Artificial Intelligence for Telecommunications Applications

Network Operations Monitoring & Management, Customer Service & Marketing VDAs, Intelligent CRM Systems, Customer Experience Management, Cyber security, Fraud Mitigation, and Other Use Cases: Market Analysis and Forecasts

The telecommunication service provider industry is one of the biggest businesses in the world. It also has historically been a capital-intensive industry with high fixed costs, which has put pressure on telecom operators to control their variable costs, particularly human capital. This tension surrounding profitability is intensifying. Many telecom operators crossed the point where revenue per bit is lower than cost per bit in 2017. Telecom operators are threatened by fast and highly-efficient web-scale companies and are straining under the challenge posed by digital transformation. On top of all that, telecom operators must solve how to profitably manage and operate the dizzyingly complex next-generation 5G/Internet of Things (IoT) networks.

It is an industry ripe for artificial intelligence (AI)-driven solutions, with their promise of lowering costs and boosting efficiencies through automation. Many telecom operators have begun to experiment and deploy AI-driven solutions in both customer-facing and internal organizations. Tractica has identified seven key telecom AI use cases: network operations monitoring and management, predictive maintenance, fraud mitigation, cybersecurity, customer service and marketing virtual digital assistants (VDAs), intelligent customer relationship management (CRM) systems, and customer experience management (CEM). This report details the market drivers and barriers, technologies, key players, and forecasts for these seven telecom AI use cases.

This Tractica report examines the market and technology issues surrounding telecom AI use cases. The technologies covered include machine learning, deep learning, natural language processing, and machine reasoning. It presents profiles for key industry players throughout the ecosystem. The report also includes global software, hardware, and services market forecasts for telecom AI, segmented by region and use case, covering the period from 2016 through 2025.

Key Questions Addressed:

What is the current state of the market for telecom AI and how will it develop over the next decade?
What are the key use cases that will drive greater telecom AI adoption?
What are the key drivers of market growth, and the key challenges faced by telecom AI, in each world region?
Who are the key players in the market, what is their competitive positioning, and which ones are poised for greatest success in the years ahead?
What is the size of the telecom AI market opportunity?