Navigating the AI Landscape: A Primer for CSPs

AI’s Many Benefits for CSPs

Since the release of ChatGPT, more and more people are talking about artificial intelligence (AI). But AI is not new. Businesses have been using forms of AI for almost five decades. According to McKinsey’s 2022 Global Survey on AI, 50% of respondents say their organization has adopted AI in at least one business unit or function. A survey of 400 telecom professionals worldwide revealed that 34% have been using AI for at least six months, with another 31% in the research or assessment stage. AI is paying off for the companies that are using it. Almost three quarters (73%) of survey respondents said their company saw increased annual revenue, and 80% saw reduced costs.

When used correctly, AI offers many benefits for communication service providers (CSPs), improving network performance, customer experience, operational efficiency and revenue generation.


What Is Artificial Intelligence?

There is no universally accepted definition of AI. Gartner, Inc. defines AI as “applying advanced analysis and logic-based techniques, including machine learning (ML), to interpret events, support and automate decisions and to take actions.”

Types of AI

Several types of AI are commonly used in business settings:


ML is used to analyze large quantities of data to find patterns and anomalies that people would likely miss. ML creates an algorithm (called a “model”) that “learns” through “training.” Algorithms identify patterns in data, providing new insights and predictions. ML recommends actions but does not direct systems to act without human guidance. For example, ML identifies increases in network traffic, enabling CSPs to allocate resources accordingly.


Conversational AI refers to a set of technologies that enable human-like interactions between computers and people. Powered by ML and natural language processing (NLP), conversational AI recognizes speech and text, understands intent and responds in a conversational manner. Some chatbots and virtual assistants employ conversational AI to automate customer service interactions.


Generative AI refers to algorithms (such as ChatGPT) that can create new content—such as text, computer code, and videos—based on the data they were trained on. Some businesses are starting to use ChatGPT to produce marketing and other content.


How CSPs Can Use AI

Optimize Network Performance

AI-powered network optimization and resource allocation. CSPs need AI to build the self-optimizing networks (SONs) that support the rapid growth of traffic on 5G networks. AI algorithms monitor the SONs, identifying traffic and usage patterns and detecting and predicting network anomalies. This information allows CSPs to (re)allocate resources and fix problems before they affect customers.


Predictive maintenance and fault detection. A ML algorithm can be trained to identify faults in different network functions, predict when those faults will occur and generate an alert when a flaw is discovered. AI can also identify the root cause of each fault, improving the CSP’s ability to resolve the underlying problem. Faults can include configuration errors, security breaches and hardware failures.


Real-time traffic management and congestion control. Machine learning analyzes real-time traffic patterns and device usage, adjusting the network configuration to accommodate changing demands. This reduces congestion, enhances network performance and reduces latency. AI algorithms can also prioritize traffic flows according to user requirements so critical applications and services receive the required network resources.


Streamline Operations

Automate routine tasks and processes. CSPs can use process automation to automate data entry, billing, order processing and other time-intensive back-office tasks. This saves time, reduces errors and frees staff to handle more critical projects.


Intelligent network planning and capacity management. Increases in network traffic impact the billing, customer service, and other departments. By predicting those increases, AI helps CSPs prepare to accommodate them. For example, if ML predicts a 20% increase in traffic in July, a CSP can optimize resource allocation and plan network capacity to ensure they meet the increase in demand.


AI-driven fraud detection and cybersecurity. By detecting suspicious behavioral patterns in real time, ML algorithms can reduce fraudulent activities such as fake profiles and unauthorized network access. AI-powered anti-fraud systems can immediately block user accounts or services, minimizing the damage.


Enhance the Customer Experience

Personalize recommendations and cross-sell/upsell offers. ML algorithms can be used to tailor recommendations and promotions based on customers’ behavior patterns and content preferences. Netflix has credited its recommendation engine with saving more than $1B per year by keeping members from canceling their subscription.


Improve customer support. AI-powered chatbots and virtual assistants improve customer experience and satisfaction by providing immediate, human-like responses to questions or concerns, 24/7.


Resolve network issues proactively via predictive analytics. Wireless subscribers actively seek out CSPs that deliver efficient, reliable and far-reaching network coverage. Almost half (45%) of smartphone user churn is due to poor network quality. Network analytics proactively identifies network issues and informs their resolution, preventing outages and decreasing latency and congestion. The end result? Better customer experience and retention.

AI has the potential to transform the telecommunications industry by improving network optimization and CX and streamlining operations.

Contact us to discover how CSG can enable you to capitalize on the advances in AI/ML to stay ahead of the market and meet the evolving needs of your customers.

Navigating the AI Landscape: A Primer for CSPs