The Europe AI in Telecommunication Market should witness market growth of 37.1% CAGR during the forecast period (2022-2028).
AI in telecommunications offers a simpler and easier interface to accommodate complex operations or telecom services. Moreover, expanding Over-The-Top (OTT) services like video streaming have changed how music and video content are distributed and consumed. As a result, the demand for bandwidth has increased significantly as more customers use OTT services. Handling this much traffic from OTT services results in high operational expenses (OpEx) for the telecom sector. Hence, AI assists the telecom sector in lowering operational costs by reducing the human interaction required for network configuration and maintenance.
Automation and AI can be used by telecom firms to lower operational costs while enhancing customer satisfaction. With computers performing human duties, such as choosing the traffic route by reading network material, artificial intelligence has already benefited the core of the telecommunications industry. Furthermore, it also assists in developing the self-optimizing network, which can shape the system based on current conditions within the bounds defined by the appropriate designer. It assists network operations in identifying problems, such as Service-Level Agreement (SLA) violations, and determining their underlying causes.
The British market for telecommunications is one of the world's largest. The availability of telecommunications infrastructure is deemed crucial since it facilitates substantial economic and social activities in the UK. Mobile and internet networks in the United Kingdom have accommodated the increase in distant employment. To ensure that data demand and consumption can be met, providers continue to extend their networks and increase their capacity. In the United Kingdom, 5G is being deployed in a non-standalone (NSA) mode, which is dependent on the 4G LTE core network.
With 5G core networks and 5G RAN, it is expected that all operators will eventually upgrade to 5G standalone (SA), especially as more 5G capabilities, including ultra-low latency communication (URLC) and virtual network functions, such as network slicing, increase and introduce new use cases for the technology. This continual rise of the region's telecommunications industry would result in the expansion of regional AI in telecommunication market.
The Germany market dominated the Europe AI in Telecommunication Market by Country in 2021, and would continue to be a dominant market till 2028; thereby, achieving a market value of $657.3 million by 2028. The UK market would generate a CAGR of 36% during (2022-2028). Additionally, The France market is poised to grow at a CAGR of 38.2% during (2022-2028).
Based on Technology, the market is segmented into Machine Learning, Natural Language Processing (NLP), Data Analytics, and Others. Based on Deployment, the market is segmented into On-premise, and Cloud. Based on Component, the market is segmented into Solution, and Service. Based on Application, the market is segmented into Network Optimization, Virtual Assistance, Customer Analytics, Self-Diagnostics, Network Security, and Others. Based on countries, the market is segmented into Germany, UK, France, Russia, Spain, Italy, and Rest of Europe.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include NVIDIA Corporation, AT&T, Inc., IBM Corporation, Infosys Limited, Intel Corporation, Microsoft Corporation, Salesforce.com, Inc., ZTE Corporation, Google LLC (Alphabet, Inc.), and Cisco Systems, Inc.
AI in telecommunications offers a simpler and easier interface to accommodate complex operations or telecom services. Moreover, expanding Over-The-Top (OTT) services like video streaming have changed how music and video content are distributed and consumed. As a result, the demand for bandwidth has increased significantly as more customers use OTT services. Handling this much traffic from OTT services results in high operational expenses (OpEx) for the telecom sector. Hence, AI assists the telecom sector in lowering operational costs by reducing the human interaction required for network configuration and maintenance.
Automation and AI can be used by telecom firms to lower operational costs while enhancing customer satisfaction. With computers performing human duties, such as choosing the traffic route by reading network material, artificial intelligence has already benefited the core of the telecommunications industry. Furthermore, it also assists in developing the self-optimizing network, which can shape the system based on current conditions within the bounds defined by the appropriate designer. It assists network operations in identifying problems, such as Service-Level Agreement (SLA) violations, and determining their underlying causes.
The British market for telecommunications is one of the world's largest. The availability of telecommunications infrastructure is deemed crucial since it facilitates substantial economic and social activities in the UK. Mobile and internet networks in the United Kingdom have accommodated the increase in distant employment. To ensure that data demand and consumption can be met, providers continue to extend their networks and increase their capacity. In the United Kingdom, 5G is being deployed in a non-standalone (NSA) mode, which is dependent on the 4G LTE core network.
With 5G core networks and 5G RAN, it is expected that all operators will eventually upgrade to 5G standalone (SA), especially as more 5G capabilities, including ultra-low latency communication (URLC) and virtual network functions, such as network slicing, increase and introduce new use cases for the technology. This continual rise of the region's telecommunications industry would result in the expansion of regional AI in telecommunication market.
