AI In Telecommunication Market Size, Share & Trends Analysis Report By Application (Network Security, Network Optimization, Customer Analytics, Virtual Assistance, Self-Diagnostics), By Region, And Segment Forecasts, 2023 - 2030

AI In Telecommunication Market Size, Share & Trends Analysis Report By Application (Network Security, Network Optimization, Customer Analytics, Virtual Assistance, Self-Diagnostics), By Region, And Segment Forecasts, 2023 - 2030


AI In Telecommunication Market Growth & Trends

The global AI in telecommunication market size is expected to reach USD 11.29 billion by 2030, according to a new report by Grand View Research, Inc. The market is anticipated to register a CAGR of 28.2% from 2023 to 2030.

Communication Service Providers (CSPs) need to bring the intelligence in their system optimization, planning, and operations to address the increasing complexities in communication networks caused due to the deployment of new technology paradigms, such as Network Function Virtualization (NFV) and Software-Defined Wide-Area Networking (SD-WAN). Therefore, the telecommunications industry is exploring and introducing AI to improve network efficiency and customer experience.

The telecommunication industry has leveraged technologies, such as cloud computing, big data analytics, and deep learning, to fulfill consumer demands of multimedia services and network security. Also, the intellectualization of communication networks has become possible with the invention of technologies of service-aware network systems and deep packet inspection. Researchers in the industry are tapping into artificial intelligence-based techniques to optimize network architecture & management, and to enable more autonomous operations.

Furthermore, the next-generation wireless networks are anticipated to evolve into more complex system architectures due to the diversified service requirements and heterogeneity in devices, system architectures, and applications. Artificial intelligence has renewed interest in the telecom industry due to the rising complexity of network technology. Potential AI-based use-cases in communication networks include network operation monitoring & management, fraud mitigation, predictive maintenance, cybersecurity, and virtual assistants for marketing and customer service. However, network operation monitoring & management remains the top use-case in the telecom industry as several communications service providers have adopted AI approaches to address the need for communication automation and agility.

