[{"data":1,"prerenderedAt":806},["ShallowReactive",2],{"uc-hub-pattern-anomaly-detection":3},{"type":4,"typeLabel":5,"term":6,"includeUnpublished":10,"indexable":11,"stats":12,"useCases":24,"benchmarks":653,"topIndustries":736,"topFunctions":756,"topPatterns":774,"stageMix":775,"regionMix":788,"organizations":805,"other":120},"pattern","AI pattern",{"id":7,"label":8,"description":9},"anomaly-detection","Anomaly detection","Models that flag unusual behaviour in transactions, networks or processes for review.",false,true,{"useCases":13,"publicDeployments":14,"blitsAiDeployments":15,"organizations":16,"countries":17,"outcomeDisclosureRate":18,"gradeMix":19},40,134,3,122,23,57,{"A":20,"B":21,"C":22,"D":23},0,72,61,1,[25,61,82,103,122,139,153,168,188,202,217,231,255,278,295,310,322,333,348,367,380,399,416,429,441,451,462,477,492,504,517,529,541,554,568,585,598,610,620,634],{"slug":26,"title":27,"shortTitle":28,"definition":29,"status":30,"industries":31,"functions":33,"patterns":36,"audience":40,"autonomy":41,"adoptionStage":42,"segment":43,"evidenceCount":44,"publicEvidenceCount":44,"organizations":45,"bestGrade":51,"headline":52,"lastVerified":60,"indexable":11},"autonomous-network-operations","Agentic AI for autonomous, intent based network operations","Autonomous network operations","AI agents that run closed loops over a telecom network: they take an intent from the operator (for example a latency or availability target for a service), observe the network, diagnose deviations and execute corrective actions across radio, transport and core, within guardrails set by engineers and with human approval for major changes.","published",[32],"telecommunications",[34,35],"network-operations","it-and-engineering",[37,7,38,39],"agentic-workflow","prediction-and-scoring","classification-and-routing","back-office","supervised-agent","emerging","network",6,[46,47,48,49,50],"Deutsche Telekom","du","KDDI","stc Group","Telstra","B",{"kpi":53,"label":54,"unit":55,"n":23,"nUpTo":20,"kind":56,"value":57,"qualifier":58,"claimant":59,"organization":46,"vendorReported":10},"processing-time-reduction","Cycle time reduction","percent","reported",95,"at-least","organization","2026-09-26",{"slug":62,"title":63,"shortTitle":64,"definition":65,"status":30,"industries":66,"functions":69,"patterns":70,"audience":71,"autonomy":41,"adoptionStage":72,"evidenceCount":73,"publicEvidenceCount":73,"organizations":74,"bestGrade":77,"headline":78,"lastVerified":81,"indexable":11},"cloud-cost-optimization-agent","AI agent for cloud cost optimization and FinOps","Cloud cost optimization agent","An AI agent that continuously reads an organization's cloud usage and billing data, uses machine learning to separate normal spend from waste, and either rightsizes resources and buys a mix of committed capacity matched to forecast usage on its own within set limits, or proposes higher risk changes for an engineer to approve.",[67,68],"cross-industry","technology",[35],[7,38,37],"employee-facing","early-adopters",2,[75,76],"Akamai Technologies","VERMEG","C",{"kpi":79,"label":80,"unit":55,"n":23,"nUpTo":20,"kind":56,"value":13,"qualifier":58,"claimant":59,"organization":75,"vendorReported":10},"cost-reduction","Cost reduction","2026-09-28",{"slug":83,"title":84,"shortTitle":85,"definition":86,"status":30,"industries":87,"functions":89,"patterns":91,"audience":71,"autonomy":93,"adoptionStage":72,"evidenceCount":73,"publicEvidenceCount":73,"organizations":94,"bestGrade":77,"headline":97,"lastVerified":81,"indexable":11},"data-quality-monitoring-agent","AI agent for data quality monitoring and observability","Data quality monitoring agent","An AI agent that watches data pipelines and tables continuously, uses machine learning to learn the normal pattern of freshness, volume, schema and distribution for each one, flags anomalies before they reach a dashboard or a downstream model, and traces the lineage back to the change that caused them so an engineer can fix the source, not just the symptom.",[67,68,88],"retail-and-ecommerce",[35,90],"analytics-and-reporting",[7,39,92],"summarization","assist",[95,96],"Contentsquare","SeatGeek",{"kpi":98,"label":99,"unit":55,"n":23,"nUpTo":20,"kind":56,"value":100,"qualifier":101,"claimant":102,"organization":96,"vendorReported":11},"productivity-gain","Productivity gain",50,"exact","vendor",{"slug":104,"title":105,"shortTitle":106,"definition":107,"status":30,"industries":108,"functions":109,"patterns":112,"audience":116,"autonomy":41,"adoptionStage":42,"segment":117,"evidenceCount":73,"publicEvidenceCount":23,"organizations":118,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"network-outage-communication-agent","AI agent for network outage detection and customer communication","Outage communication","An AI agent that turns network alarms into a clear picture of which customers are affected by an outage and why, tells them proactively by message, app or phone with a cause and an estimated fix time, answers their questions during the incident, and updates them until service is restored.",[32],[110,34,111],"customer-service","field-service",[7,39,113,114,115],"content-generation","conversational-agent","voice-agent","customer-facing","front-office",[119],"Comcast",null,"2026-09-27",{"slug":123,"title":124,"shortTitle":125,"definition":126,"status":30,"industries":127,"functions":129,"patterns":131,"audience":40,"autonomy":41,"adoptionStage":72,"segment":40,"evidenceCount":73,"publicEvidenceCount":73,"organizations":133,"bestGrade":77,"headline":136,"lastVerified":81,"indexable":11},"travel-and-expense-audit-agent","AI agent for travel and expense report audit","Travel and expense audit","An AI agent that checks every travel and expense report line against policy, receipts and prior submissions instead of a small manual sample, flags duplicates, altered receipts and policy violations with the evidence attached, and auto approves the clean majority so auditors spend their time on the reports that are genuinely risky.",[67,128,68],"pharma-and-life-sciences",[130],"finance-and-accounting",[132,7,39,37],"document-processing",[134,135],"Databricks","Takeda",{"kpi":137,"label":138,"unit":55,"n":73,"nUpTo":20,"kind":56,"value":21,"qualifier":101,"claimant":102,"organization":134,"vendorReported":11},"automation-rate","Automation rate",{"slug":140,"title":141,"shortTitle":142,"definition":143,"status":30,"industries":144,"functions":146,"patterns":148,"audience":40,"autonomy":93,"adoptionStage":72,"segment":149,"evidenceCount":73,"publicEvidenceCount":73,"organizations":150,"bestGrade":77,"headline":120,"lastVerified":81,"indexable":11},"smart-meter-analytics","AI analytics for smart meter and AMI data","Smart meter analytics","AI that turns the flood of readings from smart electricity, gas and water meters into usable information: it monitors meter and network health at scale, estimates which appliances drive a household's usage from the meter signal alone, flags unusual consumption, and targets efficiency and electrification programmes at the customers who will benefit most, instead of a utility treating every meter and every customer the same way.",[145],"energy-and-utilities",[147,90],"operations",[7,38],"metering-and-billing",[151,152],"Consolidated Edison (Con Edison)","Southern California Gas Company (SoCalGas)",{"slug":154,"title":155,"shortTitle":156,"definition":157,"status":30,"industries":158,"functions":160,"patterns":161,"audience":71,"autonomy":93,"adoptionStage":72,"segment":162,"evidenceCount":73,"publicEvidenceCount":73,"organizations":163,"bestGrade":51,"headline":166,"lastVerified":81,"indexable":11},"hospital-bed-and-staff-capacity-command-center","AI command center for hospital bed and staff capacity planning","Hospital capacity command center","An AI powered operations center that predicts patient admissions, discharges and transfers across a hospital or health system, and helps a team of coordinators sitting in one room sequence real time bed assignments, staffing levels and patient moves, so patients get into the right bed faster and existing capacity is used fully without adding beds.",[159],"healthcare",[147,90],[38,39,7],"hospital operations",[164,165],"Humber River Health","Johns Hopkins Medicine",{"kpi":53,"label":54,"unit":55,"n":73,"nUpTo":20,"kind":56,"value":167,"qualifier":101,"claimant":59,"organization":165,"vendorReported":10},38,{"slug":169,"title":170,"shortTitle":171,"definition":172,"status":30,"industries":173,"functions":178,"patterns":181,"audience":71,"autonomy":182,"adoptionStage":42,"segment":183,"evidenceCount":15,"publicEvidenceCount":15,"organizations":184,"bestGrade":51,"headline":120,"lastVerified":81,"indexable":11},"model-risk-validation-copilot","AI copilot for model risk validation and monitoring","Model risk validation","A copilot for independent model validation and review, whether run by a bank's validation function, an external tester or a supervisor, that checks model documentation against the model risk standard, generates and scores challenger tests (for generative AI, often with an LLM as a judge calibrated against human experts), watches production models for drift and drafts and consistency checks the validation report. An accountable validator owns every conclusion.",[174,175,176,177],"banking","insurance","capital-markets","wealth-and-asset-management",[179,180],"risk-management","regulatory-compliance",[37,132,113,7],"copilot","second-line",[185,186,187],"European Central Bank (ECB Banking Supervision)","Standard Chartered","United Overseas Bank (UOB)",{"slug":189,"title":190,"shortTitle":191,"definition":192,"status":30,"industries":193,"functions":194,"patterns":195,"audience":71,"autonomy":182,"adoptionStage":72,"segment":43,"evidenceCount":44,"publicEvidenceCount":44,"organizations":197,"bestGrade":51,"headline":201,"lastVerified":121,"indexable":11},"network-fault-triage-copilot","AI copilot for network operations centre fault triage","NOC fault triage copilot","AI in the network operations centre (NOC) that correlates alarms and performance data from radio, transport, core and fixed networks into a small number of probable faults, ranks them by customer impact, proposes the likely root cause and fix from runbooks, vendor documentation and past tickets, and routes the ticket to the right team, while an engineer decides what to change.",[32],[34,147],[7,39,196,92,37],"rag-knowledge-assistant",[198,46,48,199,50,200],"Bell Canada","Orange","Vodafone",{"kpi":53,"label":54,"unit":55,"n":23,"nUpTo":20,"kind":56,"value":57,"qualifier":58,"claimant":59,"organization":46,"vendorReported":10},{"slug":203,"title":204,"shortTitle":205,"definition":206,"status":30,"industries":207,"functions":208,"patterns":209,"audience":40,"autonomy":41,"adoptionStage":210,"evidenceCount":211,"publicEvidenceCount":211,"organizations":212,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"retail-demand-forecasting-and-replenishment","AI demand forecasting and automated replenishment for retail","Demand forecasting and replenishment","Machine learning that forecasts demand for every item in every store or fulfillment center, day by day, from sales history, promotions, prices, weather and local events, and turns the forecast into automatic store and warehouse orders within limits set by planners, who handle the exceptions.",[88],[147,90],[38,7],"mainstream",4,[213,214,215,216],"Albert Heijn","Morrisons","One Stop","Walmart",{"slug":218,"title":219,"shortTitle":220,"definition":221,"status":30,"industries":222,"functions":223,"patterns":225,"audience":71,"autonomy":93,"adoptionStage":72,"segment":226,"evidenceCount":15,"publicEvidenceCount":15,"organizations":227,"bestGrade":77,"headline":120,"lastVerified":121,"indexable":11},"credit-early-warning-monitoring","AI early warning and covenant monitoring for loan portfolios","Credit early warning and covenants","A monitoring system that tracks covenant tests and borrower reporting across a loan book, reads financials, filings and news, and combines them with payment and sector signals to flag borrowers whose credit is deteriorating, with the evidence and a suggested next step for the relationship manager.",[174],[179,224],"lending-and-credit",[7,132,37,92],"lending",[228,229,230],"OakNorth Bank","PNC Financial Services","Sumitomo Mitsui Banking Corporation",{"slug":232,"title":233,"shortTitle":234,"definition":235,"status":30,"industries":236,"functions":238,"patterns":240,"audience":71,"autonomy":41,"adoptionStage":72,"segment":241,"evidenceCount":242,"publicEvidenceCount":242,"organizations":243,"bestGrade":51,"headline":251,"lastVerified":121,"indexable":11},"aml-alert-triage","AI for AML transaction monitoring alert triage","AML alert triage","Machine learning and AI agents that score anti money laundering alerts for genuine risk, close clear false positives with a written and stored rationale, and hand investigators the remaining alerts already enriched with the customer, counterparty and transaction context.",[174,237],"payments",[239],"financial-crime-compliance",[38,7,37,92],"middle-office",8,[244,245,246,247,248,249,187,250],"Australia Post","BMO and Amalgamated Bank","HSBC","Nexo","Ratepay","Shift4","Uphold",{"kpi":252,"label":253,"unit":55,"n":73,"nUpTo":20,"kind":56,"value":254,"qualifier":101,"claimant":102,"organization":249,"vendorReported":11},"false-positive-reduction","False positive reduction",86,{"slug":256,"title":257,"shortTitle":258,"definition":259,"status":30,"industries":260,"functions":262,"patterns":265,"audience":40,"autonomy":41,"adoptionStage":72,"segment":117,"evidenceCount":44,"publicEvidenceCount":44,"organizations":267,"bestGrade":51,"headline":273,"lastVerified":60,"indexable":11},"application-and-identity-fraud-detection","AI for application and identity fraud detection","Application and identity fraud","AI that checks incoming account and loan applications for forged or AI generated documents, synthetic and stolen identities, and coordinated application rings, by analysing documents, device and application data across the whole queue and cross checking against bureau and official sources.",[174,237,67,261,32],"government",[263,264,224],"fraud-prevention","onboarding-and-kyc",[132,7,266,38],"computer-vision",[268,269,270,271,272,50],"BCU","Close Brothers Motor Finance","CNG Holdings","Department for Work and Pensions","Payoneer",{"kpi":274,"label":275,"unit":276,"n":23,"nUpTo":20,"kind":56,"value":277,"qualifier":101,"claimant":59,"organization":271,"vendorReported":10},"detection-rate-improvement","Detection improvement","multiplier",2.5,{"slug":279,"title":280,"shortTitle":281,"definition":282,"status":30,"industries":283,"functions":284,"patterns":287,"audience":40,"autonomy":93,"adoptionStage":72,"evidenceCount":288,"publicEvidenceCount":288,"organizations":289,"bestGrade":51,"headline":294,"lastVerified":121,"indexable":11},"benefit-fraud-and-error-detection","AI for benefit fraud and error detection in social security","Benefit fraud and error detection","Risk models that help a social security or benefits agency decide which claims, payments and recipients to check for fraud or error, so that caseworkers verify the riskiest cases first, while every decision on entitlement stays with a person and the model is tested for fairness before and during use.",[261],[263,285,286],"citizen-services","case-management",[38,7],5,[290,271,291,292,293],"Centers for Medicare and Medicaid Services","Gemeente Rotterdam","U.S. Department of the Treasury, Bureau of the Fiscal Service","Uitvoeringsinstituut Werknemersverzekeringen (UWV)",{"kpi":274,"label":275,"unit":276,"n":23,"nUpTo":20,"kind":56,"value":277,"qualifier":101,"claimant":59,"organization":271,"vendorReported":10},{"slug":296,"title":297,"shortTitle":298,"definition":299,"status":30,"industries":300,"functions":303,"patterns":304,"audience":40,"autonomy":41,"adoptionStage":72,"segment":40,"evidenceCount":73,"publicEvidenceCount":73,"organizations":305,"bestGrade":77,"headline":308,"lastVerified":81,"indexable":11},"cash-application-and-remittance-matching","AI for cash application and remittance matching","Cash application and remittance matching","AI that reads remittance advices in many formats, matches incoming customer payments to open receivable invoices, proposes deduction and short pay reason codes from prior resolutions, and routes only the genuine exceptions to a cash application analyst, so the accounts receivable sub ledger clears itself for the clean majority of payments.",[67,301,88,159,302],"manufacturing","logistics-and-transportation",[130],[132,37,7,39],[306,307],"Keurig Dr Pepper","ResMed",{"kpi":137,"label":138,"unit":55,"n":73,"nUpTo":20,"kind":56,"value":309,"qualifier":101,"claimant":102,"organization":306,"vendorReported":11},98,{"slug":311,"title":312,"shortTitle":313,"definition":314,"status":30,"industries":315,"functions":316,"patterns":317,"audience":40,"autonomy":41,"adoptionStage":42,"segment":183,"evidenceCount":15,"publicEvidenceCount":15,"organizations":318,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"continuous-controls-testing","AI for continuous controls testing and control self assessment","Continuous controls testing","AI that moves control testing from periodic samples to continuous, full population assurance: it collects evidence from source systems, maps each artefact to the control it supports, tests every transaction or record against the control's rule, flags exceptions for a human to judge and prepares the risk and control self assessment from incident and loss data for the business to review.",[67,174,175,176,261],[179,180,147],[37,132,7,39],[319,320,321],"Federal Deposit Insurance Corporation","U.S. Department of the Interior","Pension Benefit Guaranty