Telecommunications
Use Cases
AI Daily Brief
Newsfor Telecommunications
Sort by
All Telecommunications AI Use Cases
Accelerate data integration from multiple sourcesAccelerate identification and protection of intellectual propertyAssist IT Project management by keeping track of progress and estimating riskAutomate contract due diligenceAutomate cybersecurity systemsDigitise and automate processes using Robotic Process Automation (RPA)Enhance product and service offeringForecast network demandIdentify alternative roles for candidates during or after recruitment processIdentify and source potential candidates in the marketIdentify key characteristics of successful employees for recruitment and career development supportImprove administrative productivity with Robotic Process AutomationManage cybersecurity threats and regulatory reportingOptimise engineer field force labour allocationOptimise field network performanceOptimise mobile job schedulingOptimise network resource allocation based on real time and predictive load analysisOptimise network traffic load balancingOptimise supply chainOptimise website experience to improve engagement and conversion ratesPredict and drive customer retention and churn managementPredict maintenance on network assetsPredict problems and recommend proactive maintenance for fixed equipment such as substations or electricity pylonsPredict regional demand trends for telecoms trafficPrioritise capex investment recommendations across networkScan resumes to improve diversity and quality of candidate pool for recruitmentSecure communications through deployment of crypto technologySupport review and design of supplier contracts
Telecommunications Case Studies
AT&T monitors its network constantly offering seamless service and plans maintenance and upgrades optimally using machine learningAT&T pulls sales leads from multiple systems to automate data entry into legacy systems using Robotic Process AutomationBharti Airtel reduces time to hire from weeks to days and offer-drop rate from 80% to 26% through predictive hiringBritish Telecom improves network security by using machine learning to detect real-time cyber threatsBritish Telecom saves an estimated £100M a year using the automated contract analysis platform RAVNEquinix predicts customer churn with 90% accuracy using a machine learning neural network modelFrance Telecom''s Telekomunikacja Polksa realised that certain customers have a greater or lesser influences on networks of mobile phones users. If highly connected networkers churn then this is likely to cause a large ripple effect. To improve customer churn prediction and identification of who to retain they developed social graphs and analysis based on the transaction history and network connections of customers. This allowed them to improve prediction by 47%.Infinera will optimise its supply chain management to make better predictions about delivery dates using machine learningMTN sped up their patent application rate with 50% fewer rejections using TurboPatent''s patent drafting automation platformNeopost identifies customers at risk of churn with machine learning using PredicSisNokia aims to boost 5G network performance and cut costs with the use of machine learningOrange Silicon Valley speeds up project completion using TARA machine learning hiring and project management platformQuickplay safeguards its data and interconnected systems with Darktrace’s AI-enabled cyber security productSK Telecom to prevent voice phishing cyber attacks using AIT-mobile reduces churn by up to 50% by identifying and retaining highly-influential ''tribe leader'' customers with advanced predictive modellingTelefonica O2 automates processing of more than 35% of outsourced business processes using robotic process automationTigoUne reduces management system failure by 80% through a machine learning workforce management solutionUS cellular increases customer lifetime value by 61% by analysing website visitor behavior against online and offline sales, subscriptions and renewals using machine learningVerizon monitors and optimises network performance in real-tim using machine learning to analyse network interface data