The Germany market dominated the Europe AI in Telecommunication Market by Country in 2021, and would continue to be a dominant market till 2028; thereby, achieving a market value of $657.3 million by 2028. The UK market would generate a CAGR of 36% during (2022-2028). Additionally, The France market is poised to grow at a CAGR of 38.2% during (2022-2028).
Based on Technology, the market is segmented into Machine Learning, Natural Language Processing (NLP), Data Analytics, and Others. Based on Deployment, the market is segmented into On-premise, and Cloud. Based on Component, the market is segmented into Solution, and Service. Based on Application, the market is segmented into Network Optimization, Virtual Assistance, Customer Analytics, Self-Diagnostics, Network Security, and Others. Based on countries, the market is segmented into Germany, UK, France, Russia, Spain, Italy, and Rest of Europe.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include NVIDIA Corporation, AT&T, Inc., IBM Corporation, Infosys Limited, Intel Corporation, Microsoft Corporation, Salesforce.com, Inc., ZTE Corporation, Google LLC (Alphabet, Inc.), and Cisco Systems, Inc.
Scope of the Study
By Technology
- Machine Learning
- Natural Language Processing (NLP)
- Data Analytics
- Others
By Deployment
- On-premise
- Cloud
By Component
- Solution
- Service
By Application
- Network Optimization
- Virtual Assistance
- Customer Analytics
- Self-Diagnostics
- Network Security
- Others
By Country
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
Key Market Players
List of Companies Profiled in the Report:
- NVIDIA Corporation
- AT&T, Inc.
- IBM Corporation
- Infosys Limited
- Intel Corporation
- Microsoft Corporation
- Salesforce.com, Inc.
- ZTE Corporation
- Google LLC (Alphabet, Inc.)
- Cisco Systems, Inc.
Unique Offerings
- Exhaustive coverage
- The highest number of Market tables and figures
- Subscription-based model available
- Guaranteed best price
- Assured post sales research support with 10% customization free
Table of Contents
Chapter 1. Market Scope & Methodology1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Europe AI in Telecommunication Market, by Technology
1.4.2 Europe AI in Telecommunication Market, by Deployment
1.4.3 Europe AI in Telecommunication Market, by Component
1.4.4 Europe AI in Telecommunication Market, by Application
1.4.5 Europe AI in Telecommunication Market, by Country
1.5 Methodology for the research
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition & Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 Analyst's Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.3 Market Share Analysis, 2021
3.4 Top Winning Strategies
3.4.1 Key Leading Strategies: Percentage Distribution (2018-2022)
Chapter 4. Europe AI in Telecommunication Market by Technology
4.1 Europe Machine Learning Market by Country
4.2 Europe Natural Language Processing (NLP) Market by Country
4.3 Europe Data Analytics Market by Country
4.4 Europe Others Market by Country
Chapter 5. Europe AI in Telecommunication Market by Deployment
5.1 Europe On-premise Market by Country
5.2 Europe Cloud Market by Country
Chapter 6. Europe AI in Telecommunication Market by Component
6.1 Europe Solution Market by Country
6.2 Europe Service Market by Country
Chapter 7. Europe AI in Telecommunication Market by Application
7.1 Europe Network Optimization Market by Country
7.2 Europe Virtual Assistance Market by Country
7.3 Europe Customer Analytics Market by Country
7.4 Europe Self-Diagnostics Market by Country
7.5 Europe Network Security Market by Country
7.6 Europe Others Market by Country
Chapter 8. Europe AI in Telecommunication Market by Country
8.1 Germany AI in Telecommunication Market
8.1.1 Germany AI in Telecommunication Market by Technology
8.1.2 Germany AI in Telecommunication Market by Deployment
8.1.3 Germany AI in Telecommunication Market by Component
8.1.4 Germany AI in Telecommunication Market by Application
8.2 UK AI in Telecommunication Market
8.2.1 UK AI in Telecommunication Market by Technology
