AI in Telecommunication Market Insights:
Market Research Future (MRFR), in its latest “AI in Telecommunication Market” report, states that the global market of AI in telecommunication is expected to thrive at a CAGR of 32% during the assessment period (2018 to 2023). The need to simplify communication in the world of the digital is a surging need of the hour. This is promoting the adoption of AI-driven solutions by the telecom industry. Recently, due to increase in cases of telecommunication breakdown much noise in connectivity and other related inconveniences are observed. Hence, this is pressing the need for deploying AI in telecommunication to resolve connectivity issues. As per MRFR analysis, the AI in telecommunication market is expected to attain a valuation of about USD 1 billion by 2023.
Application of AI technology is redefining industrial processes by improving productivity, operational efficacy, cost management, automation, providing assistance in making quick decisions. The advent of wireless communication cast a deep impact on the telecom industry. While it brings to users a seamless method of communication, the mounting complexities in the technicality of wireless connectivity are creating potential opportunities for the market to surge. Another potential driver for the AI in Telecommunication Market growth is the growing demand for highly sophisticated and intelligent autonomous network solutions. In addition, the growing requirement for data-driven solutions is also expected to propel the AI in telecommunication market.
AI in Telecommunication Market Key Players:
MRFR listed renowned players functioning in the global AI for telecommunication market. They are; IBM Corporation (US), Huawei Technologies Co. Ltd (China), Intel Corporation (US), Microsoft Corporation (US), Nuance Communication (US), Cisco Systems (US), H2O.ai (US), ZTE Corporation (China), Salesforce (US), Google LLC (US), Infosys Limited (India), and others. The growing competition among key players can favor the market.
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AI in Telecommunication Market Segmental Analysis:
The AI in telecommunication market is assessed by component, technology, deployment mode, and application.
- By component, the market is sectioned into services and solutions.
- The solution segment is further sub-segmented into network security, network optimization, NFV (network function virtualization), SDN (software-defined network), and others. The services segment is sub-segmented into managed services and professional service.
- By deployment mode, the market is segmented into and on-premise and cloud.
- By technology, the market is classified into machine learning (ML), deep learning (DL), and natural language processing (NLP).
- By application, the market is segmented into traffic resource utilization, classification, network optimization, and others.
AI in Telecommunication Market Regional Analysis:
The increase in investment is being made for absorbing technologies, such as AL and big data analytics, in the telecommunication sector in the US. This is expected to gain considerable traction for the North America AI telecommunication market. An increase in the adoption of AI-driven solutions to enhance operational efficiency is likely to define the telecommunication industry’s progress. As per MRFR’s findings, the ai in telecom market in North America is expected to generate the highest revenue in the assessment period. Alongside, communication solutions providers in the region, such as AT&T, are observed to experiment with AI to bring in the next-gen wireless technology. It is likely to favor the regional market growth.
In Asia Pacific, the market is expected to experience a rapid expansion in the review period. It is due to the rise in funding for research and development in the field of AI that can benefit the telecommunication industry. In addition, increase in the adoption of NFV and SDN technologies that are dedicated to improving the functioning of enterprises by enabling network to be more powerful, cost-efficient, flexible and aid in the anomaly detection, network orchestration, predictive maintenance, others.
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