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Global Artificial Intelligence for Telecommunications Applications Market Opportunities and Forecast 2020-2027

  • DLR567
  • 06 October, 2021
  • Service & Software
  • Pages: 120
  • Global
Global Artificial Intelligence for Telecommunications Applications 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 (contact center analytics and marketing campaign analytics)), By Component (Solutions [Software tools, Platforms], Services [Professional services, Managed services]), By Deployment Mode (Cloud, On-premises), and opportunities and forecast 2020-2027

Artificial Intelligence for Telecommunications Applications Market Overview

Together with 5G, the Internet of Things and cloud computing, artificial intelligence is radically reshaping the telecommunications landscape in an era of advanced digitization and high-speed technological development. Artificial Intelligence applications in the telecommunications industry use advanced algorithms to look for patterns within the data, enabling telcos to both detect and predict network anomalies, and allowing them to proactively fix problems before customers are negatively impacted. The global Artificial Intelligence for Telecommunications Applications market is expected to grow at a sound pace in the times to follow.
 
The global Artificial Intelligence for Telecommunications Applications market is anticipated to rise because of an increasing number of AI-enabled smartphones. These phones have many features such as image recognition, voice recognition, robust security, and many as compared to the traditional phones. Due to this key reason, it is becoming popular among users. Moreover, the application of AI in Telecommunication is beneficial for telecom operators as well, because it provides a simpler and easier interface that aids to provide complex processes or telecom services. 
 
Besides this, artificial intelligence significantly helps in improving the efficiency of the telecommunication network. With the help of artificial intelligence and machine learning, the telecommunication network can autonomously act and make a qualified decision to lessen network congestion which is not possible in conventional telecommunication. This crucial fact further contributes more to the development of the market to a large extent.

Additionally, the growing need to monitor content on telecommunication networks and the need to eradicate human error from the telecommunication networks is the prime factor boosting the global Artificial Intelligence for Telecommunications Applications market. Also, the arrival of 5G technologies in mobile networks will give a solid boost to the market.

On the downside, incompatibility between telecommunication systems and AI technology which leads to integration complexity in these solutions is anticipated to restrain the growth of the Artificial Intelligence for Telecommunications Applications Market.

Report Metric Details
Market size available for years 2019–2027
Base year considered 2019
Forecast period 2020–2027
Forecast unit Value (USD Million)
Segments covered Technology, Application, Component, Deployment Mode, and Region
Regions covered North America (the U.S. and Canada), Europe (UK, Germany, France, Italy, Spain, Russia, Rest of Europe), Asia-Pacific (China, India, Japan, Australia, South East Asia, Rest of Asia Pacific), Latin America and the Middle East and Africa (Brazil, Saudi Arabia, UAE, Rest of LAMEA)
Companies covered Microsoft Corporation, Atomwise, Inc., H2O ai, Sense.ly, Inc., Zebra Medical Vision, Inc., Lifegraph, Baidu, Inc., International Business Machines Corporation, NVIDIA Corporation, Enlitic, Inc., Google, LLC, and Intel Corporation.


Covid-19 Impact on Artificial Intelligence for Telecommunications Applications Market

Like many other industries, COVID-19 badly knocked the electronic and semiconductor industries. This unprecedented event has impacted nearly 230 countries in just a few weeks, resulting in the forced shutdown of manufacturing and transportation activities within and across the countries. This has directly affected the overall sector's growth. It is estimated that COVID-19 to leave more than USD 30 billion impacts on the electronics and semiconductor industry. The sector is majorly affected due to transport restrictions on major electronics and semiconductor raw material providers. However, the emerging need for semiconductors in several industries will offer rapid market recovery over the future period.

Artificial Intelligence for Telecommunications Applications Market Segment Overview



Based on Application, the Customer analytics segment is projected to have the highest share in the global Artificial Intelligence for Telecommunications Applications market. This is due to the increasing need for real-time behavioral insights. Artificial intelligence allows operators to collect and analyze the customer’s data from a subscriber's intelligencer perspective. Further, this information can be used in several situations, such as advertisements and personalized offers for the subscriber. Again, this information can be used by operators to achieve network optimization with improved utilization of network resources. According to Technologies, Natural Language Processing (NLP) is the fastest-growing segment in the market. In the telecommunication industry, utilization of the NLP technology is rising to read the information stored in the digital format and understand the human languages from several data sets.
 