8.2.2 UK AI in Telecommunication Market by Deployment
8.2.3 UK AI in Telecommunication Market by Component
8.2.4 UK AI in Telecommunication Market by Application
8.3 France AI in Telecommunication Market
8.3.1 France AI in Telecommunication Market by Technology
8.3.2 France AI in Telecommunication Market by Deployment
8.3.3 France AI in Telecommunication Market by Component
8.3.4 France AI in Telecommunication Market by Application
8.4 Russia AI in Telecommunication Market
8.4.1 Russia AI in Telecommunication Market by Technology
8.4.2 Russia AI in Telecommunication Market by Deployment
8.4.3 Russia AI in Telecommunication Market by Component
8.4.4 Russia AI in Telecommunication Market by Application
8.5 Spain AI in Telecommunication Market
8.5.1 Spain AI in Telecommunication Market by Technology
8.5.2 Spain AI in Telecommunication Market by Deployment
8.5.3 Spain AI in Telecommunication Market by Component
8.5.4 Spain AI in Telecommunication Market by Application
8.6 Italy AI in Telecommunication Market
8.6.1 Italy AI in Telecommunication Market by Technology
8.6.2 Italy AI in Telecommunication Market by Deployment
8.6.3 Italy AI in Telecommunication Market by Component
8.6.4 Italy AI in Telecommunication Market by Application
8.7 Rest of Europe AI in Telecommunication Market
8.7.1 Rest of Europe AI in Telecommunication Market by Technology
8.7.2 Rest of Europe AI in Telecommunication Market by Deployment
8.7.3 Rest of Europe AI in Telecommunication Market by Component
8.7.4 Rest of Europe AI in Telecommunication Market by Application
Chapter 9. Company Profiles
9.1 NVIDIA Corporation
9.1.1 Company Overview
9.1.2 Financial Analysis
9.1.3 Segmental and Regional Analysis
9.1.4 Research & Development Expense
9.1.5 SWOT Analysis
9.2 IBM Corporation
9.2.1 Company Overview
9.2.2 Financial Analysis
9.2.3 Regional & Segmental Analysis
9.2.4 Research & Development Expenses
9.2.5 Recent strategies and developments:
9.2.5.1 Product Launches and Product Expansions:
9.2.6 SWOT Analysis
9.3 Infosys Limited
9.3.1 Company Overview
9.3.2 Financial Analysis
9.3.3 Segmental and Regional Analysis
9.3.4 Research & Development Expense
9.3.5 Recent strategies and developments:
9.3.5.1 Geographical Expansions:
9.3.6 SWOT Analysis
9.4 Intel Corporation
9.4.1 Company Overview
9.4.2 Financial Analysis
9.4.3 Segmental and Regional Analysis
9.4.4 Research & Development Expenses
9.4.5 Recent strategies and developments:
9.4.5.1 Product Launches and Product Expansions:
9.4.5.2 Acquisition and Mergers:
9.4.6 SWOT Analysis
9.5 Microsoft Corporation
9.5.1 Company Overview
9.5.2 Financial Analysis
9.5.3 Segmental and Regional Analysis
9.5.4 Research & Development Expenses
9.5.5 Recent strategies and developments:
9.5.5.1 Partnerships, Collaborations, and Agreements:
9.5.6 SWOT Analysis
9.6 Salesforce.com, Inc.
9.6.1 Company Overview
9.6.2 Financial Analysis
9.6.3 Regional Analysis
9.6.4 Research & Development Expense
9.6.5 SWOT Analysis
9.7 Google LLC (Alphabet, Inc.)
9.7.1 Company Overview
9.7.2 Financial Analysis
9.7.3 Segmental and Regional Analysis
9.7.4 Research & Development Expense
9.7.5 Recent strategies and developments:
9.7.5.1 Partnerships, Collaborations, and Agreements:
9.7.6 SWOT Analysis
9.8 Cisco Systems, Inc.
9.8.1 Company Overview
9.8.2 Financial Analysis
9.8.3 Regional Analysis
9.8.4 Research & Development Expense
9.8.5 Recent strategies and developments:
9.8.5.1 Acquisition and Mergers:
9.8.6 SWOT Analysis
9.9 ZTE Corporation
9.9.1 Company Overview
9.9.2 Financial Analysis
9.9.3 Segmental and Regional Analysis
9.9.4 Research & Development Expenses
9.10. AT&T, Inc.
9.10.1 Company Overview
9.10.2 Financial Analysis
9.10.3 Segmental and Regional Analysis
9.10.4 Research & Development Expense
Companies Mentioned
- NVIDIA Corporation
- AT&T, Inc.
- IBM Corporation
- Infosys Limited
- Intel Corporation
- Microsoft Corporation
- Salesforce.com, Inc.
- ZTE Corporation
- Google LLC (Alphabet, Inc.)
- Cisco Systems, Inc.
Methodology
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