Uplift modeling, also known as individual treatment effect (ITE) estimation, is an important approach for data-driven decision making that aims to identify the causal impact of an intervention on individuals. This paper introduces a new benchmark dataset for uplift modeling focused on churn prediction, coming from a telecom company in Belgium, Orange Belgium. Churn, in this context, refers to customers terminating their subscription to the telecom service. This is the first publicly available dataset offering the possibility to evaluate the efficiency of uplift modeling on the churn prediction problem. Moreover, its unique characteristics make it more challenging than the few other public uplift datasets.

Today's telecommunication sectors face enormous demands from customers to offer a far better user experience and high-quality telecom services. Businesses got to overcome the challenge and competition with the help of customized AI in telecom for their users, focusing on long-term business relationships. AI is continuously revolutionizing the face of the Telecom Industry. The telecom sector is leveraging the potential of AI to analyze and work out the large volume of Big Data. It helps gain competitive and valuable insight to improve business process operations.

What may be the most appropriate definition of Artificial Intelligence (AI)? What are the broad requirements to develop and deploy AI models in a telecom sector? What are the challenges faced by telecom service providers in adopting AI? How can big data (BD) in the telecom sector be utilised for developing AI models? These are some of the questions that the Telecom Regulatory Authority of India (TRAI) is looking to deal with in its new consultation paper which seeks to understand how artificial intelligence and big data can be used in the telecom sector. The paper is open for consultation till September 16, 2022 and one can send their counter comments till September 30, 2022.

Artificial Intelligence has applications in all fields including telecommunications. Mobile data analytics, total network optimization, enhancing security, improvement of network operations, control of operational cost and network design are some of the areas where AI can be deployed. Prediction of consumer behaviour, introduction of such services which will be appreciated by him/her, launching of customised services, reduction of power consumption, improving resilience of the network, predictive maintenance, optimum utilisation of network elements, seamless provision of services and real time fraud detection and fraud prevention are other interesting applications of AI. As operators move from 4G to 5G implementation, network complexity and cost sharply increase because of implementation of Customer Experience Management (CEM), IOT, SDN (Software Defined Network), NFV (Network Function Virtualisation), 5G Radio access equipment and core infrastructure, 5G for private networks etc. But the average revenue per user is stagnating.

Like any other industry, the telecom industry is also going through a sea of change today. The industry has come in the forefront of the digital transformation and has made a remarkable shift in terms of newage technologies. The advent of these emerging technologies has allowed millions of people to experience new ways of acquiring information as well as carrying out interaction and communication, which somehow has created a long-term impact on the human lifestyle. There are many communication service providers (CSP's) that have started adopting a multi-channel approach to provide a great experience to its customers. From customer service to delivery, from personalisation to product quality, from dealing with complaints to social responsibility, customers mainly expects the top-quality service from the service providers. However, in case, if the customer does not get the services up to the mark, then he looks after another provider who meets up to their expectations.

DUBLIN--(BUSINESS WIRE)--The "Intelligence Report - Artificial Intelligence and the Telecoms Sector" report has been added to ResearchAndMarkets.com's offering. This report explores the key trends occurring in the Artificial Intelligence sector, the enterprises involved, various applications and the identification of potential opportunities for the telecoms industry. The International Telecommunications Union (ITU) highlighted both 5G and Artificial Intelligence as important innovations required to enable smart cities. For many years Artificial Intelligence (AI) was just a futuristic concept - but with recent progress in Machine Learning capabilities; the AI sector has been firmly pushed into the spotlight. In 2019 we will see this interest in Artificial Intelligence grow even further.

Data centres are expanding internationally 3.2.5 Growing maintenance and energy costs 3.2.6 Case study: Australia 3.2.7 Glimpses of the future 4. 5G trends 4.1 5G is an evolutionary process 4.2 5G in the global context 4.2.1 5G statistics and forecasts 4.3 The spectrum issue 4.3.1 5G spectrum developments 4.3.2

The telecommunications services industry is one of the fastest growing industries in the world and is already using machine learning (ML), artificial intelligence (AI) and Internet of Things (IoT) to enhance their customer service. According to a study by Transparency Market Research (TMR), the global market for artificial intelligence is estimated to post an impressive 36.1% CAGR between 2016 and 2024, rising to a valuation of US$3,061.35 billion by the end of 2024 from US$126.14 billion in 2015. As the market is seeing a rapid growth in Europe, North America and Latin America, the telecom services spending in Asia-Pacific region was projected to grow by around 2.06% in 2016 compared to 2015. Technavio's market research analysts predict that the global telecom IoT market to grow steadily and post an impressive CAGR of more than 42% by 2020. Even as IoT is set to revolutionize industries in its own way, it is worth noting that IoT would produce terabytes, petabytes and exabytes of big data.