[{"data":1,"prerenderedAt":227},["ShallowReactive",2],{"uc-hub-function-network-operations":3},{"type":4,"typeLabel":5,"term":6,"includeUnpublished":10,"indexable":11,"stats":12,"useCases":22,"benchmarks":176,"topIndustries":177,"topFunctions":183,"topPatterns":184,"stageMix":201,"regionMix":214,"organizations":226,"other":78},"function","Business function",{"id":7,"label":8,"description":9},"network-operations","Network operations","Planning, monitoring, fault handling and optimization of telecom and utility networks.",false,true,{"useCases":13,"publicDeployments":14,"blitsAiDeployments":15,"organizations":16,"countries":17,"outcomeDisclosureRate":18,"gradeMix":19},8,25,0,19,12,60,{"A":15,"B":20,"C":21,"D":15},14,11,[23,60,80,99,114,124,143,161],{"slug":24,"title":25,"shortTitle":26,"definition":27,"status":28,"industries":29,"functions":31,"patterns":33,"audience":38,"autonomy":39,"adoptionStage":40,"segment":41,"evidenceCount":42,"publicEvidenceCount":42,"organizations":43,"bestGrade":49,"headline":50,"lastVerified":59,"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",[30],"telecommunications",[7,32],"it-and-engineering",[34,35,36,37],"agentic-workflow","anomaly-detection","prediction-and-scoring","classification-and-routing","back-office","supervised-agent","emerging","network",6,[44,45,46,47,48],"Deutsche Telekom","du","KDDI","stc Group","Telstra","B",{"kpi":51,"label":52,"unit":53,"n":54,"nUpTo":15,"kind":55,"value":56,"qualifier":57,"claimant":58,"organization":44,"vendorReported":10},"processing-time-reduction","Cycle time reduction","percent",1,"reported",95,"at-least","organization","2026-09-26",{"slug":61,"title":62,"shortTitle":63,"definition":64,"status":28,"industries":65,"functions":66,"patterns":69,"audience":73,"autonomy":39,"adoptionStage":40,"segment":74,"evidenceCount":75,"publicEvidenceCount":54,"organizations":76,"bestGrade":49,"headline":78,"lastVerified":79,"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.",[30],[67,7,68],"customer-service","field-service",[35,37,70,71,72],"content-generation","conversational-agent","voice-agent","customer-facing","front-office",2,[77],"Comcast",null,"2026-09-27",{"slug":81,"title":82,"shortTitle":83,"definition":84,"status":28,"industries":85,"functions":86,"patterns":88,"audience":91,"autonomy":92,"adoptionStage":93,"segment":41,"evidenceCount":42,"publicEvidenceCount":42,"organizations":94,"bestGrade":49,"headline":98,"lastVerified":79,"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.",[30],[7,87],"operations",[35,37,89,90,34],"rag-knowledge-assistant","summarization","employee-facing","copilot","early-adopters",[95,44,46,96,48,97],"Bell Canada","Orange","Vodafone",{"kpi":51,"label":52,"unit":53,"n":54,"nUpTo":15,"kind":55,"value":56,"qualifier":57,"claimant":58,"organization":44,"vendorReported":10},{"slug":100,"title":101,"shortTitle":102,"definition":103,"status":28,"industries":104,"functions":105,"patterns":107,"audience":91,"autonomy":39,"adoptionStage":93,"segment":41,"evidenceCount":109,"publicEvidenceCount":109,"organizations":110,"bestGrade":49,"headline":113,"lastVerified":79,"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.",[30],[7,106],"analytics-and-reporting",[36,108,35,34],"recommendation-and-personalization",5,[44,111,47,112,97],"NTT DOCOMO","Telefónica España",{"kpi":51,"label":52,"unit":53,"n":54,"nUpTo":15,"kind":55,"value":56,"qualifier":57,"claimant":58,"organization":44,"vendorReported":10},{"slug":115,"title":116,"shortTitle":117,"definition":118,"status":28,"industries":119,"functions":120,"patterns":121,"audience":38,"autonomy":39,"adoptionStage":93,"segment":41,"evidenceCount":42,"publicEvidenceCount":42,"organizations":122,"bestGrade":49,"headline":78,"lastVerified":79,"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.",[30],[7,68,87],[35,36,34],[46,96,112,48,123,97],"Verizon",{"slug":125,"title":126,"shortTitle":127,"definition":128,"status":28,"industries":129,"functions":130,"patterns":131,"audience":38,"autonomy":132,"adoptionStage":93,"segment":41,"evidenceCount":109,"publicEvidenceCount":109,"organizations":133,"bestGrade":49,"headline":139,"lastVerified":79,"indexable":11},"ran-energy-optimization","AI for radio access network energy optimization","RAN energy optimization","Machine learning that predicts traffic per cell and puts radio carriers, cells and hardware components into sleep modes when demand is low, then wakes them before users notice, so a mobile network uses less electricity without losing coverage or quality.",[30],[7],[36],"autonomous",[134,135,136,137,138],"BT Group","Indosat Ooredoo Hutchison","O2 Telefónica Germany","Safaricom","Telefónica",{"kpi":140,"label":141,"unit":53,"n":15,"nUpTo":54,"kind":55,"value":13,"qualifier":142,"claimant":58,"organization":138,"vendorReported":10},"energy-savings","Energy savings","up-to",{"slug":144,"title":145,"shortTitle":146,"definition":147,"status":28,"industries":148,"functions":149,"patterns":152,"audience":38,"autonomy":39,"adoptionStage":93,"segment":153,"evidenceCount":154,"publicEvidenceCount":154,"organizations":155,"bestGrade":49,"headline":156,"lastVerified":79,"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.",[30],[150,7,151],"fraud-prevention","security-operations",[35,36,37],"customer-protection",4,[48,97],{"kpi":157,"label":158,"unit":53,"n":54,"nUpTo":15,"kind":55,"value":159,"qualifier":160,"claimant":58,"organization":97,"vendorReported":10},"detection-rate-improvement","Detection improvement",30,"exact",{"slug":162,"title":163,"shortTitle":164,"definition":165,"status":28,"industries":166,"functions":168,"patterns":169,"audience":91,"autonomy":92,"adoptionStage":93,"segment":171,"evidenceCount":75,"publicEvidenceCount":75,"organizations":172,"bestGrade":175,"headline":78,"lastVerified":79,"indexable":11},"power-line-vegetation-management","AI vegetation management for power lines","Power line vegetation management","AI that analyses satellite, aerial or lidar imagery of the land along power lines to estimate where and how fast vegetation will grow into the lines or fall onto them, and turns that into a risk based trimming and hazard tree removal plan, replacing fixed trimming cycles and manual patrols.",[167],"energy-and-utilities",[7,68],[170,36],"computer-vision","grid",[173,174],"Entergy","National Grid","C",[],[178,181],{"id":30,"label":179,"count":180},"Telecommunications",7,{"id":167,"label":182,"count":54},"Energy and utilities",[],[185,187,189,191,193,195,197,199],{"id":35,"label":186,"count":42},"Anomaly detection",{"id":36,"label":188,"count":42},"Prediction and scoring",{"id":34,"label":190,"count":154},"Agentic workflow",{"id":37,"label":192,"count":154},"Classification and routing",{"id":170,"label":194,"count":54},"Computer vision",{"id":70,"label":196,"count":54},"Content generation",{"id":71,"label":198,"count":54},"Conversational agent",{"id":89,"label":200,"count":54},"RAG knowledge assistant",[202,204,207,210,212],{"stage":203,"count":54},"announced",{"stage":205,"count":206},"pilot",3,{"stage":208,"count":209},"production",15,{"stage":211,"count":42},"scaled",{"stage":213,"count":15},"paused",[215,218,220,222,224],{"region":216,"count":217},"europe",9,{"region":219,"count":13},"asia-pacific",{"region":221,"count":109},"north-america",{"region":223,"count":75},"middle-east",{"region":225,"count":54},"africa",[134,95,77,44,173,135,46,111,174,136,96,137,138,112,48,123,97,45,47],1790598324035]