The global AI in telecommunication market size is expected to reach USD 11.29 billion by 2030, according to the report. 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.
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.
Table of Contents
Chapter 1. Methodology and Scope
Chapter 2. Executive Summary
Chapter 3. Artificial Intelligence in Telecommunication Market Variables, Trends & Scope
Chapter 4. Artificial Intelligence in Telecommunication Market: Application Estimates & Trend Analysis
Chapter 5. Artificial Intelligence in Telecommunication Market: Regional Estimates & Trend Analysis
Chapter 6. Competitive Landscape
List of Tables
List of Figures
Companies Profiled
- IBM Corporation
- Microsoft
- Intel Corporation
- Google LLC
- AT&T Intellectual Property
- Cisco Systems, Inc.
- Nuance Communications, Inc.
- Evolv Technologies Holdings Inc.
- H2O.ai.
- Infosys Limited
- Salesforce, Inc.
- NVIDIA Corporation
Methodology
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Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 100 |
| Published | November 2023 |
| Forecast Period | 2022 - 2030 |
| Estimated Market Value ( USD | $ 1.45 Billion |
| Forecasted Market Value ( USD | $ 11.29 Billion |
| Compound Annual Growth Rate | 28.2% |
| Regions Covered | Global |
| No. of Companies Mentioned | 12 |
