Market Research Report
Artificial Intelligence for Telecommunications Applications: Network Operations Monitoring/Management, Customer Service/Marketing VDAs, Intelligent CRM Systems, CEM, Cybersecurity, Fraud Mitigation, Other - Global Market Analysis and Forecasts
|Published by||Omdia | Tractica||Product code||630464|
|Published||Content info||55 Pages; 19 Tables, Charts & Figures
Delivery time: 1-2 business days
|Artificial Intelligence for Telecommunications Applications: Network Operations Monitoring/Management, Customer Service/Marketing VDAs, Intelligent CRM Systems, CEM, Cybersecurity, Fraud Mitigation, Other - Global Market Analysis and Forecasts|
|Published: September 5, 2019||Content info: 55 Pages; 19 Tables, Charts & Figures||
Telecommunications service providers face a handful of daunting market conditions. Around the globe, revenue and subscriber growth are flat. To combat profit erosion, most communications service providers (CSPs) are struggling through a process to become digital service providers more akin to web companies that offer rapidly evolving and highly customized services.
5G/Internet of Things (IoT) and digital transformation are initiatives that CSPs hope will drive top-line growth. While they pursue these, CSPs are under equal pressure to find ways to become more efficient and cut costs as a means to increase profitability. This is an industry ripe for artificial intelligence (AI)-driven solutions. Telecom operators have begun to experiment and deploy AI-driven solutions that leverage fast, scalable interpretation, analytics, and prediction to provide top-line revenue or reduce costs. According to Tractica's analysis, telecom AI software revenue is expected to grow from $419.0 million in 2018 to more than $11.2 billion in 2025.
This Tractica report details the major market drivers and barriers, technologies, key players, and forecasts related to eight telecom AI use cases. These include network operations monitoring and management; predictive maintenance; fraud mitigation; cybersecurity; customer service and marketing virtual digital assistants (VDAs); intelligent customer relationship management (CRM) systems; customer experience management (CEM)/service delivery; and video compression. The technologies covered include machine learning (ML), deep learning (DL), and natural language processing (NLP). Global software market forecasts for telecom AI, segmented by region, use case, and meta category, extend through 2025.