Corporation",{"slug":323,"title":324,"shortTitle":325,"definition":326,"status":30,"industries":327,"functions":328,"patterns":330,"audience":40,"autonomy":182,"adoptionStage":42,"segment":40,"evidenceCount":23,"publicEvidenceCount":23,"organizations":331,"bestGrade":51,"headline":120,"lastVerified":81,"indexable":11},"fee-and-interest-leakage-detection","AI for fee and interest leakage detection","Fee and interest leakage","An independent verification layer that recomputes what each fee, FX margin, spread and interest charge should have been under the contract and pricing tables, compares it with what was actually billed, and surfaces overcharges and undercharges account by account for correction, customer remediation and revenue recovery.",[174,237,67],[130,329,180,147],"product-and-pricing",[7,37,196],[332],"State Bank of India",{"slug":334,"title":335,"shortTitle":336,"definition":337,"status":30,"industries":338,"functions":339,"patterns":341,"audience":40,"autonomy":93,"adoptionStage":210,"segment":340,"evidenceCount":288,"publicEvidenceCount":288,"organizations":342,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"claims-fraud-detection","AI for insurance claims fraud detection","Claims fraud detection","AI that scores every insurance claim for fraud from first notice of loss onwards, combining claim, policy, document, image and network data to find suspicious claims, organised rings and inflated losses, and sends each alert with its reasons to a claims handler or special investigations unit for review.",[175],[340,263],"claims",[7,38,132,266,39],[343,344,345,346,347],"Assurant","AXA Switzerland","General Insurance Association of Singapore","Lemonade","Tokio Marine & Nichido Fire Insurance",{"slug":349,"title":350,"shortTitle":351,"definition":352,"status":30,"industries":353,"functions":354,"patterns":355,"audience":71,"autonomy":182,"adoptionStage":72,"evidenceCount":44,"publicEvidenceCount":288,"organizations":356,"bestGrade":51,"headline":362,"lastVerified":121,"indexable":11},"aiops-incident-triage","AI for IT incident triage and root cause analysis (AIOps)","AIOps incident triage","AI that turns a flood of monitoring alerts into one probable incident, routes it to the right team, proposes likely root causes and remediation from runbooks and past incidents, and drafts the stakeholder updates and the post incident review, while an engineer authorizes every change.",[67,174,68,32,237],[35,147,179],[7,39,92,196,37],[357,358,359,360,361],"Google","Meta","Microsoft","Mizuho Financial Group","TD Bank",{"kpi":363,"label":364,"unit":55,"n":15,"nUpTo":20,"kind":365,"value":366,"qualifier":101,"claimant":120,"organization":120,"vendorReported":10},"accuracy","Accuracy","median",90,{"slug":368,"title":369,"shortTitle":370,"definition":371,"status":30,"industries":372,"functions":373,"patterns":374,"audience":40,"autonomy":41,"adoptionStage":72,"segment":40,"evidenceCount":211,"publicEvidenceCount":211,"organizations":375,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"ledger-and-payment-reconciliation","AI for ledger and payment reconciliation","Ledger and payment reconciliation","AI that matches entries across nostro and vostro statements, card and scheme settlement files, the general ledger and suspense accounts, proposes matches and clearing journals, and routes only the genuine breaks to an operator with a plain language explanation.",[174,237,176,67,177,261],[130,147],[37,7,132],[376,377,378,379],"Comrade Trustee Services","Ginnie Mae","National Bank of Greece (Cyprus)","World Food Programme",{"slug":381,"title":382,"shortTitle":383,"definition":384,"status":30,"industries":385,"functions":386,"patterns":387,"audience":71,"autonomy":182,"adoptionStage":72,"segment":183,"evidenceCount":288,"publicEvidenceCount":288,"organizations":388,"bestGrade":51,"headline":394,"lastVerified":60,"indexable":11},"market-abuse-surveillance-triage","AI for market abuse surveillance alert triage","Market abuse surveillance","AI that helps surveillance analysts triage market abuse and conduct alerts, such as spoofing, layering, wash trades, ramping and insider dealing, by gathering the trade, order, news and communications context, explaining in plain language what triggered each alert and drafting the investigation narrative for the analyst to disposition.",[176,174,177],[180,239],[7,37,92,39],[389,390,391,392,393],"Commodity Futures Trading Commission","Deutsche Bank","Japan Exchange Group","Nasdaq","U.S. Securities and Exchange Commission",{"kpi":395,"label":396,"unit":55,"n":23,"nUpTo":20,"kind":56,"value":397,"qualifier":398,"claimant":59,"organization":392,"vendorReported":10},"handling-time-reduction","Handling time reduction",33,"approximately",{"slug":400,"title":401,"shortTitle":402,"definition":403,"status":30,"industries":404,"functions":405,"patterns":406,"audience":40,"autonomy":41,"adoptionStage":72,"evidenceCount":211,"publicEvidenceCount":211,"organizations":407,"bestGrade":51,"headline":412,"lastVerified":121,"indexable":11},"merchant-underwriting-and-risk-monitoring","AI for merchant underwriting and risk monitoring","Merchant underwriting and monitoring","AI that helps acquirers, payment facilitators and software platforms with embedded payments decide which merchants to accept and on what terms, by checking what a business really sells and how risky it is at onboarding, and then watches every active merchant for changes in behaviour, ranking the few that need an analyst so fraud, prohibited trade and credit losses are caught early.",[237,68,174],[264,263,179],[38,7,39,92,37],[408,409,410,411],"Airwallex","Tekmetric","Visa","Weave Communications",{"kpi":413,"label":414,"unit":55,"n":73,"nUpTo":20,"kind":56,"value":415,"qualifier":398,"claimant":102,"organization":411,"vendorReported":11},"alert-volume-reduction","Alert volume reduction",89,{"slug":417,"title":418,"shortTitle":419,"definition":420,"status":30,"industries":421,"functions":422,"patterns":423,"audience":71,"autonomy":41,"adoptionStage":72,"segment":43,"evidenceCount":288,"publicEvidenceCount":288,"organizations":425,"bestGrade":51,"headline":428,"lastVerified":121,"indexable":11},"network-planning-and-capacity-optimization","AI