Artificial Intelligence for Telecommunications Applications Market, By Technology
·       Machine learning and deep learning
·       Natural Language Processing (NLP)
 
Artificial Intelligence for Telecommunications Applications Market, By Application
·       Customer analytics
·       Network security
·       Network optimization
·       Self-diagnostics
·       Virtual assistance
·       Others (contact center analytics and marketing campaign analytics)
 
Artificial Intelligence for Telecommunications Applications Market, By Component
  • Solutions
    • Software tools
    • Platforms
  • Services
    • Professional services
    • Managed services
Artificial Intelligence for Telecommunications Applications Market, By Deployment Mode
·       Cloud
·       On-premises
 
Artificial Intelligence for Telecommunications Applications Market Regional Overview

In terms of region, North America is anticipated to have the maximum share in the global Artificial Intelligence for Telecommunications Applications market. The North American region has shown bigger investments in the market, and many vendors have evolved to provide to the rapidly growing market. Significant growth is projected in the region during the forecast period. In addition to this, in North America, AI in telecommunication technology is effectively used for several applications, such as network optimization, network security, customer diagnostics, and virtual assistance. Similarly, the market in the Asia Pacific is projected to rise at a considerable rate in the coming years. The rapid technological advancements in developing countries, such as China and India is a prime factor that escalates the growth of the market in this region.  
 
Artificial Intelligence for Telecommunications Applications Market, By Geography
 
·       North America (US & Canada)
·       Europe (UK, Germany, France, Italy, Spain, Russia & Rest of Europe)
·       Asia-Pacific (Japan, China, India, Australia, & South Korea, & Rest of Asia-Pacific)
·       LAMEA (Brazil, Saudi Arabia, UAE & Rest of LAMEA)

Artificial Intelligence for Telecommunications Applications Market, Key Players

·       Microsoft Corporation
·       Atomwise, Inc.
·       H2O ai
·       Sense.ly, Inc.
·       Zebra Medical Vision, Inc.
·       Lifegraph
·       Baidu, Inc.
·       International Business Machines Corporation
·       NVIDIA Corporation
·       Enlitic, Inc.
·       Google, LLC
·       Intel Corporation

Frequently Asked Questions (FAQ) :

Q1. What are the driving factors for the Artificial Intelligence for Telecommunications Applications market?

A. Increasing awareness among telecommunication enterprises about the features and benefits of the AI technology in the telecommunication industry, growing adoption of AI for several applications in the telecommunication industry, and utilization of AI-enabled smartphones are significant factors that boost the growth of Artificial Intelligence for Telecommunications Applications market.

Q2. What are the restraining factors for the Artificial Intelligence for Telecommunications Applications market?

A. The incompatibility between telecommunication systems and AI technology which leads to integration complexity in these solutions is anticipated to restrain the growth of the Artificial Intelligence for Telecommunications Applications Market.

Q3. Which Segments are covered in the Artificial Intelligence for Telecommunications Applications market report?

A. Technology, Application, Component, Deployment Mode, and Region, these segments are covered in the Artificial Intelligence for Telecommunications Applications market report.

Q4. Which segment is projected to hold the largest share in the Artificial Intelligence for Telecommunications Applications Market. ?

A. The Customer analytics segment is projected to hold the largest share in the Artificial Intelligence for Telecommunications Applications Market.

Q5. Which are the prominent players in the Artificial Intelligence for Telecommunications Applications Market?

