Nowadays, telecom companies are adopting technologies like SDN-NFV, virtualization etc. AI or Artificial Intelligence is going to play a major role in smooth integration of such technologies and automating the networks.

AI applications in circles of mobile networks focus around 3 applications- Network Function Virtualization (NFV), Software Defined Networks (SDN) and Self Optimizing Networks (SON). Among these, SON’s are most current.

SON’s enable operators automatically to optimize network quality on basis of traffic information by time zone and region based machine learning algorithms. As per studies, 31% of telecom organizations are focusing to exploit existing infrastructure and remaining are making new technology investments for AI systems.

While these are global trends, artificial intelligence in Telecom india applications are burgeoning. These are driven primarily by enterprise needs to drive viable efficiencies and consumer demand for contextualization.

AI will help telecom operators in analyzing conversions rates of offers, subscriber profiling, network activity and trends in content usage. This will help them push offers which are tailored as per needs of subscribers at the right time.

Making use of data analytics and AI, operators will be able to identify and promote several services to customers at the right time. For instance, with regard to postpaid customers, operators should encourage services of high-speed data and offer customized data packs when subscriber is running low on data. The crucial factor is timing of providing subscriber intelligence based tailored packages.

Example is the case of SK Telecom which has deployed an AI-assisted network with capabilities of machine learning and big data analytics to improve customer experience, via automated detection, optimization and trouble shooting of mobile networks.


Even as affordable and reliable bandwidth is enabled, it opens up a wide arena of opportunities which can spread over telecom networks. This makes possible convergence at network level. This is then value enhanced by contributing intelligence and dynamism inside the systems via AI, that makes the solution reactive, proactive and intuitive.

Telecom becomes the default highway for anything related to digital and adds several opportunities in the telecom domain. There will be much differences with regard to present perception of telecom and may involve a different set of revenue streams.

AI will have an impact on a variety of areas- most crucial being network optimization, resource utilization, anomaly prediction and detection, network orchestration and traffic classification. Additionally, AI will help mobile devices with chat bots and virtual assistants.

AI is also helping in automating networks. Emerging technologies like cloud are pushing networks to handle more volumes of data, which makes automation vital for superior network connectivity and planning. With AI, networks can take independent decisions. The network will also add intelligence, so it will grow in capabilities like humans.

AI based applications of intelligent networks like precision algorithms can offer intelligent network operation/optimization solutions. Also, AI technology will also lead to the evolution of self-healing, self-optimizing and automatic networks, supported by high performance computing power and capabilities of data analytics.

AI enabled networks can think beyond their correlative programming and suggest scenarios based on outcomes. In the future, AI can differentiate between causal and correlative and actively pursue their own choice of outcomes beyond the scope of human programming. Uses of artificial intelligence in Telecom companies are thus highly versatile.

These are all some of the uses of AI in the telecom industry.

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