Artificial Intelligence in Telecommunication Market (By Technology: Machine learning and deep learning, Natural Language Processing (NLP); By Application: Customer analytics, Network security, Network optimization, Self-diagnostics, Virtual Assistance, Others; By Component: Solutions, Services; Market By Deployment Mode: Cloud, On-premises) - Global Industry Analysis, Size, Share, Growth, Trends, Revenue, Regional Outlook and Forecast 2022 – 2030

Published Date : Apr 2022 | No. of Pages : 250 Pages | Category : ICT

The global artificial intelligence in telecommunication market size is expected to be worth around US$ 9.8 billion by 2030 from valued at US$ 680 million  in 2021 and is anticipated to grow at a CAGR of 39% during forecast period 2022 to 2030.

The main application of artificial intelligence in telecommunications is for network management. The two key technologies that are widely in telecommunication industry are expert systems and machine learning. However, AI is expected to be more beneficial in telecom industry, if the operators upgrade their networks to Software Defined Networks (SDNs), which leads to network virtualization and the deployment of relatively better cloud-based services.

Advent of The fifth generation of mobile networks (5G) and Internet of Things (IoT) technologies, to build future networks is expected to aid in integration of AI in telecom industry. Mobile networks have to deal with heterogeneous data coming from all over the world and from a huge variety of systems, retailers and network types and they should have the ability to act in real-time. So, the analysis of these huge data sets from all over the world is time consuming and somewhere it is next to impossible. In this case Artificial Intelligence plays a key role because it is used to predict and analyze issues faster than human. Artificial Intelligence will make the fifth generation of mobile networks more open enabling connectivity to predictability.

To solve these issues in the telecom industry, machine learning tools are used, which is used to tackle the churning prediction problem. The methods used for solving churning problem includes artificial neural networks, decision trees learning, regression analysis, logistic regression, support vector machines, naive Bayes, sequential pattern mining and market basket analysis, linear discriminant analysis, and rough set approach. Hence, the use of machine learning helps to detect fraudulent calls in mobile phones by examining the user’s calling behavior.

However, lack of availability of cheaper hardware to develop AI-enabled products is the major factor restraining the growth of the AI in telecommunication market.

Report Scope of the Artificial Intelligence in Telecommunication Market

Report Coverage Details
Market Size by 2030 USD 9.8 Billion
Growth Rate from 2022 to 2030 CAGR of 39%
Largest Market North America
Fastest Growing Market Asia Pacific
Base Year 2021
Forecast Period 2022 to 2030
Companies Mentioned Atomwise, Inc., Lifegraph, Sense.ly, Inc., Zebra Medical Vision, Inc., Baidu, Inc., H2O ai, IBM Watson Health, NVIDIA, Enlitic, Inc., Google, Inc., Intel Corporation, Microsoft Corporation

 

Application Insights

The customer analytics segment is expected to have the highest market share owing to the growing need for real-time behavioral insights. Artificial intelligence enables operators to collect and analyze the customer’s data from a subscriber's intelligencer perspective. This information can be further utilized in several scenarios, such as advertisements and personalized offers for the subscriber.

The virtual assistance segment is expected to portray the fastest growth over the forecast period due to the fact that customer service automation creates substantial savings for telecom companies. Also, customer support chatbots in the communication industry can be trained adequately as machine learning algorithms can automate inquiries and route customers to the optimal agent.

Regional Insights

North America accounted for the largest share in 2021 and will maintain dominance throughout the forecast years as the region is one of the early adopters of advanced technologies. Moreover, a growing number of telecom companies using automation and AI for customer service and network optimization purposes will support the region’s growth. For instance, in 2018, AT&T Intellectual Property launched the mobile 5G, supported by edge AI computing in the U.S.

On the other hand, Asia Pacific is projected to demonstrate growth at the fastest CAGR over the forecast period. This is attributed to rising adoption of machine learning and natural language processing technologies and several 5G pilot projects. This is expected to boost the AI market in telecom industry. For instance, China Telecom Corporation Ltd. established a new 5G base station in Lanzhou on December 2017 to expand 5G pilot projects in China. This growth is attributed to the rapid technological advancements in emerging economies, such as China and India. For instance, Huawei Technologies Co., Ltd., a global provider of telecommunications equipment and consumer electronics, is cooperating with China Telecom Corporation Ltd., internet access and mobile telecommunications services provider. This collaboration is anticipated to explore the radio cell capacity prediction and wireless network cell anomaly detection, based on the Network AI Engine (NAIE).

Key Players

  • IBM Corporation
  • Microsoft
  • Intel Corporation
  • Google
  • AT&T Intellectual Property
  • Cisco Systems
  • Nuance Communications, Inc.
  • Evolv Technology Solutions, Inc.
  • H2O.ai
  • Infosys Limited
  • Salesforce.com, Inc.
  • NVIDIA Corporation

Market Segmentation

By Technology

  • Machine learning and deep learning
  • Natural Language Processing (NLP)

By Application

  • Customer analytics
  • Network security
  • Network optimization
  • Self-diagnostics
  • Virtual assistance
  • Others

By Component

  • Solutions
    • Software tools
    • Platforms
  • Services
    • Professional services
    • Managed services

Market By Deployment Mode

  • Cloud
  • On-premises

By Region

  • North America
  • Europe
  • Asia Pacific (APAC)
  • Middle East and Africa (MEA)
  • Latin America

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