A. Microsoft Corporation, Atomwise, Inc., H2O ai, Sense.ly, Inc., Zebra Medical Vision, Inc., Lifegraph, Baidu, Inc., International Business Machines Corporation, NVIDIA Corporation, Enlitic, Inc., Google, LLC, and Intel Corporation. are some of the key players in the Artificial Intelligence for Telecommunications Applications Market.
Artificial Intelligence for Telecommunications Applications Market Study Global Market Analysis, Insights and Forecast, 2020-2027

    1. Introduction

    • 1.1. Research Scope
    • 1.2. Market Segmentation
    • 1.3. Research Methodology
    • 1.4. Definitions and Assumptions

    2. Executive Summary

      3. Market Dynamics

      • 3.1. Market Drivers
      • 3.2. Market Restraints
      • 3.3. Market Opportunities

      4. Key Insights

      • 4.1. Key Emerging Trends – For Major Countries
      • 4.2. Latest Technological Advancement
      • 4.3. Regulatory Landscape
      • 4.4. Industry SWOT Analysis
      • 4.5. Porters Five Forces Analysis

      5. Global Artificial Intelligence for Telecommunications Applications Market Analysis (USD Billion), Insights and Forecast, 2020-2027

      • 5.1. Key Findings / Summary
      • 5.2. Market Analysis, Insights and Forecast – By Technology
        • 5.2.1. Machine learning and deep learning
        • 5.2.2. Natural Language Processing (NLP)
      • 5.3. Market Analysis, Insights and Forecast – By Application
        • 5.3.1. Customer analytics
        • 5.3.2. Network security
        • 5.3.3. Network optimization
        • 5.3.4. Self-diagnostics
        • 5.3.5. Virtual assistance
        • 5.3.6. Others (contact center analytics and marketing campaign analytics)
      • 5.4. Market Analysis, Insights and Forecast – By Component
        • 5.4.1. Solutions
          • 5.4.1.1. Software tools
          • 5.4.1.2. Platforms
        • 5.4.2. Services
          • 5.4.2.1. Professional services
          • 5.4.2.2. Managed services
    • 5.5. Market Analysis, Insights and Forecast – By Deployment Mode
      • 5.5.1. Cloud
      • 5.5.2. On-premises
    • 5.6. Market Analysis, Insights and Forecast – By Region
      • 5.6.1. North America
      • 5.6.2. Europe
      • 5.6.3. Asia Pacific
      • 5.6.4. Latin America, Middle East and Africa
    • 6. North America Artificial Intelligence for Telecommunications Applications Market Analysis (USD Billion), Insights and Forecast, 2020-2027

      • 6.1. Key Findings / Summary
      • 6.2. Market Analysis, Insights and Forecast – By Technology
        • 6.2.1. Machine learning and deep learning
        • 6.2.2. Natural Language Processing (NLP)
      • 6.3. Market Analysis, Insights and Forecast – By Application
        • 6.3.1. Customer analytics
        • 6.3.2. Network security
        • 6.3.3. Network optimization
        • 6.3.4. Self-diagnostics
        • 6.3.5. Virtual assistance
        • 6.3.6. Others (contact center analytics and marketing campaign analytics)
      • 6.4. Market Analysis, Insights and Forecast – By Component
        • 6.4.1. Solutions
          • 6.4.1.1. Software tools
          • 6.4.1.2. Platforms
        • 6.4.2. Services
          • 6.4.2.1. Professional services
          • 6.4.2.2. Managed services
    • 6.5. Market Analysis, Insights and Forecast – By Deployment Mode
      • 6.5.1. Cloud
      • 6.5.2. On-premises
    • 6.6. Market Analysis, Insights and Forecast – By Country
      • 6.6.1. U.S.
      • 6.6.2. Canada
    • 7. Europe Artificial Intelligence for Telecommunications Applications Market Analysis (USD Billion), Insights and Forecast, 2020-2027

      • 7.1. Key Findings / Summary
      • 7.2. Market Analysis, Insights and Forecast – By Technology
        • 7.2.1. Machine learning and deep learning
        • 7.2.2. Natural Language Processing (NLP)
      • 7.3. Market Analysis, Insights and Forecast – By Application
        • 7.3.1. Customer analytics
        • 7.3.2. Network security
        • 7.3.3. Network optimization
        • 7.3.4. Self-diagnostics
        • 7.3.5. Virtual assistance
        • 7.3.6. Others (contact center analytics and marketing campaign analytics)
      • 7.4. Market Analysis, Insights and Forecast – By Component
        • 7.4.1. Solutions
          • 7.4.1.1. Software tools
          • 7.4.1.2. Platforms
        • 7.4.2. Services
          • 7.4.2.1. Professional services
          • 7.4.2.2. Managed services
    • 7.5. Market Analysis, Insights and Forecast – By Deployment Mode
      • 7.5.1. Cloud
      • 7.5.2. On-premises
    • 7.6. Market Analysis, Insights and Forecast – By Country
      • 7.6.1. UK
      • 7.6.2. Germany
      • 7.6.3. France
      • 7.6.4. Italy
      • 7.6.5. Spain
      • 7.6.6. Russia
      • 7.6.7. Rest of Europe
    • 8. Asia Pacific Artificial Intelligence for Telecommunications Applications Market Analysis (USD Billion), Insights and Forecast, 2020-2027