for mobile network planning and capacity optimization","Network planning and capacity","Machine learning that forecasts where and when a mobile network will run out of capacity, recommends where to add cells, spectrum or hardware, and continuously tunes radio parameters so existing capacity carries more traffic, with planners approving investments and major changes.",[32],[34,90],[38,424,7,37],"recommendation-and-personalization",[46,426,49,427,200],"NTT DOCOMO","Telefónica España",{"kpi":53,"label":54,"unit":55,"n":23,"nUpTo":20,"kind":56,"value":57,"qualifier":58,"claimant":59,"organization":46,"vendorReported":10},{"slug":430,"title":431,"shortTitle":432,"definition":433,"status":30,"industries":434,"functions":435,"patterns":436,"audience":40,"autonomy":182,"adoptionStage":72,"segment":241,"evidenceCount":15,"publicEvidenceCount":15,"organizations":437,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"mule-network-detection","AI for money mule account and network detection","Mule network detection","Graph and behavioural machine learning that finds money mule accounts and the networks around them, such as circular flows, layering chains and clusters of newly linked accounts, and supports investigators in tracing scam proceeds and restricting accounts before the money is gone.",[174,237],[263,239],[7,38,37,92],[438,439,440],"BigPay","ANZ, Commonwealth Bank, NAB, Suncorp Bank and Westpac (BioCatch Trust Australia)","Reserve Bank Innovation Hub (Reserve Bank of India)",{"slug":442,"title":443,"shortTitle":444,"definition":445,"status":30,"industries":446,"functions":447,"patterns":448,"audience":40,"autonomy":41,"adoptionStage":72,"segment":43,"evidenceCount":44,"publicEvidenceCount":44,"organizations":449,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"predictive-network-maintenance","AI for predictive network maintenance in telecom","Predictive network maintenance","Machine learning that spots the early signs of network failure, such as degrading cells, faulty customer equipment, ageing hardware or planned digging near fibre, and triggers a preventive fix, a remote reset or a targeted intervention before customers lose service.",[32],[34,111,147],[7,38,37],[48,199,427,50,450,200],"Verizon",{"slug":452,"title":453,"shortTitle":454,"definition":455,"status":30,"industries":456,"functions":457,"patterns":458,"audience":71,"autonomy":182,"adoptionStage":42,"segment":40,"evidenceCount":73,"publicEvidenceCount":73,"organizations":459,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"regulatory-report-assembly","AI for regulatory report assembly","Regulatory report assembly","AI that assembles periodic and data driven regulatory filings and returns, such as prudential and statistical returns, threshold and transaction reports and disclosure packs, by pulling data into the regulator's schema, validating it, reconciling figures to source, explaining movements against prior periods and drafting commentary, before a named officer reviews and submits. Narratives for individual suspicious activity cases are a separate use case.",[174,175,176,237],[180,130,239],[37,7,113,92],[460,461],"Board of Governors of the Federal Reserve System","National Credit Union Administration",{"slug":463,"title":464,"shortTitle":465,"definition":466,"status":30,"industries":467,"functions":468,"patterns":469,"audience":71,"autonomy":93,"adoptionStage":72,"evidenceCount":44,"publicEvidenceCount":44,"organizations":470,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"inspection-prioritization","AI for risk based inspection prioritization in food safety, workplace and environmental regulation","Inspection prioritization","Models that predict which premises, operators or activities are most likely to be non compliant, so that inspectors in food safety, workplace safety, environmental and other regulation spend their visits where the risk is highest, ideally with inspectors choosing the visits and random inspections testing the model.",[261],[179,286,180],[38,7],[471,472,473,474,475,476],"Care Quality Commission","Driver and Vehicle Standards Agency","U.S. Environmental Protection Agency, Office of Enforcement and Compliance Assurance","Food Standards Agency","Nederlandse Arbeidsinspectie","Nederlandse Voedsel- en Warenautoriteit (NVWA)",{"slug":478,"title":479,"shortTitle":480,"definition":481,"status":30,"industries":482,"functions":483,"patterns":485,"audience":40,"autonomy":41,"adoptionStage":210,"segment":40,"evidenceCount":288,"publicEvidenceCount":211,"organizations":486,"bestGrade":51,"headline":490,"lastVerified":121,"indexable":11},"supplier-invoice-processing","AI for supplier invoice processing in accounts payable","Supplier invoice processing","AI that captures supplier invoices from any format, extracts header and line data, matches them to purchase orders and goods receipts, proposes tax and cost centre coding, flags duplicates and suspected fraud, and routes them for approval and posting, leaving only exceptions to accounts payable staff.",[67,174,261,88,145],[130,484],"procurement",[132,37,7,39],[319,487,488,489],"Kingfisher","U.S. Immigration and Customs Enforcement","Veolia",{"kpi":98,"label":99,"unit":55,"n":23,"nUpTo":23,"kind":56,"value":491,"qualifier":101,"claimant":59,"organization":487,"vendorReported":10},80,{"slug":493,"title":494,"shortTitle":495,"definition":496,"status":30,"industries":497,"functions":498,"patterns":499,"audience":40,"autonomy":93,"adoptionStage":72,"evidenceCount":15,"publicEvidenceCount":15,"organizations":500,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"tax-compliance-risk-scoring","AI for tax compliance risk scoring and audit selection","Tax compliance risk scoring","Models that score tax returns, taxpayers and transactions for the risk of error, underreporting or fraud, so that a tax administration spends its audit and compliance capacity where the risk is