Artificial intelligence (AI) has emerged as a key technology enabler in the telecom industry transformation, providing telecom businesses with the ability to streamline operations, enhance customer experience, and improve network performance.
Impact of AI Applications on the Telecom Industry
Here are some ways AI is impacting the telecom industry:
1. Improve Network Performance: Telecom companies can monitor network performance in real-time and resolve issues before they become major problems. They can predict network failures and take proactive measures to prevent them.
For example, AT&T uses AI to predict and prevent network outages, reducing downtime and improving customer satisfaction.
2. Streamline Operations: AI-powered tools are helping telecom businesses streamline their operations and reduce costs.
For example, AI-powered sales intelligence can help businesses identify potential customers, predict their needs, and personalize their experiences. They enable businesses to optimize their pricing, identify new revenue streams, and improve their sales processes.
3. Enhance Customer Experience and Satisfaction: AI enables telecom companies to provide 24/7 personalized and seamless customer experiences through AI-powered chatbots and virtual assistants.
AT&T, Verizon, Comcast, and virtually every other large telco use AI to improve customer service.
In another use case, telecoms can use AI to detect issues and recommend the right service based on customer data.
This data, historical knowledge, and personalized service can help companies create better products and services and market them to meet customer needs.
For example, Vodafone’s AI-powered recommendation engine analyzes customer data and provides personalized product recommendations based on their preferences and behaviors.
When Vodafone introduced its TOBi, its chatbot, customer satisfaction improved by 68%.
4. Predict Maintenance & Improve Network Optimization: AI-enabled predictive maintenance is an essential AI/ML application that improves customer satisfaction.
AI solutions based on historical data help telecom companies predict future malfunctions and resource utilization with predictive maintenance.
Data-derived insights enable businesses to monitor equipment, learn from historical data, anticipate equipment failure, and proactively repair it.
AI-powered drones have helped telecom operators capture cell phone tower damage and increase coverage during natural disasters.
Network optimization is another AI-enabled application. A Self-Organizing Network (SON) powered by AI can assist networks to continuously adapt and reconfigure themselves based on their current requirements.
In addition, it is useful when designing new networks. Since AI-enabled networks can self-analyze and self-optimize, they are more efficient at providing consistent service.
5. Robotic Process Automation: Robotic Process Automation (RPA) is an AI-based technology that automates repetitive business processes, especially operations, specifically repetitive tasks and actions governed by rules.
RPA improves operational efficiency by freeing operator time, allowing them to focus on more strategic tasks, such as error-free management of their back-office operations and workforce.
The RPA market is anticipated to reach $ 13 Billion by 2030, an increase of over $ 12 billion compared to 2020.
6. Predict Analysis and Increase Productivity: Telecoms possess vast customer data. Using AI and ML, telecoms can extract actionable business insights from this data, allowing them to make quicker and more informed business decisions.
AI helps with customer segmentation, preventing customer churn, predicting customer lifetime value, product development, improving margins, and price optimization, among other tasks.
Telecom companies must manage complexity to provide the best customer experience at the lowest cost.
Nokia’s new service uses AI/ML to reduce network maintenance time and ensure engineers have the latest network information and skills. In 2021, Nokia and Vodafone launched a Google Cloud-based ML product that fixes network anomalies before they affect Vodafone customers.
The product immediately detects and fixes mobile site congestion, interference, and latency, which can affect customer service. Vodafone’s Anomaly Detection Service automatically detects and fixes 80% of mobile network faults and capacity demands.
7. Detect Fraud: Telecom network engineers can detect instances of unauthorized access and false caller profiles with machine learning.
Algorithms monitor the global telecom network activity of CSPs to achieve this. Consequently, the network traffic on these networks is closely monitored.
The pattern recognition abilities of AI algorithms are reintroduced, allowing network administrators to identify potentially problematic situations such as a large number of calls from a false number or repeated blank calls from suspicious sources.
Telecom frauds include scam calls, mobile money fraud, SMS fraud, subscription fraud, and spoofing.
For example, Vodafone partnered with a data science-based company to analyze the network traffic for intelligent, data-driven fraud management.
In Conclusion
AI enables the telecom industry to improve its operations, enhance customer experience, and gain a competitive edge in the market.
Besides, there are cross-industrial applications with vast and varied opportunities for stakeholders to drive growth and innovation.
Draup’s sales intelligence platform enables service providers, startups, and enterprises to learn trends, prospects’ initiatives, and business intentions. The sales teams can address pain points and pitch their solutions/services to enterprises to create various applications.
