세계의 네트워크용 인공지능 시장 : 컴퍼넌트, 테크놀로지, 전개 모드, 산업별 예측(2025-2030년)

The Artificial Intelligence in Networks Market was valued at USD 8.83 billion in 2023, expected to reach USD 11.07 billion in 2024, and is projected to grow at a CAGR of 26.14%, to USD 44.88 billion by 2030.

The scope of Artificial Intelligence (AI) in networks encompasses its integration in enhancing network efficiency, security, and management. AI's definition in this context refers to implementing machine learning, deep learning, and analytics to optimize network performance, predict and mitigate network failures, and automate maintenance tasks. The necessity of AI in networks arises from the exponential increase in data traffic and the need for robust, adaptive networks that can efficiently handle this load while ensuring high security. AI's applications in this field are vast, including network optimization, predictive maintenance, traffic management, and enhanced security protocols. In terms of end-use, telecommunications, data centers, and IT infrastructure businesses are primary adopters, striving to enhance bandwidth management, reduce latency, and improve user experience. Market insights highlight the surging demand for AI-driven network solutions due to increased IoT adoption, 5G deployments, and cloud-based services. Critical growth factors include the enhancement of network infrastructures, technological advancement, and rising investments in AI research.

A significant market opportunity lies in the tailored AI solutions for specific network challenges, such as reducing downtime and managing data efficiently across distributed networks. Recommendations to seize these opportunities include investing in R&D for customized AI solutions, focusing on strategic partnerships with technology providers, and enhancing AI training data quality. Limitations include the high initial investment cost, interoperability issues, and the need for skilled professionals. Moreover, concerns about data privacy and security pose significant challenges. Innovation should focus on developing AI systems that offer seamless integration, robust data security measures, and the capability to handle dynamic network demands. Research should delve into improving AI's predictive analytics and anomaly detection in real-time network operations. The market for AI in networks is dynamic, rapidly evolving, and holds transformative potential for reshaping network infrastructures across various domains. Businesses should focus on agile, forward-thinking strategies to capitalize on these emerging trends.

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving Artificial Intelligence in Networks Market

The Artificial Intelligence in Networks Market is undergoing transformative changes driven by a dynamic interplay of supply and demand factors. Understanding these evolving market dynamics prepares business organizations to make informed investment decisions, refine strategic decisions, and seize new opportunities. By gaining a comprehensive view of these trends, business organizations can mitigate various risks across political, geographic, technical, social, and economic domains while also gaining a clearer understanding of consumer behavior and its impact on manufacturing costs and purchasing trends.

• Market Drivers
  • Rapid expansion of network infrastructure, including 5G deployment and iot devices integration
  • Rising adoption of autonomous networks for dynamic resource allocation
  • Exponential surge in volume of network traffic
• Market Restraints
  • High Implementation costs and technological complexity
• Market Opportunities
  • Development and expansion of 5G networking infrastructure
  • Increasing innovations in AI-driven network security
• Market Challenges
  • Concerns associated with privacy breaches and data security

Porter's Five Forces: A Strategic Tool for Navigating the Artificial Intelligence in Networks Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the Artificial Intelligence in Networks Market. It offers business organizations with a clear methodology for evaluating their competitive positioning and exploring strategic opportunities. This framework helps businesses assess the power dynamics within the market and determine the profitability of new ventures. With these insights, business organizations can leverage their strengths, address weaknesses, and avoid potential challenges, ensuring a more resilient market positioning.

PESTLE Analysis: Navigating External Influences in the Artificial Intelligence in Networks Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the Artificial Intelligence in Networks Market. Political, Economic, Social, Technological, Legal, and Environmental factors analysis provides the necessary information to navigate these influences. By examining PESTLE factors, businesses can better understand potential risks and opportunities. This analysis enables business organizations to anticipate changes in regulations, consumer preferences, and economic trends, ensuring they are prepared to make proactive, forward-thinking decisions.

Market Share Analysis: Understanding the Competitive Landscape in the Artificial Intelligence in Networks Market

A detailed market share analysis in the Artificial Intelligence in Networks Market provides a comprehensive assessment of vendors' performance. Companies can identify their competitive positioning by comparing key metrics, including revenue, customer base, and growth rates. This analysis highlights market concentration, fragmentation, and trends in consolidation, offering vendors the insights required to make strategic decisions that enhance their position in an increasingly competitive landscape.