highest, with an officer deciding every compliance action and the selection itself monitored for fairness.",[261],[179,286,263],[38,7],[501,502,503],"Belastingdienst","HM Revenue and Customs","Internal Revenue Service",{"slug":505,"title":506,"shortTitle":507,"definition":508,"status":30,"industries":509,"functions":510,"patterns":512,"audience":40,"autonomy":41,"adoptionStage":72,"segment":513,"evidenceCount":211,"publicEvidenceCount":211,"organizations":514,"bestGrade":51,"headline":515,"lastVerified":121,"indexable":11},"telecom-fraud-detection","AI for telecom fraud detection (SIM swap, IRSF and Wangiri)","Telecom fraud detection","AI that protects the operator's own network, revenue and numbers from fraud: it watches call, messaging, roaming and account activity to detect SIM swap and port out takeovers, international revenue share fraud (IRSF) and Wangiri one ring scams, blocks or flags them in real time, and shares risk signals with banks and other businesses that rely on the phone number for security. Scam calls aimed at subscribers are handled by call blocking.",[32],[263,34,511],"security-operations",[7,38,39],"customer-protection",[50,200],{"kpi":274,"label":275,"unit":55,"n":23,"nUpTo":20,"kind":56,"value":516,"qualifier":101,"claimant":59,"organization":200,"vendorReported":10},30,{"slug":518,"title":519,"shortTitle":520,"definition":521,"status":30,"industries":522,"functions":523,"patterns":524,"audience":40,"autonomy":182,"adoptionStage":42,"segment":241,"evidenceCount":211,"publicEvidenceCount":15,"organizations":525,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"portfolio-drift-monitoring-and-rebalancing","AI portfolio drift monitoring and rebalancing proposals","Drift and rebalancing","Continuous monitoring of every client portfolio against its mandate or model, which detects drift beyond agreed bands and prepares a tax aware, low turnover rebalancing proposal with its rationale for an advisor or portfolio manager to approve before any trade is placed.",[177,174],[147,179,90],[7,37,38,113],[526,527,528],"Morgan Stanley","SimCorp","Vanguard",{"slug":530,"title":531,"shortTitle":532,"definition":533,"status":30,"industries":534,"functions":535,"patterns":536,"audience":71,"autonomy":93,"adoptionStage":72,"segment":537,"evidenceCount":73,"publicEvidenceCount":73,"organizations":538,"bestGrade":51,"headline":120,"lastVerified":81,"indexable":11},"freight-rail-rolling-stock-predictive-maintenance","AI predictive maintenance for freight rail rolling stock","Rail rolling stock predictive maintenance","Machine vision and machine learning that inspect freight railcar wheels, bearings and other running gear as trains pass wayside sensors and camera portals at track speed, learn what a healthy wheel or a healthy reading looks like, and flag the ones that need attention before a crack, an overheating bearing or a worn wheel causes a service failure or a derailment.",[302],[147,111],[266,7,38],"mechanical-and-safety",[539,540],"BNSF Railway","Norfolk Southern",{"slug":542,"title":543,"shortTitle":544,"definition":545,"status":30,"industries":546,"functions":547,"patterns":548,"audience":71,"autonomy":93,"adoptionStage":72,"segment":549,"evidenceCount":15,"publicEvidenceCount":15,"organizations":550,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"industrial-asset-predictive-maintenance","AI predictive maintenance for industrial and energy assets","Industrial predictive maintenance","Machine learning that learns the normal behaviour of industrial and energy equipment from sensor and process data, flags early signs of degradation weeks or months before a failure, and turns them into prioritised maintenance work, so plants and utilities plan repairs instead of reacting to breakdowns.",[145,301],[147,111],[7,38],"asset-management",[551,552,553],"Duke Energy","Georgia-Pacific","Shell",{"slug":555,"title":556,"shortTitle":557,"definition":558,"status":30,"industries":559,"functions":560,"patterns":561,"audience":71,"autonomy":93,"adoptionStage":210,"segment":562,"evidenceCount":73,"publicEvidenceCount":73,"organizations":563,"bestGrade":51,"headline":566,"lastVerified":81,"indexable":11},"radiology-worklist-triage","AI prioritization of radiology and imaging worklists","Radiology worklist triage","An AI system that analyzes a medical image immediately after a scan, flags time sensitive findings such as a brain bleed, a stroke causing large vessel occlusion or a pulmonary embolism, and reorders the radiologist's worklist and notifies the care team so the most urgent cases are read and acted on first, while a radiologist confirms every finding before it changes a patient's treatment.",[159],[147],[266,39,7],"emergency and inpatient imaging",[564,565],"Adventist Health + Rideout","Sheba Medical Center",{"kpi":53,"label":54,"unit":55,"n":23,"nUpTo":20,"kind":56,"value":567,"qualifier":398,"claimant":102,"organization":564,"vendorReported":11},44,{"slug":569,"title":570,"shortTitle":571,"definition":572,"status":30,"industries":573,"functions":575,"patterns":576,"audience":71,"autonomy":41,"adoptionStage":72,"segment":578,"evidenceCount":15,"publicEvidenceCount":15,"organizations":579,"bestGrade":51,"headline":583,"lastVerified":121,"indexable":11},"production-line-quality-inspection","AI quality inspection on the production line","Production quality inspection","AI that inspects every unit on a production line, from camera images, sound or machine process data, to find defects, missing parts and wrong variants in real time, and routes the few anomalies it flags to a quality inspector instead of relying on manual sampling at the end of the line.",[301,574],"automotive",[147],[266,7,577,37],"synthetic-data-generation","production",[580,581,582],"Audi","BMW