AI In Telecommunication Market Report Highlights
  • Improving customer experience is one of the major factors driving the growth of the market since chatbots deployed for customer service have fueled the business earnings adequately
  • Machine learning approaches are beginning to emerge in the telecommunication domain to address the challenges of virtualization
  • AI-supported network-centric applications include anomaly detection for maintenance and provisioning, performance monitoring, alert suppression, automated resolution of a trouble ticket, network faults prediction, and network capacity planning or congestion prediction
  • Asia Pacific is expected to grow at the fastest CAGR of 32.9% during the forecast period. This growth is attributed to the rapid technological advancements in emerging economies, such as China and India.
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Chapter 1. Methodology and Scope
1.1. Market Segmentation & Scope
1.1.1. Application
1.1.2. Regional scope
1.1.3. Estimates and forecast timeline
1.2. Research Methodology
1.3. Information Procurement
1.3.1. Purchased database
1.3.2. GVR’s internal database
1.3.3. Secondary sources
1.3.4. Primary research
1.3.5. Details of primary research
1.4. Information or Data Analysis
1.5. Market Formulation & Validation
1.6. Model Details
1.7. List of Secondary Sources
1.8. List of Primary Sources
1.9. Objectives
Chapter 2. Executive Summary
2.1. Market Outlook
2.2. Segment Outlook
2.2.1. Application outlook
2.2.2. Regional outlook
2.3. Competitive Insights
Chapter 3. Artificial Intelligence in Telecommunication Market Variables, Trends & Scope
3.1. Market Lineage Outlook
3.2. Industry Value Chain Analysis
3.3. Market Dynamics
3.3.1. Market driver analysis
3.3.2. Market restraint analysis
3.3.3. Market opportunity analysis
3.4. Artificial Intelligence in Telecommunication Market Analysis Tools
3.4.1. Industry analysis - Porter’s
3.4.1.1. Supplier power
3.4.1.2. Buyer power
3.4.1.3. Substitution threat
3.4.1.4. Threat of new entrant
3.4.1.5. Competitive rivalry
3.4.2. PESTEL analysis
3.4.2.1. Political landscape
3.4.2.2. Technological landscape
3.4.2.3. Economic landscape
Chapter 4. Artificial Intelligence in Telecommunication Market: Application Estimates & Trend Analysis
4.1. Artificial Intelligence in Telecommunication Market: Key Takeaways
4.2. Artificial Intelligence in Telecommunication Market: Movement & Market Share Analysis, 2022 & 2030
4.3. Network Security
4.3.1. Network security market estimates and forecasts, 2017 to 2030 (USD Million)
4.4. Network optimization
4.4.1. Network optimization market estimates and forecasts, 2017 to 2030 (USD Million)
4.5. Customer Analytics
4.5.1. Customer analytics market estimates and forecasts, 2017 to 2030 (USD Million)
4.6. Virtual Assistance
4.6.1. Virtual assistance therapy market estimates and forecasts, 2017 to 2030 (USD Million)
4.7. Self-Diagnostics
4.7.1. Self-Diagnostics market estimates and forecasts, 2017 to 2030 (USD Million)
4.8. Others
4.8.1. Others market estimates and forecasts, 2017 to 2030 (USD Million)
Chapter 5. Artificial Intelligence in Telecommunication Market: Regional Estimates & Trend Analysis
5.1. Regional Outlook
5.2. Artificial Intelligence in Telecommunication Market by Region: Key Takeaway
5.3. North America
5.3.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.3.2. U.S.
5.3.2.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.3.3. Canada
5.3.3.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.4. Europe
5.4.1. UK
5.4.1.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.4.2. Germany
5.4.2.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.4.3. France
5.4.3.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.5. Asia Pacific
5.5.1. Japan
5.5.1.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.5.2. China
5.5.2.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.5.3. India
5.5.3.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.5.4. Australia
5.5.4.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.5.5. South Korea
5.5.5.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.6. Latin America
5.6.1. Brazil
5.6.1.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.6.2. Mexico
5.6.2.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.7. MEA
5.7.1. Saudi Arabia
5.7.1.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.7.2. South Africa
5.7.2.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
5.7.3. UAE
5.7.3.1. Market estimates and forecasts, 2017 to 2030 (Revenue, USD Million)
Chapter 6. Competitive Landscape
6.1. Recent Developments & Impact Analysis, By Key Market Participants
6.2. Market Participant Categorization
6.2.1. IBM Corporation
6.2.1.1. Company overview
6.2.1.2. Financial performance
6.2.1.3. Product benchmarking
6.2.1.4. Strategic initiatives
6.2.2. Microsoft
6.2.2.1. Company overview
6.2.2.2. Financial performance
6.2.2.3. Product benchmarking
6.2.2.4. Strategic initiatives
6.2.3. Intel Corporation
6.2.3.1. Company overview
6.2.3.2. Financial performance
6.2.3.3. Product benchmarking
6.2.3.4. Strategic initiatives
6.2.4. Google LLC
6.2.4.1. Company overview
6.2.4.2. Financial performance
6.2.4.3. Product benchmarking
6.2.4.4. Strategic initiatives
6.2.5. AT&T Intellectual Property
6.2.5.1. Company overview
6.2.5.2. Financial performance
6.2.5.3. Product benchmarking
6.2.5.4. Strategic initiatives
6.2.6. Cisco Systems, Inc.
6.2.6.1. Company overview
6.2.6.2. Financial performance
6.2.6.3. Product benchmarking
6.2.6.4. Strategic initiatives
6.2.7. Nuance Communications, Inc.
6.2.7.1. Company overview
6.2.7.2. Financial performance
6.2.7.3. Product benchmarking
6.2.7.4. Strategic initiatives
6.2.8. Evolv Technologies Holdings Inc.
6.2.8.1. Company overview
6.2.8.2. Financial performance
6.2.8.3. Product benchmarking
6.2.8.4. Strategic initiatives
6.2.9. H2O.ai.
6.2.9.1. Company overview
6.2.9.2. Financial performance
6.2.9.3. Product benchmarking
6.2.9.4. Strategic initiatives
6.2.10. Infosys Limited
6.2.10.1. Company overview
6.2.10.2. Financial performance
6.2.10.3. Product benchmarking
6.2.10.4. Strategic initiatives
6.2.11. Salesforce, Inc.
6.2.11.1. Company overview
6.2.11.2. Financial performance
6.2.11.3. Product benchmarking
6.2.11.4. Strategic initiatives
6.2.12. NVIDIA Corporation
6.2.12.1. Company overview
6.2.12.2. Financial performance
6.2.12.3. Product benchmarking
6.2.12.4. Strategic initiatives

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