The AI in networks market is anticipated to grow exponentially owing to wide-scale 5G deployments across various industry verticals around the globe. AI algorithms are increasingly being incorporated into networking infrastructures and protocols at diverse points like edge devices, controllers, core networks to enable functions like network automation, anomaly detection, predictive maintenance and customized end user experiences.

Artificial intelligence is finding widespread applications across networking domains for tasks ranging from infrastructure management, traffic optimization, predictive maintenance, security and enhanced customer experiences. Network configurations are becoming highly complex to support the exponential data traffic from diverse network architectures like IoT, edge computing, private networks etc. AI provides the means to automate various network operations and free up resources from routine tasks for strategic decision making. Network analytics powered by AI enhances visibility into network health, user behavior and enables proactive issue resolution. The use of machine learning algorithms for tasks like anomaly detection improves network reliability and security. Personalized virtual assistants, predictive self-service capabilities are enhancing customer care.

The Global AI In Networks Market is estimated to be valued at USD 11.5 Bn in 2024 and is expected to reach USD 24.3 Bn by 2031, growing at a compound annual growth rate (CAGR) of 15.7% from 2024 to 2031.

Key Takeaways
Key players operating in the AI in Networks market are Huawei Technologies Co., Ltd., Cisco Systems, IBM Corporation, Nokia Corporation, ZTE Corporation.

Rapid growth in mobile data usage and transition to 5G networks is a major demand driving factor for AI adoption in core and edge networks. More than 60% of global mobile data traffic is expected to be carried by 5G networks by 2026.

The AI In Networks Market uses of AI like predictive maintenance through computer vision and predictive analytics can help telecom operators reduce downtime and operations expenditure substantially. Over 70% of telecom operators expect AI to reduce network maintenance costs by at least 25% in the next 3 years.

Market Trends
Edge AI and distributed machine learning architectures are emerging as prominent trends to support latency sensitive applications and real-time insights closer to endpoints. This reduces back-haul traffic and bandwidth costs.
Network as a Service models leveraging hyper-convergence, virtualization and containerization are gaining momentum. AI augments the programmability, automation, and flexibility of virtualized and cloud native networks.

Market Opportunities
Integration of AI capabilities into unified communication tools, collaboration platforms can enhance productivity. Real-time translation, automated meeting scheduling are examples.
Adoption of AI for customized experiences through applications of technologies like customized virtual assistants, personalized content and service recommendations presents a sizable monetization opportunity for telecom operators.

Impact of COVID-19 on AI In Networks Market
The global pandemic of COVID-19 has significantly impacted the growth of AI In Networks Market. During the initial stages of lockdowns imposed across various countries, the demand from end use industries reduced drastically as operations were halted. This led to decline in revenue for network operators and service providers in 2020. However, with work from home becoming new normal, the usage of cloud services and reliance on digital connectivity increased manifold. This boosted the investments of telecom players to enhance their network infrastructure using advanced AI and automation solutions to handle increased traffic and provide seamless connectivity.

As the pandemic continued in 2021, the telecom industry realized the importance of AI for dynamic network optimization, troubleshooting, predictive maintenance and enhancing customer experience. Many network operators fast tracked their AI deployment plans and initiatives to make networks more intelligent, autonomous and empowered to handle fluctuating traffic patterns. This has tremendously boosted the adoption of AI platforms, solutions and services for networks during the pandemic. Going forward, AI is expected to play a crucial role for telecom industry in building resilient, automated and self-learning networks that can adapt in real-time as demand patterns change.

The pandemic also highlighted the importance of digital infrastructure and connectivity for economic and social development. Many countries fast tracked plans to expand broadband access and next generation networks to rural and remote areas. This presents new opportunities for AI In Networks Market players to provide solutions for automated network planning, deployment and management of expanded networks. Overall, while COVID-19 initially led to decline, the increased focus on digitalization and need for intelligent networks is expected to drive higher growth in the long run.

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Ravina Pandya, Content Writer, has a strong foothold in the market research industry. She specializes in writing well-researched articles from different industries, including food and beverages, information and technology, healthcare, chemical and materials, etc.

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