According to markets and markets, the global market for AI software in the telecommunication industry has increased from a modest 5235.7 million in 2016 to nearly 2.5 billion.
Unsurprisingly, the start of Artificial Intelligence not only allows telcos to invest and perform better but also to gain profits, making the transition to AI at least, partially. Telecom operators will be able to generate additional and meaningful revenue streams by tapping into business units that they may have previously benefited from.
Let’s take a closer look at three key areas of interest for telecom businesses in the AI space: — Improve performance, increased profitability and additional profitability of their service offering, and try to find better uses of AI and data science. The telco sector.
Combatting Overload
In place of AI, your network can automatically respond to any significant overload. Detecting overload, automating the number of virtual machines needed to manage the amount of incoming, and most virtual traffic through these virtual machines can be networked immediately and without human intervention.
Optimizing Service Quality by Predicting Future Network Usage
Artificial Intelligence technology can help you optimize your service quality. You can use machine learning algorithms to track how the usage of your network changes across different geographies over a period of time. Many factors contribute to achieving good optimization results, including time zone, hour, weather, national or regional holidays, and more.
Performing Predictive Maintenance
Without artificial intelligence, you cannot foresee a hardware-related network problem until it is, in fact, affected or interrupted by your normal operation.
Machine learning is now turning the tables on you by giving you the ability to detect various horrible network signals that are a precursor to impending network failure.
In summary, artificial intelligence can take your network’s visibility and reliability to a whole new level.
Averting Malicious Actions
Machine learning can reliably protect your network against malicious activity, for example, DDoS attacks.
With Machine Learning, your network can be trained to detect a large number of similar requests, simultaneously dump it, and decide whether to flat-out reject these requests or manually move to another, less busy data center. By your employees.
