, or evaluating employees, which needs a separate assessment.",{"question":184,"answer":185},"Should IT and HR share one assistant?","Often yes: employees do not care which department owns the answer. Bank of America's Erica for Employees started with IT support and added HR topics such as benefits and payroll forms, and Vituity's assistant covers both IT and HR requests. Keep separate content owners and data scopes behind the single front door.",[187,188,189,190,191],"employee-onboarding-assistant","it-service-desk-resolution-agent","enterprise-knowledge-search","policy-drafting-and-gap-analysis","recruitment-screening-and-interview-scheduling","2026-09-27",[194],{"date":192,"note":195},"First published","hr-and-policy-assistant",[198,239,281,315],{"title":199,"useCases":200,"organization":201,"vendors":206,"summary":209,"stage":210,"year":211,"channels":212,"languages":213,"metrics":215,"outcomeDisclosed":228,"sources":229,"verification":233,"grade":236,"id":237,"organizationSlug":238},"Bank of America: Erica for Employees, the internal IT and HR assistant",[188,196],{"name":202,"anonymized":203,"country":204,"region":205,"industry":18},"Bank of America",false,"US","north-america",[207],{"name":202,"role":208},"in-house","Bank of America launched Erica for Employees in 2020, building on its customer facing assistant, to give staff technology support such as mobile device password resets and device activation. In 2023 it was extended to HR topics such as where to review health benefits and how to find payroll and tax forms. The bank reports that most employees use it and that it has more than halved calls into the IT service desk.","scaled",2020,[30],[214],"en",[216,224],{"kpi":45,"value":217,"unit":218,"qualifier":219,"period":220,"claimant":221,"quote":222,"sourceUrl":223},90,"percent","at-least","as of April 2025","organization","Today, over 90% of employees use Erica for Employees, with the virtual assistant having reduced calls into the IT service desk by more than 50%.","https://newsroom.bankofamerica.com/content/newsroom/press-releases/2025/04/ai-adoption-by-bofa-s-global-workforce-improves-productivity--cl.html",{"kpi":225,"value":226,"unit":218,"qualifier":219,"period":227,"claimant":221,"quote":222,"sourceUrl":223},"contact-deflection",50,"calls into the IT service desk, as of April 2025",true,[230],{"url":223,"title":231,"publisher":202,"date":232},"AI Adoption by BofA's Global Workforce Improves Productivity, Client Service","2025-04-08",{"level":234,"checkedAt":235},"source-verified","2026-09-26","B","bank-of-america-erica-for-employees","bank-of-america",{"title":240,"useCases":241,"organization":242,"vendors":245,"summary":247,"stage":210,"year":248,"channels":249,"languages":250,"metrics":251,"outcomeDisclosed":228,"sources":274,"verification":278,"grade":236,"id":279,"organizationSlug":280},"IBM: AskHR, the virtual HR assistant for employees and managers",[196],{"name":243,"anonymized":203,"country":204,"region":244,"industry":19},"IBM","global",[246],{"name":243,"role":208},"IBM's internal virtual agent AskHR automates more than 80 HR tasks, from payslip and sickness policy questions to job verification letters and vacation requests, and lets managers start transfers and organization changes in SAP SuccessFactors. AskHR has been refined since 2016; IBM added watsonx Orchestrate for generative and agentic automation in 2025. IBM reports high containment, fewer tickets and lower HR operating cost from the assistant over that longer period.",2016,[30],[214],[252,258,262,265,270],{"kpi":43,"value":253,"unit":218,"qualifier":254,"period":255,"claimant":221,"quote":256,"sourceUrl":257},94,"exact","common questions","AskHR also achieved a 94% containment rate of common questions, has led to a 75% reduction in support tickets raised since 2016, and created more than 11.5 million employee interactions in 2024 alone.","https://www.ibm.com/case-studies/ibm-askhr",{"kpi":44,"value":259,"unit":260,"qualifier":219,"period":261,"claimant":221,"quote":256,"sourceUrl":257},11500000,"count","calendar year 2024",{"kpi":225,"value":263,"unit":218,"qualifier":254,"period":264,"claimant":221,"quote":256,"sourceUrl":257},75,"HR support tickets raised, since 2016",{"kpi":46,"value":266,"unit":218,"qualifier":254,"period":267,"baseline":268,"claimant":221,"quote":269,"sourceUrl":257},40,"over four years","HR team operational costs four years earlier","The AI agent helped contribute to a 40% reduction in the HR team’s operational costs over the past four years.",{"kpi":45,"value":271,"unit":218,"qualifier":254,"period":272,"claimant":221,"quote":273,"sourceUrl":257},99,"managers","The adoption of AskHR has reached 99% among managers.",[275],{"url":257,"title":276,"publisher":243,"date":277},"IBM