Artificial intelligence (AI), also called machine intelligence, is a part of computer science that helps replicate human intelligence processes by machines, and it is designed to think like humans and mimic their actions. These processes include learning, speech and text recognition, problem-solving, and reasoning. The increasing need to accumulate, assess, utilize, and eventually monetize billions of chunks of data and information has led to the introduction of machine learning, artificial intelligence, and big data. AI has been introduced to meet the ever-growing demand for automation. AI is being used across various areas of the telecommunications segment and thus, has become a new trend in the telecom industry.

The telecommunications sector is facing complexities with the growing number of networking facilities, customer care, service configuration, and billing processes. As the market is growing, demand and economic pressure are increasing, which is creating several challenges for the telco industry. To meet the ever-increasing demand from millions of subscribers, the communication service providers (CSPs) are investing in AI solutions to bring optimization in the operational support services. The telecom industry is deploying machine learning and artificial intelligence in various facets of their business, from improving predictive maintenance and customer experience, to enhancing network reliability. Various telecom operators such as Nokia, Vodafone, Telia, and others have also started deploying AI-powered technologies in both internal and business-to-business processes.

• Virtual Assistants
  
  Virtual assistants enable telecom service providers to reduce complexities for proper customer care management. VR technology such as Intelligent Virtual Agents (IVA), a human-like graphical chatbot, is gaining importance in the telecommunication sector. IVA is built on the laws of artificial intelligence and is programmed to interact with humans. These technologies help the Telcom industry in improving customer experience and satisfaction, and in optimizing a huge number of processes related to billing inquiries, troubleshooting, device settings, etc.
• Network Optimization
  
  AI help the telecom industry to automatically improve network quality with the help of AI-powered self-optimizing networks (SONs). It helps in redeploying power at distinct network loads and thus, deliver improved quality services to subscribers. The use of advanced algorithms also helps the telecommunication industry in processing large amounts of data and call detail records, which help in identifying patterns and detecting and predicting network anomalies.
• Robotic Process Automation (RPA)
  
  RPA is the use of software with machine learning and artificial intelligence abilities to manage high-volume repeated tasks and automate routine tasks with the help of "software robots". RPA helps telecommunication providers automate their back-end activities such as streamlining customer support, data reconciliation, data entry or validation, as well as performing up-sell and cross-sell using AI-powered assisted calls. Robotic process automation applications allow CSPs to improve efficiency, reduce costs, deliver a better customer experience, and enhance accuracy.

• Vodafone
  Vodafone Group, a British multinational telecommunications conglomerate, has deployed virtual assistant app “TOBi” to improve customer services. TOBi, a text bot, has helped Vodafone enhance customer engagement and personalize their sales journey through directly answering customer questions, addressing problems or suggestions, and offering more appropriate products.
• Telia
  
  Telia Company AB, a Swedish multinational telephone company, has used machine learning and AI-powered technologies to identify the most valuable accounts based on available data, keeping the company’s database continually up to date. Further, Telia has incorporated virtual assistants to its customer services chatbots to provide a better experience to its customers.
• China Mobile
  
  China Mobile Limited, a leading telecommunications services provider in Mainland China, is leveraging AI-enabled and big data technologies for fraud detection. It has introduced “Tiandun”, a big data-based anti-fraud system, to detect fraudulent activity in order differentiate normal calls or text from spam calls or text and then stop them.

AI Trends:

• Predictive analytics, driven by artificial intelligence, is helping the telecom industry in providing better services by way of utilizing data, advanced algorithms, and machine learning techniques to anticipate future results based on historical information.
• Big data platforms such as Spark allow programmers to work on large data sets, well beyond the capacities of a single server.
• Search Engine Artificial intelligence and machine learning have introduced users to a new method to search by using images and voice, unlike the text mode. Moreover, because of the integration of AI and ML into mobile apps, it has now become compulsory for Android developers to develop an image recognition system and voice recognition system. Further, AI will also provide app localization for enhancing the conversion rate.
• SK Telecom enhances customer experience through automated detection, troubleshooting, and optimization of mobile networks, using big data and machine learning.
• Artificial Intelligence defined 5G Radio Access Networks (RAN) is a flexible, rapidly deployable, and cross-layer artificial intelligence (AI)-based framework to enable the imminent and future demands on 5G and beyond.

The Future of AI in the Telecommunication Industry: