Telecommunication companies are generating billions of dollars in revenue annually by leveraging the power of Artificial Intelligence, Data Science, and IoT integrations. In 2020, a potential American telecom company/operator, AT&T, generated €161.5 billion in revenue, but there is a decline in annual revenues compared to 2021 and 2022. The reason behind the revenue decline can be the abandonment of Artificial intelligence technologies. So, what should these companies have to do? To achieve success over the competitors and increase revenue streams in 2023.

In every facet of life, challenges keep coming, and overcoming them is all we have learned so far, and that's how AI is surprising every industry with its capabilities to enrich businesses. Now, automation and AI technology is the new technological advancement adopted by the telecom industry to solve challenges like network failures, improper resource utilization, managing bandwidth requirements, and issues related to customer support. According to a study, the global AI market in the telecom industry is expected to grow by $8.63 billion between 2022 and 2026, at a CAGR of 47.33 %. The telecommunications industry is experimenting and delivering new innovative concepts to businesses using artificial intelligence. AI capabilities are extracted for business use from collecting necessary data such as customer profiles, log behaviors, mobile devices, networks, service utilization, sales data, geo-location intelligence, and billing to assist customers better.

The number of smartphone users across the world has skyrocketed over the last decade and promises to do so in the future too. Additionally, most business functions can now be executed on mobile devices. However, despite the mobile surge, telecom operators around the world are still not that profitable, with average net profit margins hovering around the 17% mark. The main reasons for the middling profit rates are the high number of market rivals vouching for the same customer base and the high overhead expenses associated with the sector. Communication Service Providers (CSPs) need to become more data-driven to reduce such costs and, automatically, improve their profit margins.

PRNewswire has recently reported on ABI Research regarding Mobile Broadband Operators. They are ramping up spending for big data and machine learning as they transform into digital service providers. With a long history of handling huge datasets, and with their path now blazed by the IT ecosystem, mobile operators will devote more than 50 billion to big data and machine learning analytics through 2021, forecasts ABI Research. Machine learning technologies will lead operators to profoundly change how they manage the telecom business. "Machine learning-based predictive analytics are applicable to all aspects of the telecom business," says Joe Hoffman, Managing Director and Vice President at ABI Research.

Mobile broadband operators are ramping up spend for big data and machine learning as they transform into digital service providers. With a long history of handling huge datasets, and with their path now blazed by the IT ecosystem, mobile operators will devote more than 50 billion to big data and machine learning analytics through 2021, forecasts ABI Research. Machine learning technologies will lead operators to profoundly change how they manage the telecom business. "Machine learning-based predictive analytics are applicable to all aspects of the telecom business," says Joe Hoffman, Managing Director and Vice President at ABI Research. "It is important that operators master and internalize these technologies and not rely solely on their vendors' expertise. Executives that overlook big data and machine learning risk irrelevance."