AskHR","2025-08-21",{"level":234,"checkedAt":235},"ibm-askhr",null,{"title":282,"useCases":283,"organization":285,"vendors":287,"summary":291,"stage":292,"year":293,"channels":294,"languages":295,"metrics":296,"outcomeDisclosed":228,"sources":302,"verification":312,"grade":313,"id":314,"organizationSlug":280},"Turing: AI drafted replies to HR support tickets",[196,284],"email-and-ticket-reply-drafting",{"name":286,"anonymized":203,"country":204,"region":205,"industry":19},"Turing",[288],{"name":289,"role":290},"Google","platform","Turing (listed by Google Cloud as Turing Enterprises), an AI company headquartered in San Francisco, built a custom AI model trained on its internal knowledge that drafts replies to HR support tickets. Google Cloud reports a one third cut in ticket processing time after two days of development. A plan to automate 60% of its 52,000 annual HR tickets with Gemini Gems is a target, not a result.","production",2025,[30],[214],[297],{"kpi":47,"value":298,"unit":218,"qualifier":254,"claimant":299,"quote":300,"sourceUrl":301},33,"vendor","Turing also built a custom AI model trained on internal knowledge to draft replies to HR support tickets, reducing ticket processing time by 33% after two days of development.","https://cloud.google.com/transform/101-real-world-generative-ai-use-cases-from-industry-leaders",[303,306,309],{"url":301,"title":304,"publisher":305},"Real world gen AI use cases from the world's leading organizations","Google Cloud",{"url":307,"title":308,"publisher":286},"https://www.turing.com/company","About Turing",{"url":310,"title":311,"publisher":286},"https://www.turing.com/terms-of-service","Terms of Service",{"level":234,"checkedAt":192},"C","turing-hr-ticket-reply-drafting",{"title":316,"useCases":317,"organization":318,"vendors":320,"summary":323,"stage":210,"year":211,"channels":324,"languages":325,"metrics":326,"outcomeDisclosed":228,"sources":332,"verification":335,"grade":313,"id":336,"organizationSlug":280},"Vituity: AI assistant for IT and HR requests in a physician group",[188,196],{"name":319,"anonymized":203,"country":204,"region":205,"industry":20},"Vituity",[321],{"name":322,"role":290},"Moveworks","Vituity, a healthcare organization owned and led by a partnership of nearly 5,000 physicians, deployed a Moveworks AI assistant called Otto in Microsoft Teams in April 2020, connected to ServiceNow, Okta and internal knowledge. It started with IT workflows such as password resets, account provisioning and software access, then expanded into HR questions and other operational domains. The vendor reports that the average time to close issues fell by one full business day and that first line help desk capacity was freed.",[29],[214],[327],{"kpi":328,"value":266,"unit":218,"qualifier":254,"period":329,"claimant":299,"quote":330,"sourceUrl":331},"productivity-gain","level 1 help desk capacity","It now absorbs a significant share of routine IT and HR requests — including password resets, software access, HR questions, and account provisioning— freeing up 40% of level 1 help-desk capacity.","https://www.moveworks.com/us/en/customers/vituity-helps-physicians-with-moveworks-proactive-it-support",[333],{"url":331,"title":334,"publisher":322},"Vituity helps physicians with proactive IT support",{"level":234,"checkedAt":235},"vituity-it-and-hr-assistant",1,[339,347,352,357,362],{"kpi":45,"label":340,"unit":218,"aggregate":228,"higherIsBetter":228,"n":59,"nUpTo":341,"median":342,"min":217,"max":271,"byClaimant":343,"vendorOnly":203,"points":344},"Employee adoption",0,94.5,{"organization":59,"vendor":341,"regulator":341,"independent":341},[345,346],{"evidenceId":279,"organization":243,"value":271,"qualifier":254,"claimant":221,"grade":236,"pooled":228},{"evidenceId":237,"organization":202,"value":217,"qualifier":219,"claimant":221,"grade":236,"pooled":228},{"kpi":43,"label":348,"unit":218,"aggregate":228,"higherIsBetter":228,"n":337,"nUpTo":341,"median":253,"min":253,"max":253,"byClaimant":349,"vendorOnly":203,"points":350},"Containment rate",{"organization":337,"vendor":341,"regulator":341,"independent":341},[351],{"evidenceId":279,"organization":243,"value":253,"qualifier":254,"claimant":221,"grade":236,"pooled":228},{"kpi":46,"label":353,"unit":218,"aggregate":228,"higherIsBetter":228,"n":337,"nUpTo":341,"median":266,"min":266,"max":266,"byClaimant":354,"vendorOnly":203,"points":355},"Cost reduction",{"organization":337,"vendor":341,"regulator":341,"independent":341},[356],{"evidenceId":279,"organization":243,"value":266,"qualifier":254,"claimant":221,"grade":236,"pooled":228},{"kpi":47,"label":358,"unit":218,"aggregate":228,"higherIsBetter":228,"n":337,"nUpTo":341,"median":298,"min":298,"max":298,"byClaimant":359,"vendorOnly":228,"points":360},"Cycle time reduction",{"organization":341,"vendor":337,"regulator":341,"independent":341},[361],{"evidenceId":314,"organization":286,"value":298,"qualifier":254,"claimant":299,"grade":313,"pooled":228},{"kpi":44,"label":363,"unit":260,"aggregate":203,"higherIsBetter":228,"n":337,"nUpTo":341,"median":259,"min":259,"max":259,"byClaimant":364,"vendorOnly":203,"points":365},"Interactions