FPNV Positioning Matrix: Evaluating Vendors' Performance in the Artificial Intelligence in Networks Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the Artificial Intelligence in Networks Market. This matrix enables business organizations to make well-informed decisions that align with their goals by assessing vendors based on their business strategy and product satisfaction. The four quadrants provide a clear and precise segmentation of vendors, helping users identify the right partners and solutions that best fit their strategic objectives.

Strategy Analysis & Recommendation: Charting a Path to Success in the Artificial Intelligence in Networks Market

A strategic analysis of the Artificial Intelligence in Networks Market is essential for businesses looking to strengthen their global market presence. By reviewing key resources, capabilities, and performance indicators, business organizations can identify growth opportunities and work toward improvement. This approach helps businesses navigate challenges in the competitive landscape and ensures they are well-positioned to capitalize on newer opportunities and drive long-term success.

Key Company Profiles

The report delves into recent significant developments in the Artificial Intelligence in Networks Market, highlighting leading vendors and their innovative profiles. These include Alibaba Group Holding Limited, Amazon Web Services, Inc., Arista Networks, Inc., Atos SE, Baidu, Inc., Check Point Software Technologies Ltd., Ciena Corporation, Cisco Systems, Inc., Dell Technologies Inc., Ericsson AB, F5 Networks, Inc., Fortinet, Inc., Fujitsu Limited, Google LLC, Hewlett Packard Enterprise Company, Huawei Technologies Co., Ltd., Intel Corporation, International Business Machines Corporation, Juniper Networks, Inc., Microsoft Corporation, NetApp, Inc., Nokia Corporation, Nvidia Corporation, Palo Alto Networks, Inc., Qualcomm Incorporated, Salesforce.com, Inc., SAP SE, Telefonaktiebolaget LM Ericsson, Tencent Holdings Limited, and VMware, Inc..

Market Segmentation & Coverage

This research report categorizes the Artificial Intelligence in Networks Market to forecast the revenues and analyze trends in each of the following sub-markets:

• Based on Component, market is studied across Services and Solutions. The Services is further studied across Managed Services and Professional Services. The Professional Services is further studied across Consulting, System Integration & Implementation, and Training & Support. The Solutions is further studied across Hardware and Software. The Hardware is further studied across AI Accelerators and GPUs. The Software is further studied across AI Frameworks & Software Libraries and AI Platforms.
• Based on Technology, market is studied across Automated Planning & Scheduling, Computer Vision, Deep Learning, Expert Systems, Machine Learning, and Natural Language Processing. The Machine Learning is further studied across Reinforcement Learning, Supervised Learning, and Unsupervised Learning.
• Based on Deployment Mode, market is studied across On-Cloud and On-Premises.
• Based on Industry, market is studied across Banking, Financial Services, & Insurance, Energy & Utilities, Government & Defense, Healthcare, Information Technology, Manufacturing, Media & Entertainment, Retail & E-commerce, Telecommunications, and Transportation & Logistics.
• Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

The report offers a comprehensive analysis of the market, covering key focus areas:

1. Market Penetration: A detailed review of the current market environment, including extensive data from top industry players, evaluating their market reach and overall influence.

2. Market Development: Identifies growth opportunities in emerging markets and assesses expansion potential in established sectors, providing a strategic roadmap for future growth.

3. Market Diversification: Analyzes recent product launches, untapped geographic regions, major industry advancements, and strategic investments reshaping the market.

4. Competitive Assessment & Intelligence: Provides a thorough analysis of the competitive landscape, examining market share, business strategies, product portfolios, certifications, regulatory approvals, patent trends, and technological advancements of key players.

5. Product Development & Innovation: Highlights cutting-edge technologies, R&D activities, and product innovations expected to drive future market growth.

The report also answers critical questions to aid stakeholders in making informed decisions:

1. What is the current market size, and what is the forecasted growth?

2. Which products, segments, and regions offer the best investment opportunities?

3. What are the key technology trends and regulatory influences shaping the market?

4. How do leading vendors rank in terms of market share and competitive positioning?

5. What revenue sources and strategic opportunities drive vendors' market entry or exit strategies?

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Segmentation & Coverage
• 1.3. Years Considered for the Study
• 1.4. Currency & Pricing
• 1.5. Language
• 1.6. Stakeholders

2. Research Methodology

• 2.1. Define: Research Objective
• 2.2. Determine: Research Design
• 2.3. Prepare: Research Instrument
• 2.4. Collect: Data Source
• 2.5. Analyze: Data Interpretation
• 2.6. Formulate: Data Verification
• 2.7. Publish: Research Report
• 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