      • 8.1. Key Findings / Summary
      • 8.2. Market Analysis, Insights and Forecast – By Technology
        • 8.2.1. Machine learning and deep learning
        • 8.2.2. Natural Language Processing (NLP)
      • 8.3. Market Analysis, Insights and Forecast – By Application
        • 8.3.1. Customer analytics
        • 8.3.2. Network security
        • 8.3.3. Network optimization
        • 8.3.4. Self-diagnostics
        • 8.3.5. Virtual assistance
        • 8.3.6. Others (contact center analytics and marketing campaign analytics)
      • 8.4. Market Analysis, Insights and Forecast – By Component
        • 8.4.1. Solutions
          • 8.4.1.1. Software tools
          • 8.4.1.2. Platforms
        • 8.4.2. Services
          • 8.4.2.1. Professional services
          • 8.4.2.2. Managed services
    • 8.5. Market Analysis, Insights and Forecast – By Deployment Mode
      • 8.5.1. Cloud
      • 8.5.2. On-premises
    • 8.6. Market Analysis, Insights and Forecast – By Country
      • 8.6.1. China
      • 8.6.2. India
      • 8.6.3. Japan
      • 8.6.4. Australia
      • 8.6.5. South East Asia
      • 8.6.6. Rest of Asia Pacific
    • 9. Latin America, Middle East and Africa Artificial Intelligence for Telecommunications Applications Market Analysis (USD Billion), Insights and Forecast, 2020-2027

      • 9.1. Key Findings / Summary
      • 9.2. Market Analysis, Insights and Forecast – By Technology
        • 9.2.1. Machine learning and deep learning
        • 9.2.2. Natural Language Processing (NLP)
      • 9.3. Market Analysis, Insights and Forecast – By Application
        • 9.3.1. Customer analytics
        • 9.3.2. Network security
        • 9.3.3. Network optimization
        • 9.3.4. Self-diagnostics
        • 9.3.5. Virtual assistance
        • 9.3.6. Others (contact center analytics and marketing campaign analytics)
      • 9.4. Market Analysis, Insights and Forecast – By Component
        • 9.4.1. Solutions
          • 9.4.1.1. Software tools
          • 9.4.1.2. Platforms
        • 9.4.2. Services
          • 9.4.2.1. Professional services
          • 9.4.2.2. Managed services
    • 9.5. Market Analysis, Insights and Forecast – By Deployment Mode
      • 9.5.1. Cloud
      • 9.5.2. On-premises
    • 9.6. Market Analysis, Insights and Forecast – By Country
      • 9.6.1. Brazil
      • 9.6.2. Saudi Arabia
      • 9.6.3. UAE
      • 9.6.4. Rest of LAMEA
    • 10. Competitive Analysis

      • 10.1. Company Market Share Analysis, 2018
      • 10.2. Key Industry Developments
      • 10.3. Company Profile
      • 10.4. Microsoft Corporation
        • 10.4.1. Business Overview
        • 10.4.2. Segment 1 & Service Offering
        • 10.4.3. Overall Revenue
        • 10.4.4. Geographic Presence
        • 10.4.5. Recent Development
      *Similar details will be provided for the following companies
      • 10.5. Atomwise, Inc.
      • 10.6. H2O ai
      • 10.7. Sense.ly, Inc.
      • 10.8. Zebra Medical Vision, Inc.
      • 10.9. Lifegraph
      • 10.10. Baidu, Inc.
      • 10.11. International Business Machines Corporation
      • 10.12. NVIDIA Corporation
      • 10.13. Enlitic, Inc.
      • 10.14. Google, LLC

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