AI in Networks Market Size, Share, and Industry Analysis, By Deployment (On-Premises and Cloud-Based), By Technology (Machine Learning, Generative AI, Deep Learning, Natural Language Processing, and Others), By End-Use Industry (BFSI, Telecommunications, Healthcare, Government & Defense, Media & Entertainment, Retail & E-Commerce, Data Centers, and Others), and Regional Forecast, 2025-2032

The global AI in networks market is growing significantly due to the rising complexity of contemporary networks and the need for improved performance and security. AI in network technologies is transforming network management by leveraging machine learning and advanced analytics to enhance performance, security, and efficiency. These technologies are incorporated into network systems in place of traditional rule-based algorithms, allowing for real-time data analysis, predictive maintenance, and dynamic resource allocation. Some important factors are the fast integration of 5G, IoT, and cloud computing, which necessitate smart network management solutions.

Impact of Generative AI on the AI in Networks Market

Generative AI is transforming the AI industry in networking through improvements in data generation, network optimization, and security. It allows for the generation of artificial data to enhance the precision and dependability of AI models during training. Moreover, generative AI streamlines the process of designing and configuring networks, resulting in networks that are more effective and durable. Additionally, it enhances network security by utilizing cutting-edge threat detection and anomaly recognition, leading to increased innovation and effectiveness in contemporary network supervision. For instance,

• In 2023, PwC US announced that it would invest USD 1.00 billion in the next three years to improve its AI capabilities, specifically in generative AI, in collaboration with Microsoft. This investment initiative focuses on enhancing PwC's AI services by utilizing the capabilities of OpenAI’s GPT-4 and Microsoft’s Azure OpenAI Service to enhance client solutions and increase efficiency. 

AI in Networks Market Driver

Emergence of 5G Technology is the Key Driver for AI in Networks Market

The emergence of 5G technology greatly influences AI in the network market by enhancing network capabilities. The speed of data is much higher on 5G networks, with minimal delay and the capability to connect numerous devices at once. The growing usage of 5G is motivated by its potential to transform different sectors and enhance connectivity in general. For instance,

• According to 5G Americas and Omdia, Global 5G connections reached nearly 2 billion in the first quarter of 2024, with 185 million new additions.

AI in Networks Market Restraint

Regulatory and Compliance Issues Hinder Market Growth

Regulatory and compliance issues present significant challenges in the AI in networks market. Various regions have distinct rules governing data usage, privacy, and AI deployment, making it challenging for companies to comply. These regulations often necessitate robust compliance frameworks, which can be resource-intensive and time-consuming to implement. For instance,

• The EU AI Act, implemented on August 1, 2024, is a crucial rule for the AI industry in the European Union. It sets out detailed regulations for AI systems, covering both high-risk and general-purpose models, affecting how they are developed and implemented in network applications. 

AI in Network Market Opportunity

Increasing Awareness of Smart Cities Creates an Opportunity for AI in Networks Market

Smart cities create a need for advanced, interconnected systems that improve urban living, offering major opportunities for AI in the network market. Cities need advanced network management solutions to handle large amounts of real-time data as they incorporate technologies, such as IoT devices, sensors, and smart infrastructure. Additionally, government backing of smart city projects often involves financial support for technology integration, fostering the necessity for predictive maintenance and proactive network management. For instance,

• In 2024, China announced new guidelines to enhance the development of smart cities and promote urban digital transformation. The country's goal is to make substantial advancements in developing livable, resilient, and smart urban areas by 2027. The National Data Bureau and other government departments have issued guidelines that highlight the importance of incorporating digital technologies in different facets of urban management, such as planning, construction, and service delivery.

Segmentation

Key Insights

The report covers the following key insights:

• Micro Macro Economic Indicators
• Drivers, Restraints, Trends, and Opportunities
• Business Strategies Adopted by the Key Players
• Impact of Generative AI on the Global AI in Networks Market
• Consolidated SWOT Analysis of Key Players

Analysis by Deployment

By deployment, the market is divided into on-premises and cloud-based.

Cloud-based deployment is more popular than on-premises deployment in the AI in networks market. Cloud-based solutions provide increased scalability, enabling organizations to adjust resources based on demand without requiring a large initial investment. Additionally, they offer increased flexibility and accessibility, allowing for remote management and real-time updates. The recent partnership among large enterprises supports this trend. For instance,

• In 2024, IBM and Intel partnered to introduce Intel Gaudi 3 AI accelerators on IBM Cloud by early 2025, improving AI scalability and cost-effectiveness. This partnership will assist with mixed and in-house setups, connecting with IBM's Watsonx AI platform to enhance efficiency and protection for business AI tasks.

