Artificial Intelligence (AI), along with related technologies like Machine Learning (ML) and Deep Learning (DL) have been transforming every field and the media industry is no exception. Although these technologies have been around for quite some time, we still feel their strong presence today, landing in every major industry. They even completely changed the way we used to communicate years ago. An AI-powered Chatbot that interacts with you like a human. The use of AI in computer applications and tools such as logo design, shopping portals, among others, has been widely used, and with good reason.
According to a recent Transparency Market Research (TMR) report, the global market for AI is expected to grow exponentially in the coming years. The analysis predicts that the global artificial intelligence market will reach $3,061.35 billion by 2024.
When it comes to telecommunications, it is one of the fastest growing industries in the world and has applied artificial intelligence, Machine Learning, and Internet of Things (IoT) to improve their customer service experience. All the major telecommunications companies such as AT&T, Spectrum, Verizon and Century Link are leading the way with these innovative technologies to create an edge in their services.
* Optimize Network and Infrastructure.
Artificial intelligence allows you to optimize your network and infrastructure. Optimized solutions can analyze, troubleshoot and repair technical problems in real time and make services uninterrupted, increasing availability compared to what third parties can provide . This process creates a Self-Organizing Network (SON); This means that the network is self-configuring, self-healing, and self-optimizing.
As soon as the root cause of the technical problem is solved, a remedial action is taken and Machine Learning enables this to be applied in the day-to-day processes. In addition, this allows the system to predict when a similar problem will occur and resolve it in a pre-preventive manner, thus greatly improving performance.
* Data driven business decisions.
The telecommunications sector generates huge volumes of data every day. Telecom operators, with the use of AI and Machine Learning, extract meaningful and structured data to help managers make efficient and fast data-driven business decisions. This massive data helps prevent customer churn, identify customer segments, predict customer lifetime value, develop products, optimize processes, improve profitability, optimize price optimization and a lot more.
* Preventive maintenance in advance.
Artificial Intelligence helps telecom operators to conduct predictive analytics and provide better service by using data, complex algorithms and Machine Learning techniques to predict future outcomes on the basis of data. historical data. That means telecom companies can use data-driven insights to track equipment, predict failures, and proactively fix problems with telecommunications equipment like cable lines, cell towers, and more. mobile phones, data center servers, and even consumer set-top boxes.
* Robotic process automation.
Robotic Process Automation (RPA) is essentially an AI-based business process automation technology. Since telecommunications devices process huge amounts of data on a daily basis, the probability of human error is always high. But automating the entire business process through RPA, repetitive and rule-based operations are made more efficient, more accurate.
According to a study conducted by Deloitte, telecom, media and technology executives said that companies are investing a large amount in cognitive technology while 40% of them confirm that They have already received huge benefits and 75% expect that cognitive computing will dramatically change their company in the next three years.
Robotic process automation frees up customer service point of view (CSP) staff for more value-added work by streamlining the execution of complex, time-consuming processes and such as data entry, billing, human resource management, and order fulfillment.
* Fraud detection.
As one of the largest and ever-evolving sectors in the world, the telecommunications industry is highly prone to fraudulent activities. The biggest fraud cases the industry has witnessed are authorization, illegal access, theft or fake profile creation, fraud, duplication, and more. Fraudulent activity can damage a brand’s reputation in the marketplace.
This requires telecommunications businesses to deploy systemsng, fraud detection tools and mechanisms. Machine learning algorithms are very helpful in detecting fraud. These algorithms are applied to a large number of customers and operator data to determine the characteristics of normal traffic. Machine learning algorithms identify anomalies and use data visualization techniques, displaying them as real-time alerts to analysts.