AI in Telecommunication  Market 2017-2023: Industry development trends and strategic plan for positive Growth discuss in research report

The increasing adoption of AI for various applications in the telecommunication industry and the utilization of AI-enabled smartphones are expected to be driving the growth of the AI in telecommunication market. Incompatibility concerns between the AI technology and telecommunication systems, which may generate integration complexities in AI in telecommunication solutions, are expected to act as restraints for the growth of the market.

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Artificial intelligence (AI) is group of methodology that focus on formation of intelligent machines with the help of human intelligence such as visual perception, speech recognition, decision-making, and translation between languages. 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.

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Key Companies

The key industry players include 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, and others.

Market Segment by Regions, regional analysis covers
North America (United States, Canada and Mexico)
Europe (Germany, France, UK, Russia and Italy)
Asia-Pacific (China, Japan, Korea, India and Southeast Asia)
South America (Brazil, Argentina, Colombia)
Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

Market Segment by Type, covers
Solutions
Services

Market Segment by Applications, can be divided into
Network Optimization
Network Security
Customer analytics
Others

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TOC :
1 Industry Overview
1.1 AI in Telecommunication Market Overview
1.1.1 AI in Telecommunication Product Scope
1.1.2 Market Status and Outlook
1.2 Global AI in Telecommunication Market Size and Analysis by Regions (2013-2018)
1.2.1 United States AI in Telecommunication Market Status and Outlook
1.2.2 EU AI in Telecommunication Market Status and Outlook
1.2.3 Japan AI in Telecommunication Market Status and Outlook
1.2.4 China AI in Telecommunication Market Status and Outlook
1.2.5 India AI in Telecommunication Market Status and Outlook
1.2.6 Southeast Asia AI in Telecommunication Market Status and Outlook
1.3 Classification of AI in Telecommunication by Service Patterns
1.3.1 Global AI in Telecommunication Revenue (Million USD) and Growth Comparison by Service Patterns (2013-2023F)
1.3.2 Global AI in Telecommunication Revenue (Million USD) Market Share by Service Patterns in 2017
1.3.3 Solutions
1.3.4 Services
1.4 AI in Telecommunication Market by End Users/Application
1.4.1 Network Optimization
1.4.2 Network Security
1.4.3 Customer Analytics
2 Global AI in Telecommunication Competition Analysis by Players
2.1 Global AI in Telecommunication Market Size (Million USD) by Players (2017-2018E)
2.2 Competitive Status
3 Company (Top Players) Profiles and Key Data
3.1 IBM 20
3.1.1 Company Profile
3.1.2 Main Business/Business Overview
3.1.3 Products, Services and Solutions
3.1.4 IBM AI in Telecommunication Revenue (Million USD) (2017-2018)
3.1.5 Recent Developments
3.2 Microsoft
3.2.1 Company Profile
3.2.2 Main Business/Business Overview
3.2.3 Products, Services and Solutions
3.2.4 Microsoft AI in Telecommunication Revenue (Million USD) (2017-2018)
3.2.5 Recent Developments
3.3 Intel
3.3.1 Company Profile
3.3.2 Main Business/Business Overview
3.3.3 Products, Services and Solutions
3.3.4 Intel AI in Telecommunication Revenue (Million USD) (2017-2018)
3.3.5 Recent Developments
3.4 AT&T
3.4.1 Company Profile
3.4.2 Main Business/Business Overview
3.4.3 Products, Services and Solutions
3.4.4 AT&T AI in Telecommunication Revenue (Million USD) (2017-2018)
3.4.5 Recent Developments
3.5 Cisco Systems
3.5.1 Company Profile
3.5.2 Main Business/Business Overview
3.5.3 Products, Services and Solutions
3.5.4 Cisco Systems AI in Telecommunication Revenue (Million USD) (2017-2018)
3.5.5 Recent Developments

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