Analysis by Technology

By technology, the market is divided into machine learning, generative AI, deep learning, natural language processing, and others.

Machine Learning (ML) typically holds the upper hand. ML algorithms are good at analyzing large amounts of network data to find patterns, predict problems, and improve network performance. ML's capability to enhance performance through learning from past data is extremely useful for functions, such as traffic control, spotting irregularities, and forecasting maintenance needs. Furthermore, ML is flexible and can be incorporated into different network operations, improving overall effectiveness and dependability.

Analysis by End-Use Industry

By end-use industry, the market is divided into BFSI, telecommunications, healthcare, government & defense, media & entertainment, retail & e-commerce, data centers, and others.

The telecommunications industry is a leading sector within the AI in networks market. This industry uses artificial intelligence to improve network efficiency, elevate customer support, and handle the growing intricacy of contemporary communication networks. Artificial intelligence technology in telecom aids in foreseeing maintenance needs, enhancing network performance, and providing automated customer service, highlighting its significance in AI implementation. For instance,

• In 2024, Ericsson, in collaboration with T-Mobile and NVIDIA, set up the AI-RAN Innovation Center in Bellevue, Washington. This partnership seeks to improve the merging of AI with radio access networks (RAN) to boost network performance, reliability, and efficiency.

Regional Analysis

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In terms of geography, the global market is segmented into North America, Europe, Asia Pacific, South America, and the Middle East & Africa.

North America holds the largest AI in networks market share due to its advanced technological infrastructure and widespread use in sectors, such as healthcare, automotive, finance, retail, and manufacturing. The area receives substantial investments in AI research and development, backed by private companies and government efforts. For instance,

• In 2024, President Joe Biden's support for Microsoft's USD 3.30 billion AI data center in Racine, Wisconsin, shows the increasing significance of AI-based infrastructure. These data centers will not just increase job opportunities and local upskilling but will also be crucial in advancing AI-enhanced network management.

Europe holds the second-largest market share. The region's strong technological foundation and abundant skilled workforce support the advancement of AI innovation. The region places a high priority on ethical AI, standardization, and interoperability to guarantee the safety, efficacy, and widespread acceptance of AI technologies. For instance,

• In 2024, The Trustworthy & Responsible AI Network (TRAIN), supported by Microsoft, has been introduced in Europe. TRAIN, which includes key European hospitals such as Erasmus MC and Sahlgrenska University Hospital in Sweden, is working toward creating resources and safeguards for reliable AI in the healthcare field.

Asia Pacific holds a considerable portion of the AI in networks market. Countries, such as China, India, and Japan have witnessed significant investments in AI research and development, leading to rapid technological progress in the region. Companies are making significant investments in artificial intelligence to improve their network infrastructure. For instance,

• In 2024, Lenovo is set to start producing AI servers at its facility in Puducherry, India, making 50,000 AI rack servers and 2,400 GPU servers each year for domestic and international markets. Furthermore, Lenovo has established an AI-dedicated research and development lab in Bengaluru. 

Key Players Covered

The global AI in networks market is fragmented, with a large number of groups and standalone providers. In the U.S., the top 5 players account for only around 23% of the market.

The report includes the profiles of the following key players:

• Aristo Networks, Inc. (U.S.)
• Cisco Systems Inc. (U.S.)
• Dell Technologies (U.S.)
• Extreme Networks (U.S.)
• Hewlett Packard Enterprise Development LP (U.S.)
• Intel (U.S.)
• NVIDIA Corporation (U.S.)
• Supermicro (U.S.)
• Telefonaktiebolaget LM Ericsson (Sweden)

Key Industry Developments

• In 2024, Cisco invested USD 1.00 billion to aid in the creation of secure and dependable AI solutions. Cisco's move highlights its plan to incorporate AI for developing, linking, and safeguarding networks, establishing itself as a crucial facilitator in the era of AI-driven networking.
• In 2024, The AI-RAN Alliance, unveiled at the GSMA Mobile World Congress, aims to incorporate AI into Radio Access Network (RAN) technology to revolutionize mobile networks. Utilizing AI, the coalition—comprised of big names, such as AWS, Microsoft, Ericsson, and Nokia—is striving to boost network efficiency, enhance spectral utilization, lower power usage, and optimize current infrastructure.