Group","Pegatron",{"kpi":79,"label":80,"unit":55,"n":23,"nUpTo":20,"kind":56,"value":584,"qualifier":101,"claimant":102,"organization":582,"vendorReported":11},7,{"slug":586,"title":587,"shortTitle":588,"definition":589,"status":30,"industries":590,"functions":591,"patterns":592,"audience":40,"autonomy":41,"adoptionStage":42,"segment":593,"evidenceCount":15,"publicEvidenceCount":15,"organizations":594,"bestGrade":77,"headline":120,"lastVerified":121,"indexable":11},"trade-finance-crime-screening","AI screening of trade finance transactions for trade based money laundering","Trade crime screening","AI that screens every trade finance transaction for financial crime risk: it checks parties, vessels and ports against sanctions and watchlists, tests goods descriptions against dual use and controlled goods lists, compares unit prices with benchmarks for over or under invoicing, and reads trade documents and messages for laundering red flags, then prepares a case narrative for a human investigator.",[174],[239,147],[132,7,39,92],"specialized-businesses",[595,596,597],"ANZ, HSBC and Lloyds Banking Group","Stanbic Bank Uganda","United Bank Limited",{"slug":599,"title":600,"shortTitle":601,"definition":602,"status":30,"industries":603,"functions":604,"patterns":605,"audience":116,"autonomy":606,"adoptionStage":210,"segment":513,"evidenceCount":288,"publicEvidenceCount":288,"organizations":607,"bestGrade":51,"headline":120,"lastVerified":60,"indexable":11},"spam-and-scam-call-blocking","AI spam and scam call blocking for mobile and landline subscribers","Spam and scam call blocking","AI in the operator's network that protects subscribers from unwanted calls: it analyses incoming calls in real time, blocks known fraudulent calls, and labels suspected scam, spam and spoofed calls on the customer's screen before they answer, so subscribers can decide whether to pick up. Fraud against the operator itself, such as SIM swap or revenue share fraud, is a separate use case.",[32],[263,110],[7,39,38],"autonomous",[198,608,50,609],"BT Group","Virgin Media O2",{"slug":611,"title":612,"shortTitle":613,"definition":614,"status":30,"industries":615,"functions":616,"patterns":617,"audience":40,"autonomy":41,"adoptionStage":72,"segment":241,"evidenceCount":23,"publicEvidenceCount":23,"organizations":618,"bestGrade":51,"headline":120,"lastVerified":121,"indexable":11},"dynamic-customer-risk-rating","Dynamic AML customer risk rating with machine learning","Dynamic customer risk rating","Explainable machine learning that produces the money laundering risk rating itself: it computes and continuously updates each customer's rating from due diligence data, products, geography, behaviour and screening results, and shows which factors drive the rating and when enhanced due diligence is warranted.",[174,237,177],[239,179],[38,7],[619],"bunq",{"slug":621,"title":622,"shortTitle":623,"definition":624,"status":30,"industries":625,"functions":626,"patterns":627,"audience":71,"autonomy":182,"adoptionStage":72,"evidenceCount":15,"publicEvidenceCount":15,"organizations":628,"bestGrade":77,"headline":632,"lastVerified":121,"indexable":11},"internal-audit-copilot","Generative AI copilot for internal audit","Internal audit copilot","A copilot for internal auditors that drafts planning memos and document request lists from prior audits, summarises large evidence sets, builds risk and control matrices from policies and process documents, and drafts findings and reports, with every statement traceable to its evidence and a qualified auditor accountable for every conclusion.",[67,174,175,261,176,177],[179,180,130],[196,92,113,132,7],[629,630,631],"Banco Bradesco","British Columbia Investment Management Corporation","XP Inc.",{"kpi":395,"label":396,"unit":55,"n":73,"nUpTo":20,"kind":56,"value":633,"qualifier":101,"claimant":102,"organization":629,"vendorReported":11},55,{"slug":635,"title":636,"shortTitle":637,"definition":638,"status":30,"industries":639,"functions":640,"patterns":641,"audience":40,"autonomy":606,"adoptionStage":210,"segment":241,"evidenceCount":642,"publicEvidenceCount":642,"organizations":643,"bestGrade":51,"headline":650,"lastVerified":121,"indexable":11},"real-time-fraud-scoring","Real time fraud scoring for card and instant payments","Real time fraud scoring","Machine learning that decides in milliseconds, without any conversation, how likely each card authorization and account to account payment is to be fraudulent, combining behavioural, device and network signals, so the bank can approve, challenge or block a payment before the money leaves. Working the resulting alerts and talking to the customer about them are separate use cases.",[174,237],[263],[38,7],9,[439,644,645,646,647,648,649,410],"Commonwealth Bank of Australia","Mastercard","NatWest Group","Pay.UK","Revolut","Stripe",{"kpi":651,"label":652,"unit":55,"n":15,"nUpTo":20,"kind":365,"value":516,"qualifier":101,"claimant":59,"organization":120,"vendorReported":10},"fraud-loss-reduction","Fraud loss reduction",[654,673,690,703,717,726],{"kpi":137,"label":138,"unit":55,"aggregate":11,"higherIsBetter":11,"n":44,"nUpTo":20,"median":655,"min":18,"max":656,"byClaimant":657,"vendorOnly":10,"points":658},84,98.7,{"organization":23,"vendor":288,"regulator":20,"independent":20},[659,661,663,666,668,671],{"evidenceId":660,"organization":410,"value":656,"qualifier":101,"claimant":59,"grade":51,"pooled":11},"visa-decision-manager",{"evidenceId":662,"organization":306,"value":309,"qualifier":101,"claimant":102,"grade":77,"pooled":11},"keurig-dr-pepper-cash-application-automation",{"evidenceId":664,"organization":307,"value":665,"qualifier":101,"claimant":102,"grade":77,"pooled":11},"resmed-cash-application-automation",96,{"evidenceId":667,"organization":134,"value":21,"qualifier":101,"claimant":102,"grade":77,"pooled":11},"databricks-expense-audit-automation",{"evidenceId":669,"organization":135,"value":670,"qualifier":101,"claimant":102,"grade":77,"pooled":11},"takeda-expense-audit-automation",63,{"evidenceId":672,"organization":247,"value":18,"qualifier":101,"claimant":102,"grade":51,"pooled":11},"nexo-unit21-ai-alert-narratives",{"kpi":98,"label":99,"unit":55,"aggregate":