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Jul 5, 2019 6:15 AM ET

Artificial Intelligence in Telecoms, 2019: AI Insight Series

Artificial Intelligence in Telecoms, 2019: AI Insight Series

iCrowd Newswire - Jul 5, 2019

Dublin,  — The “Artificial Intelligence Insight Series – Artificial Intelligence in Telecom” report has been added to ResearchAndMarkets.com’s offering.

This report includes a comprehensive analysis of the adoption of AI in telecom, highlighting the major technology trends and opportunities available across the ecosystem.

Key Insights

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.

Competitive Analysis

This section includes a study of key telecom companies and other emerging entities in the AI in telecom space. We assess the major telecom entities based on their partnerships, implementation strategies, and recent AI solutions and services. The analysis also highlights the transformation of current telecom business models with the integration of AI/ML techniques for driving new revenue streams and maximizing benefits. Some of the key entities included in the report are AT&T, Verizon, Nokia, Huawei, Ciena, Rakuten, and Orange.

Further, the report includes approximately 40 startups that are concentrating on various technological aspects like SON, cloud-native, network analytics, AI hardware, and interference cancellation. Most of these emerging players are solving these telecom industry challenges by leveraging innovative AI solutions and services. We have analyzed them closely to get a clear picture of their product and technology offerings, partnerships, customers, funding details, and future outlook. Some of the startups reported include Cellwize, Altiostar, CujoAI, Kumu Networks, GenXcomm, Cambricon, Pivotal Commware, Metawave, Senseon, Parallel Wireless, Galgus, and Affirmed Networks. 

M&A Analysis

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. 

The prominent participants in the space include telecom solution providers, MNOs, startups and investors. Some of the major acquirers include Nokia, Ericsson, Cisco and Zephyrtel.

Key Questions Addressed

Companies Mentioned 

Key Topics Covered

1. Impact of AI in the Telecom Ecosystem
1.1. Overview of the Telecom Value Chain Participants
1.2. Role of AI in the Telecom Ecosystem

2. Use Cases of AI in the Telecom Industry
2.1. Use Case 1: AI in Network Optimization
2.2. Use Case 2: AI for 5G Networks
2.3. Use Case 3: AI in Cloud
2.4. Use Case 4: AI Security 
2.5. Use Case 5: Other AI Implementations

3. How is AI Transforming Telecom Business Models?
3.1. Business Model 1: AI Managed Services
3.2. Business Model 2: AI Powered Chipsets
3.3. Business Model 3: Data Monetization 
3.4. Business Model 4: Open Source Platforms
3.5. Business Model 5: AI-Enabled Cloud Services

4. Overview of the AI Adoption by Key Telecom Companies
4.1. Adoption Status of Telecom Companies

5. How is AI Driving M&A Activity in Telecom Sector?
5.1. Technology Drivers of the Deals
5.2. Technology Distribution
5.3. Overview of the Acquired Technologies
5.4. Prominent Acquirers in the Space
5.5. Post-deal Integration Examples 

6. How are Startups Innovating in the AI Telecom Space?
6.1. Key Challenges Targeted by Startups
6.2. Startups Focusing on:
6.2.1. SON
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

For more information about this report visit https://www.researchandmarkets.com/r/9l9ot4

Research and Markets also offers Custom Research services providing focused, comprehensive and tailored research.

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Related Topics: Artificial Intelligence

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