AI business value: Unleashing the potential of AI for telecom operations
Artificial intelligence (AI) is taking automation to the next level. But AI implementation isn't just a one-off tech solution – it's a whole new way of working, which means its value is often hard to measure. To calculate how AI is driving growth in the telecommunications industry, we surveyed industry professionals about the role it plays in their organizations, using the insights to develop an industry-unique measurement framework.
Learn from the front-runners of telecom AI
Discover the AI business potential for telecom operation
We divided the findings of our study in two reports. The first report summarizes the finding of our survey, presents the top ten AI use case cluster for telecom and describes the AI value measurement framework. The second, deep-dive, focuses on selected clusters and their business benefits and provides a quick guide on the steps to accelerate AI implementation.
Watch our experts’ discussion on the report and the potential of AI in telecom l 30 min
Measuring the benefits of AI for CSPs
With hundreds of possible use cases, AI unlocks enormous business potential for CSPs.
While many of these new opportunities are easy to implement, others are very specific to the telecom industry and require deep telecom domain expertise and AI expertise. To help CSPs determine which AI use cases are best suited to their business goals, we created an industry-unique standardized measurement framework to calculate AI value creation. The framework has four distinctive steps.
Determine baseline
Specify the sought-after business outcome
Determine KPI drivers
Select the AI use case and assess business impact
What do the front-runners do?
Manager Special Project Hyper Automation & Transformation, South East Asia
Selected AI clusters deep dives
Why does network optimization have such a high business potential? How can AI in network operations prepare CSPs for the future? And how can you use cloud and infrastructure operations to build your foundation? We take you on a deep dive to find out.
Explore three of the commonly adopted AI use case clusters: network optimization, network operations and cloud and infrastructure operations clusters to uncover their growth potential, benefits and future challenges.
Network optimization
AI use cases related to optimization and improvement of network performance. Examples include proactively identifying network bottleneck issues and maximizing CAPEX investments using AI-powered prediction models. Approximately 37 percent of surveyed CSPs have AI-powered network optimization solutions.
Network operations
AI use cases related to improving the end-to-end operations and automation of the network, including network operations centres (NOC) and fieldwork. This included detecting incidents affecting the network performance and notifying CSPs of the possible first cut analysis. About 48 percent of surveyed CSPs are leveraging AI in their network operations.
Cloud and infrastructure operations
AI use cases related to improving the effectiveness, availability, and stability of cloud and infrastructure operations. Examples include infrastructure fault detection and prediction and capacity management. Close to 35 percent of surveyed CSPs have implemented AI in cloud and infrastructure operations.
Customer case study: Far EasTone increases customer satisfaction rating by leveraging AI analytics in its 5G network.
Far EasTone (FET) a market-leading service provider in Taiwan, has been using AI in its 5G network to increase performance and differente itself in a highly competitive market. This has enabled a high-performing network with uplink and downlink speeds that outperform the three largest CSPs in Taiwan. Explore FET’s steps for success.
Dave Lu, Vice President Network and Technology, Far EasTone