handled",{"organization":337,"vendor":341,"regulator":341,"independent":341},[366],{"evidenceId":279,"organization":243,"value":259,"qualifier":219,"claimant":221,"grade":236,"pooled":228},{"low":368,"high":369},160000,1120000,[371,385,405,421,440],{"slug":187,"title":372,"shortTitle":373,"definition":374,"status":9,"industries":375,"functions":378,"patterns":379,"audience":32,"autonomy":33,"adoptionStage":34,"evidenceCount":60,"publicEvidenceCount":380,"organizations":381,"bestGrade":236,"headline":280,"lastVerified":192,"indexable":228},"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.",[17,376,377,20],"government","professional-services",[22,23],[26,25,27],3,[382,383,384],"American Addiction Centers","KPMG","U.S. Department of Agriculture",{"slug":188,"title":386,"shortTitle":387,"definition":388,"status":9,"industries":389,"functions":391,"patterns":394,"audience":32,"autonomy":33,"adoptionStage":396,"evidenceCount":397,"publicEvidenceCount":398,"organizations":399,"bestGrade":236,"headline":403,"lastVerified":192,"indexable":228},"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.",[17,18,19,390,20],"retail-and-ecommerce",[392,393],"it-and-engineering","operations",[26,27,25,395],"classification-and-routing","mainstream",8,6,[400,202,401,243,402,319],"7-Eleven Vietnam","Equinix","Mercari US",{"kpi":45,"label":340,"unit":218,"n":59,"nUpTo":341,"kind":404,"value":253,"qualifier":254,"claimant":299,"organization":402,"vendorReported":228},"reported",{"slug":189,"title":406,"shortTitle":407,"definition":408,"status":9,"industries":409,"functions":412,"patterns":414,"audience":32,"autonomy":416,"adoptionStage":396,"evidenceCount":60,"publicEvidenceCount":60,"organizations":417,"bestGrade":236,"headline":280,"lastVerified":192,"indexable":228},"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.",[17,18,410,411,376,377],"wealth-and-asset-management","insurance",[23,393,413],"customer-service",[25,26,415],"summarization","assist",[202,418,419,420],"Morgan Stanley","SIGNAL IDUNA","Wells Fargo",{"slug":190,"title":422,"shortTitle":423,"definition":424,"status":9,"industries":425,"functions":427,"patterns":430,"audience":32,"autonomy":433,"adoptionStage":434,"segment":435,"evidenceCount":380,"publicEvidenceCount":380,"organizations":436,"bestGrade":236,"headline":280,"lastVerified":235,"indexable":228},"AI for policy drafting and policy gap analysis","Policy drafting and gaps","An assistant that takes a new or changed obligation, finds every internal policy, standard and procedure it touches, flags clauses that now conflict or are silent, and drafts the updated wording in house style as a redline for the policy owner to approve.",[17,18,411,426,376],"capital-markets",[428,429,23],"regulatory-compliance","legal",[25,431,432,415],"content-generation","document-processing","copilot","emerging","second-line",[437,438,439],"Federal Deposit Insurance Corporation","Administration for Children and Families","Health Resources and Services Administration",{"slug":191,"title":441,"shortTitle":442,"definition":443,"status":9,"industries":444,"functions":446,"patterns":447,"audience":449,"autonomy":433,"adoptionStage":34,"evidenceCount":450,"publicEvidenceCount":450,"organizations":451,"bestGrade":236,"headline":457,"lastVerified":192,"indexable":228},"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.",[17,376,445,377],"travel-and-hospitality",[22],[26,395,448,27],"prediction-and-scoring","customer-facing",5,[452,453,454,455,456],"Chipotle Mexican Grill","Gojob","U.S. Immigration and Customs Enforcement","Mastercard","Trace3",{"kpi":47,"label":358,"unit":218,"n":337,"nUpTo":341,"kind":404,"value":217,"qualifier":458,"claimant":221,"organization":455,"vendorReported":203},"approximately",{"indexable":228,"reasons":460},[],[462,467,472,478,484,490,496,503,511,518,524,530,537,544,550,555,562,568,574,580,586,592,597,602,607,614,620,625,630,637,643,649,655,660],{"id":146,"label":463,"issuer":154,"region":155,"url":464,"description":465,"useCases":466,"indexable":228},"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":147,"label":468,"issuer":154,"region":155,"url":469,"description":470,"useCases":471,"indexable":228},"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":149,"label":473,"issuer":474,"region":244,"url":475,"description":476,"useCases":477,"indexable":228},"ISO/IEC 42001","ISO and IEC","https://www.iso.org/standard/81230.html","The international management system standard for