This Artificial Intelligence in Telecom Market report covers the size, share, trends, forecast, status of import and export, supply chain management, distribution channels, price, profit, sale and others vital elements.
New York, NY -- (SBWIRE) -- 07/11/2019 -- Incorporated with Info-graphics, charts, 35 tables and 55 figures, this 117-page research report "Artificial Intelligence in Telecom Market Size, Type Analysis, Application Analysis, End-Use Industry Analysis, Regional Outlook, Competitive Strategies And Forecasts, 2018 - 2023" is based on a complete research of the entire Global market and covering all its sub-segments through comprehensively thorough classifications. Insightful analysis and assessment are created from superior primary and secondary information sources with data and information derived from industry specialists across the value chain. The report provides historical market data for 2014-2018, base year estimates for 2018, and forecasts from 2018 to 2023.
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Global Artificial Intelligence in Telecom Market:
Growing complexities in the communication networks today calls for an intelligent approach to network planning and optimization. With the rise of Artificial Intelligence (AI) techniques, new technology paradigms such as network virtualization, self-organizing networks (SONs), intelligent antennas, AI-powered radio-frequency (RF) front end and intelligent chipsets can be easily embedded into the communication networks.
Telecom companies are therefore leveraging AI solutions to achieve hyper-automation of telecom networks and usher in an era of self-healing and self-configuring networks. Inclusion of network intelligence allows mobile network operators (MNOs) to achieve efficient network management and cross spectrum protection.
This report includes a comprehensive analysis of the adoption of AI in telecom, highlighting the major technology trends and opportunities available across the ecosystem.
The major players covered in this report are:
AT&T, Verizon, Nokia, Huawei, Ciena, Rakuten, and Orange, Cellwize, Altiostar, CujoAI, Kumu Networks, GenXcomm, Cambricon, Pivotal Commware, Metawave, Senseon, Parallel Wireless, Galgus, and Affirmed Networks
An assessment of the acquisition trends since 2014 provides insights about the technology drivers in the AI-driven telecom market. The key technologies include cloud-native solutions, security, virtualized RAN, SON, and network analytics.
Distribution of these deals over the years provides an overview of the roadmap that the acquirers are following and highlights the unique value proposition behind the mergers and acquisitions.
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Geographically, this report studies the key regions, focuses on product sales, value, market share and growth opportunity in these regions, covering:
- United States
- Southeast Asia
We can also provide the customized separate regional or country-level reports, for the following regions:
North America, United States, Canada, Mexico, Asia-Pacific, China, India, Japan, South Korea, Australia, Indonesia, Singapore, Rest of Asia-Pacific, Europe, Germany, France, UK, Italy, Spain, Russia, Rest of Europe, Central & South America, Brazil, Argentina, Rest of South America, Middle East & Africa, Saudi Arabia, Turkey, Rest of Middle East & Africa
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Key questions addressed in the report:
- How innovative AI solutions are making an impact in the telecom value chain?
- What are the challenges and issues addressed by the implementation of AI algorithms in the telecom industry?
- What are the emerging use cases and business models that are driving the adoption of AI?
- Who are the key enablers for AI technology in the industry?
- Who are the frontrunners, and what are their implementations strategies?
- What is the current industry adoption status of AI in telecom?
- Which are the disruptive entities that can be potential targets for driving AI in telecom?
- Since 2014, what are the acquisition trends for AI in telecom?
- What are opportunities for the telecom companies to build a strong roadmap for the future of autonomous networks?
- How can companies from other sectors tap into the AI in telecom market?
- Network intelligence-related solutions are becoming the new norm for deriving insights from massive network data.
- The growing need for hyper-automation in communication networks is setting the stage for SON technologies that will help drive autonomous networks of the future.
- Virtualization of networks is fueling the need for cloud-native solutions, ranging from the ones that provide security, to the one's constituting the network core.
- The telecom solution providers, including names like Ericsson, Nokia, and Cisco, led the charts with the highest number of AI-based acquisitions.
- Emerging companies took a lead role in solving the problem of RF spectrum interference.
o Understand the demand for global Artificial Intelligence in Telecom to determine the viability of the market.
o Identify the developed and emerging markets where Artificial Intelligence in Telecom services are offered.
o Identify the challenge areas and address them.
o Develop strategies based on the drivers, trends and highlights for each of the segments.
o Evaluate the value chain to determine the workflow and to get an idea of the current position where you are placed.
o Recognize the key competitors of this market and respond accordingly.
o Knowledge of the initiatives and growth strategies taken up by the major companies and decide on the direction for further growth.
o Define the competitive positioning by comparing the products and services with the key players in the market.
Key elements from table of content:
6.2. Startups Focusing on:
6.2.2. Cloud Native Networks
6.2.3. Network Security and Analytics
6.2.4. Interference Cancellation
6.2.5. AI Hardware
6.2.6. Conversational AI
7. Insights & Recommendations
7.1. Current Adoption Status of AI in Telecom
7.2. Recommendations for Telecom Companies
7.3. Recommendations for Other Industry Players
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