11,"higherIsBetter":11,"n":211,"nUpTo":23,"median":674,"min":516,"max":491,"byClaimant":675,"vendorOnly":10,"points":676},57.5,{"organization":23,"vendor":15,"regulator":20,"independent":20},[677,681,683,686,688],{"evidenceId":678,"organization":489,"value":679,"qualifier":680,"claimant":102,"grade":77,"pooled":10},"veolia-ssc-invoice-processing",87.5,"up-to",{"evidenceId":682,"organization":487,"value":491,"qualifier":101,"claimant":59,"grade":77,"pooled":11},"kingfisher-ap-invoice-capture",{"evidenceId":684,"organization":629,"value":685,"qualifier":101,"claimant":102,"grade":77,"pooled":11},"banco-bradesco-aila-audit-assistant",65,{"evidenceId":687,"organization":96,"value":100,"qualifier":101,"claimant":102,"grade":77,"pooled":11},"seatgeek-data-quality-observability",{"evidenceId":689,"organization":631,"value":516,"qualifier":101,"claimant":102,"grade":77,"pooled":11},"xp-inc-copilot-audit-team",{"kpi":53,"label":54,"unit":55,"aggregate":11,"higherIsBetter":11,"n":211,"nUpTo":20,"median":691,"min":692,"max":57,"byClaimant":693,"vendorOnly":10,"points":694},41,34,{"organization":15,"vendor":23,"regulator":20,"independent":20},[695,697,699,701],{"evidenceId":696,"organization":46,"value":57,"qualifier":58,"claimant":59,"grade":51,"pooled":11},"deutsche-telekom-ran-guardian-and-mindr-agents",{"evidenceId":698,"organization":564,"value":567,"qualifier":398,"claimant":102,"grade":77,"pooled":11},"adventist-health-rideout-viz-ai-stroke-transfer",{"evidenceId":700,"organization":165,"value":167,"qualifier":101,"claimant":59,"grade":51,"pooled":11},"johns-hopkins-capacity-command-center",{"evidenceId":702,"organization":164,"value":692,"qualifier":101,"claimant":59,"grade":51,"pooled":11},"humber-river-health-command-centre",{"kpi":252,"label":253,"unit":55,"aggregate":11,"higherIsBetter":11,"n":211,"nUpTo":20,"median":704,"min":100,"max":254,"byClaimant":705,"vendorOnly":10,"points":706},67.5,{"organization":73,"vendor":73,"regulator":20,"independent":20},[707,709,712,715],{"evidenceId":708,"organization":249,"value":254,"qualifier":101,"claimant":102,"grade":77,"pooled":11},"shift4-thetaray-aml-transaction-monitoring",{"evidenceId":710,"organization":646,"value":711,"qualifier":101,"claimant":102,"grade":77,"pooled":11},"natwest-featurespace-fraud-and-scam-detection",75,{"evidenceId":713,"organization":246,"value":714,"qualifier":101,"claimant":59,"grade":51,"pooled":11},"hsbc-dynamic-risk-assessment",60,{"evidenceId":716,"organization":408,"value":100,"qualifier":101,"claimant":59,"grade":51,"pooled":11},"airwallex-generative-ai-website-screening",{"kpi":395,"label":396,"unit":55,"aggregate":11,"higherIsBetter":11,"n":211,"nUpTo":20,"median":567,"min":516,"max":366,"byClaimant":718,"vendorOnly":10,"points":719},{"organization":23,"vendor":15,"regulator":20,"independent":20},[720,721,722,724],{"evidenceId":682,"organization":487,"value":366,"qualifier":398,"claimant":102,"grade":77,"pooled":11},{"evidenceId":684,"organization":629,"value":633,"qualifier":101,"claimant":102,"grade":77,"pooled":11},{"evidenceId":723,"organization":392,"value":397,"qualifier":398,"claimant":59,"grade":51,"pooled":11},"nasdaq-market-surveillance-generative-ai",{"evidenceId":725,"organization":630,"value":516,"qualifier":101,"claimant":102,"grade":77,"pooled":11},"bci-copilot-internal-audit-reports",{"kpi":363,"label":364,"unit":55,"aggregate":11,"higherIsBetter":11,"n":15,"nUpTo":20,"median":366,"min":727,"max":309,"byClaimant":728,"vendorOnly":10,"points":729},42,{"organization":73,"vendor":23,"regulator":20,"independent":20},[730,732,734],{"evidenceId":731,"organization":360,"value":309,"qualifier":101,"claimant":102,"grade":77,"pooled":11},"mizuho-generative-ai-event-detection",{"evidenceId":733,"organization":359,"value":366,"qualifier":101,"claimant":59,"grade":51,"pooled":11},"microsoft-azure-triangle-incident-triage",{"evidenceId":735,"organization":358,"value":727,"qualifier":101,"claimant":59,"grade":51,"pooled":11},"meta-ai-assisted-root-cause-analysis",[737,740,743,746,748,750,752,754],{"id":174,"label":738,"count":739},"Banking",18,{"id":67,"label":741,"count":742},"Cross industry",11,{"id":237,"label":744,"count":745},"Payments and cards",10,{"id":32,"label":747,"count":642},"Telecommunications",{"id":261,"label":749,"count":242},"Government and public sector",{"id":176,"label":751,"count":44},"Capital markets",{"id":177,"label":753,"count":44},"Wealth and asset management",{"id":175,"label":755,"count":288},"Insurance",[757,760,762,764,766,768,770,772],{"id":147,"label":758,"count":759},"Operations",15,{"id":179,"label":761,"count":745},"Risk management",{"id":263,"label":763,"count":642},"Fraud prevention",{"id":130,"label":765,"count":584},"Finance and accounting",{"id":180,"label":767,"count":584},"Regulatory compliance",{"id":90,"label":769,"count":44},"Analytics and reporting",{"id":239,"label":771,"count":44},"Financial crime compliance",{"id":34,"label":773,"count":44},"Network operations",[],[776,779,781,783,786],{"stage":777,"count":778},"announced",13,{"stage":780,"count":778},"pilot",{"stage":578,"count":782},69,{"stage":784,"count":785},"scaled",36,{"stage":787,"count":15},"paused",[789,792,794,797,799,801,803],{"region":790,"count":791},"north-america",47,{"region":793,"count":727},"europe",{"region":795,"count":796},"asia-pacific",24,{"region":798,"count":759},"global",{"region":800,"count":15},"middle-east",{"region":802,"count":73},"latin-america",{"region":804,"count":23},"africa",[439,595,344,564,408,75,213,343,580,244,268,245,581,539,608,629,501,198,438,460,630,270,471,290,269,119,389,644,376,151,95,134,271,390,46,472,551,185,319,474,291,345,552,377,357,502,246,164,503,391,165,48,306,487,346,645,358,359,360,526,214,426,392,646,378,461,475,476,247,540,228,215,199,229,647,272,582,321,248,307,440,648,96,565,553,249,527,152,596,186,332,649,230,361,135,409,427,50,347,320,292,473,488,393,293,597,187,250,76,528,489,450,609,410,200,216,411,379,631,619,47,49],1790598309551]