AI.",110,{"id":150,"label":479,"issuer":480,"region":205,"url":481,"description":482,"useCases":483,"indexable":228},"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":485,"label":486,"issuer":154,"region":155,"url":487,"description":488,"useCases":489,"indexable":228},"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":148,"label":491,"issuer":492,"region":155,"url":493,"description":494,"useCases":495,"indexable":228},"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":497,"label":498,"issuer":499,"region":155,"url":500,"description":501,"useCases":502,"indexable":228},"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":504,"label":505,"issuer":506,"region":507,"url":508,"description":509,"useCases":510,"indexable":228},"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":512,"label":513,"issuer":514,"region":507,"url":515,"description":516,"useCases":517,"indexable":228},"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":519,"label":520,"issuer":521,"region":244,"url":522,"description":523,"useCases":74,"indexable":228},"pci-dss","PCI DSS","PCI Security Standards Council","https://www.pcisecuritystandards.org/","Security standard for any system that stores, processes or transmits cardholder data.",{"id":525,"label":526,"issuer":527,"region":205,"url":528,"description":529,"useCases":74,"indexable":228},"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":531,"label":532,"issuer":533,"region":155,"url":534,"description":535,"useCases":536,"indexable":228},"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":538,"label":539,"issuer":540,"region":244,"url":541,"description":542,"useCases":543,"indexable":228},"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":545,"label":546,"issuer":154,"region":155,"url":547,"description":548,"useCases":549,"indexable":228},"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":551,"label":552,"issuer":154,"region":155,"url":553,"description":554,"useCases":549,"indexable":228},"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":556,"label":557,"issuer":558,"region":205,"url":559,"description":560,"useCases":561,"indexable":228},"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":563,"label":564,"issuer":154,"region":155,"url":565,"description":566,"useCases":567,"indexable":228},"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":569,"label":570,"issuer":571,"region":205,"url":572,"description":573,"useCases":567,"indexable":228},"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":575,"label":576,"issuer":577,"region":244,"url":578,"description":579,"useCases":567,"indexable":228},"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":581,"label":582,"issuer":154,"region":155,"url":583,"description":584,"useCases":585,"indexable":228},"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":587,"label":588,"issuer":589,"region":205,"url":590,"description":591,"useCases":585,"indexable":228},"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":593,"label":594,"issuer":506,"region":507,"url":595,"description":596,"useCases":73,"indexable":228},"mas-notice-626","MAS Notice 626","https://www.mas.gov.sg/regulation/notices/notice-626","Singapore's anti money laundering and counter terrorism financing requirements for banks.",{"id":598,"label":599,"issuer":154,"region":155,"url":600,"description":601,"useCases":73,"indexable":228},"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":603,"label":604,"issuer":154,"region":155,"url":605,"description":606,"useCases":73,"indexable":228},"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":608,"label":609,"issuer":610,"region":155,"url":611,"description":612,"useCases":613,"indexable":228},"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":615,"label":616,"issuer":617,"region":205,"url":618,"description":619,"useCases":397,"indexable":228},"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":621,"label":622,"issuer":154,"region":155,"url":623,"description":624,"useCases":397,"indexable":228},"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":626,"label":627,"issuer":154,"region":155,"url":628,"description":629,"useCases":398,"indexable":228},"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":631,"label":632,"issuer":633,"region":634,"url":635,"description":636,"useCases":450,"indexable":228},"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":638,"label":639,"issuer":640,"region":155,"url":641,"description":642,"useCases":60,"indexable":228},"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":644,"label":645,"issuer":646,"region":155,"url":647,"description":648,"useCases":60,"indexable":228},"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":650,"label":651,"issuer":652,"region":507,"url":653,"description":654,"useCases":380,"indexable":228},"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":656,"label":657,"issuer":154,"region":155,"url":658,"description":659,"useCases":380,"indexable":228},"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":661,"label":662,"issuer":663,"region":205,"url":664,"description":665,"useCases":380,"indexable":228},"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.",1790598296967]