AI in Networks Market Size, Share and Trends 2024 to 2034

AI in Networks Market Size and Forecast 2024 to 2034

The global AI in networks market size is calculated at USD 11.53 billion in 2024 and is projected to surpass around USD 192.42 billion by 2034, expanding at a CAGR of 32.51% from 2024 to 2034. Increasing use of innovative technologies like IoT, 5G technology in telecom industry and cloud service adoption across various industries are creating huge amount of data, which need to be managed effectively to extract insights from it, fuelling the AI in networks market on a global level.

AI in Networks Market Key Takeaways

• North America dominated the global AI in networks market and generated more than 41% of market share in 2023.
• Asia Pacific will host the fastest-growing market in the foreseeable period.
• By component, the software segment accounted for the largest market share of 44% in 2023.
• By component, the service segment is anticipated to witness the fastest growth in the market during the forecasted years.
• By deployment, the cloud segment dominated the global market in 2023.
• By deployment, the on-premises segment is anticipated to witness the growth at a significant rate in the market during the forecasted years.
• By technology, the machine learning segment led the global market in 2023.
• By technology, the deep learning segment is anticipated to witness the fastest growth in the market during the forecasted years.
• By application, the network optimization segment held a dominant presence in the market in 2023.
• By application, the network cybersecurity segment is anticipated to witness rapid growth in the market during the forecasted years.
• By end use, in 2023, the telecommunication segment dominated the global market.
• By end use, the IT segment is anticipated to witness the fastest growth in the market during the forecasted years.

U.S. AI in Networks Market Size and Growth 2024 to 2034

The U.S. AI in networks market size is evaluated at USD 3.31 billion in 2024 and is projected to be worth around USD 56.30 billion by 2034, growing at a CAGR of 32.72% from 2024 to 2034.

North America dominated the global AI in networks market in 2023. The growth of this region is due to the rapid adoption of AI infrastructure for network management solutions and a highly established ecosystem for technological infrastructure in well-developed countries like the US. AI technology offers cost-effective solutions for risk detection. Also, the presence of major tech firms is accelerating the demand for the market in North America.

Asia Pacific will host the fastest-growing AI in networks market in the foreseeable period. The growth of this region is due to the notable transformation in the digital sectors of evolving countries like India, China, and Japan, creating a wave for advanced network solutions in various sectors to hold innovative technologies and their applications. Also, the proliferation of internet connections leads to more internet users in Asian countries along with rising mobile device adoption, creating a huge data traffic that needs to be managed by a robust network management solution.

Market Overview

The AI in networks market is expanding due to huge amounts of data generated by IoT devices, cloud computing, and 5G technologies, along with increasing digital services that need to be managed properly. AI technology can be used to optimize the bandwidth, minimize latency, and help increase network performance to handle the increasing traffic. Additionally, companies are seeking automation processes to minimize operational costs, which improves efficiency. 

AI has significantly impacted the network market and is critical in advanced network management solutions. It helps manage complexities that occur due to the large datasets generated by complex technologies like 5g technology. Moreover, organizations can leverage AI for further cost savings by reducing downtime and improving the network bandwidth.

• In June 2024, Huawei Technologies Co., Ltd., an ICT infrastructure and smart devices provider, announced an initiative to integrate AI into networks; this strategy aims to create a RAN Intelligent Agent ecosystem in partnership with network operators to boost network efficiency.

Region-wise, North America dominated the global AI in networks market, while Asia Pacific is considered the fastest-growing region in the market and the biggest contributor as well.

AI in Networks Market Growth Factors

• Increased digital services across the world.
• Exponential data generation due to the integration of IoT devices and 5g technologies.
• Companies are seeking automation, fuelling the growth of AI in networks market on a global level.
• Companies are striving to reduce cyber-attacks.
• Companies are looking for customizable and scalable options.

Market Scope

Market Dynamics

Driver

Increased demand for efficient networks across the various sectors

The major driving factor for AI in networks market is the increased demand for efficient networks across various industries. Key factors like rising demand for network management, enhanced cybersecurity, and increased support for advanced technologies like 5G are the major factors that help to proliferate the market further. Moreover, AI in networks provides automation and intelligent solutions for network performance optimization and reduces the latency of the network, making it more efficient. AI also helps predict potential cyber-attacks, which reduces downtime and improves network security.

Restraint

High cost for implementation

A major restraining factor of the AI in networks market is the high cost of implementation of AI into network management as a solution. Since this technology is newer in the market, it is costly to implement on a large scale, making it difficult for every organization, especially companies with budget constraints. Small and medium-scale organizations find it challenging to gather sufficient amounts and resources for such a huge-scale integration of AI into existing infrastructure.

Opportunity

Adoption of innovative 5G technology

The major opportunity of the AI in networks market is the wide adoption of innovative technologies like 5G technology. 5g technology requires intelligent automation tools to manage the complexity and large-scale operations. It ensures low latency and high-speed connectivity, which is required for large-scale and prompt operations. AI helps optimize the networks dynamically and allocate their resources by predicting traffic routes, which enhances the overall efficiency of the network. It creates a significant opportunity for AI solutions to manage the 5G infrastructure. Hence, telecom providers are seeking to leverage AI solutions in network management.

Component Insights

The service segment is anticipated to witness the fastest growth in the AI in networks market during the forecasted years. The rising adoption of AI technology, the increasing need for real-time data processing, and cloud migration are the major reasons fuelling the segment's growth. AI software solutions are scalable and customizable, allowing companies to customize them to their needs and capabilities.

The software segment accounted for the largest share of the AI in networks market in 2023. The growth of this segment is related to the increasing need for services helpful to grow the business and their objective and requirements for the network. Service providers ensure that AI solutions must offer and optimize the unique needs of the enterprises. Also, enterprises are adopting cloud services and edge computing.

Deployment Insights

The cloud segment dominated the global AI in networks market in 2023. Cloud segments offer scalability to organizations as per their demand and help them adjust resources, resulting in cost-effective solutions. Cloud deployment helps minimize the high initial investment for infrastructure and hardware, which allows companies to manage their operational cost as per their need and time. Cloud service also offers remote access to management tools, which helps teams to cooperate from anywhere in the world.

The on-premises segment is anticipated to witness growth at a significant rate in the AI in networks market during the forecasted years. The growth of this segment is due to various factors like data security, privacy, minimized dependency on the internet, customization, and control. On-premises deployment is helpful in environments where internet connections are limited.

Technology Insights

The machine learning segment led the global AI in networks market in 2023. Machine learning algorithms can analyze huge amounts of data since networks have become much more complex than before due to the integration of IoT, cloud services, and emerging 5G technologies, fuelling the segment's growth further.

The deep learning segment is anticipated to witness the fastest growth in the AI in networks market during the forecasted years. Deep learning can help to improve network capabilities by analyzing huge amounts of data generated by various sources like IoT devices and cloud services, which creates the perfect environment for deep learning algorithms to analyze valuable data and create insights from it.

Application Insights

The network optimization segment held a dominant presence in the AI in networks market in 2023. The growth of this segment is due to various factors like huge data volume, rising demand for real-time activities, automation processes, and network management. Companies can significantly save costs by optimizing network resources and reducing downtime. Improved user experience can be achieved by network optimization.

The network cybersecurity segment is anticipated to witness rapid growth in the AI in networks market during the forecasted years. The segment growth is fuelling due to the increasing incidences of cyber-attacks like ransomware, advanced persistent threats, and phishing, which require robust security measures.

End-use Insights

The telecommunication segment dominated the global AI in networks market. The growth of this segment is due to the AI-based predictive maintenance that telecom operators can use to detect possible network issues before they occur. This reduces downtime and increases customer satisfaction.

The IT segment is anticipated to witness the fastest growth in the AI in networks market during the forecasted years. The growth of this segment is attributed to various factors, including the complexity of the IT infrastructure and the increasing need for real-time data processing. By using AI, routine tasks can be automated further.

AI in Networks Market Companies

• Arista Networks, Inc.
• Broadcom
• Cisco Systems, Inc.
• Extreme Networks
• Huawei Technologies Co., Ltd.
• IBM Corporation
• Juniper Networks, Inc.
• Nokia
• Telefonaktiebolaget LM Ericsson
• ZTE Corporation

Recent Developments

• In September 2024, Telefonaktiebolaget LM Ericsson collaborated with T‑Mobile USA, Inc., a wireless network operator, and NVIDIA Corporation, a developer of graphics processing units (GPUs), to create a joint AI-RAN Innovation Center. The AI-RAN Innovation Center is set to propel the standardization and widespread acceptance of AI-RAN technologies across the industry. 
• In September 2024, Nokia launched the Event-Driven Automation (EDA) platform, marking a significant advancement in AI. This innovative platform, leveraging Kubernetes, transforms data center network operations by offering a highly dependable, simplified, and flexible solution for managing the lifecycle of data center networks.
• In June 2024, Cisco Systems Inc. collaborated with NVIDIA Corporation, a developer of graphics processing units (GPUs), and launched Nexus HyperFabric AI Clusters, a simplified Data Center Infrastructure Solution tailored for Generative AI. The solution merges Cisco Systems Inc.'s and NVIDIA Corporation's technological advancements to streamline the implementation of generative AI applications. It ensures comprehensive IT visibility and analytics throughout the entire AI infrastructure stack.

Segments Covered in the Report

By Component

• Hardware
• Software
• Services

By Deployment

• Cloud
• On-premises

By Technology

• Machine Learning
• Natural Language Processing
• Computer Vision
• Deep Learning
• Others

By Application

• Network Optimization
• Network Cybersecurity
• Network Predictive Maintenance
• Network Troubleshooting
• Others

By End-use

• Telecommunications
• IT
• Datacenter
• Healthcare
• Government
• Energy & Utilities
• Others

By Geography

• North America
• Asia Pacific
• Europe
• Latin America
• Middle East and Africa