• 5.1. Market Dynamics
  • 5.1.1. Drivers
    • 5.1.1.1. Rapid expansion of network infrastructure, including 5G deployment and iot devices integration
    • 5.1.1.2. Rising adoption of autonomous networks for dynamic resource allocation
    • 5.1.1.3. Exponential surge in volume of network traffic
  • 5.1.2. Restraints
    • 5.1.2.1. High Implementation costs and technological complexity
  • 5.1.3. Opportunities
    • 5.1.3.1. Development and expansion of 5G networking infrastructure
    • 5.1.3.2. Increasing innovations in AI-driven network security
  • 5.1.4. Challenges
    • 5.1.4.1. Concerns associated with privacy breaches and data security
• 5.2. Market Segmentation Analysis
  • 5.2.1. Industry: Increasing usage of artificial intelligence in networks for information technology to ensure system resilience against cyber threats
  • 5.2.2. Component: Increasing adoption of services for artificial intelligence to seamless functioning in network environments
• 5.3. Porter's Five Forces Analysis
  • 5.3.1. Threat of New Entrants
  • 5.3.2. Threat of Substitutes
  • 5.3.3. Bargaining Power of Customers
  • 5.3.4. Bargaining Power of Suppliers
  • 5.3.5. Industry Rivalry
• 5.4. PESTLE Analysis
  • 5.4.1. Political
  • 5.4.2. Economic
  • 5.4.3. Social
  • 5.4.4. Technological
  • 5.4.5. Legal
  • 5.4.6. Environmental

6. Artificial Intelligence in Networks Market, by Component

• 6.1. Introduction
• 6.2. Services
  • 6.2.1. Managed Services
  • 6.2.2. Professional Services
    • 6.2.2.1. Consulting
    • 6.2.2.2. System Integration & Implementation
    • 6.2.2.3. Training & Support
• 6.3. Solutions
  • 6.3.1. Hardware
    • 6.3.1.1. AI Accelerators
    • 6.3.1.2. GPUs
  • 6.3.2. Software
    • 6.3.2.1. AI Frameworks & Software Libraries
    • 6.3.2.2. AI Platforms

7. Artificial Intelligence in Networks Market, by Technology

• 7.1. Introduction
• 7.2. Automated Planning & Scheduling
• 7.3. Computer Vision
• 7.4. Deep Learning
• 7.5. Expert Systems
• 7.6. Machine Learning
  • 7.6.1. Reinforcement Learning
  • 7.6.2. Supervised Learning
  • 7.6.3. Unsupervised Learning
• 7.7. Natural Language Processing

8. Artificial Intelligence in Networks Market, by Deployment Mode

• 8.1. Introduction
• 8.2. On-Cloud
• 8.3. On-Premises

9. Artificial Intelligence in Networks Market, by Industry

• 9.1. Introduction
• 9.2. Banking, Financial Services, & Insurance
• 9.3. Energy & Utilities
• 9.4. Government & Defense
• 9.5. Healthcare
• 9.6. Information Technology
• 9.7. Manufacturing
• 9.8. Media & Entertainment
• 9.9. Retail & E-commerce
• 9.10. Telecommunications
• 9.11. Transportation & Logistics

10. Americas Artificial Intelligence in Networks Market

• 10.1. Introduction
• 10.2. Argentina
• 10.3. Brazil
• 10.4. Canada
• 10.5. Mexico
• 10.6. United States

11. Asia-Pacific Artificial Intelligence in Networks Market

• 11.1. Introduction
• 11.2. Australia
• 11.3. China
• 11.4. India
• 11.5. Indonesia
• 11.6. Japan
• 11.7. Malaysia
• 11.8. Philippines
• 11.9. Singapore
• 11.10. South Korea
• 11.11. Taiwan
• 11.12. Thailand
• 11.13. Vietnam

12. Europe, Middle East & Africa Artificial Intelligence in Networks Market

• 12.1. Introduction
• 12.2. Denmark
• 12.3. Egypt
• 12.4. Finland
• 12.5. France
• 12.6. Germany
• 12.7. Israel
• 12.8. Italy
• 12.9. Netherlands
• 12.10. Nigeria
• 12.11. Norway
• 12.12. Poland
• 12.13. Qatar
• 12.14. Russia
• 12.15. Saudi Arabia
• 12.16. South Africa
• 12.17. Spain
• 12.18. Sweden
• 12.19. Switzerland
• 12.20. Turkey
• 12.21. United Arab Emirates
• 12.22. United Kingdom

13. Competitive Landscape

• 13.1. Market Share Analysis, 2023
• 13.2. FPNV Positioning Matrix, 2023
• 13.3. Competitive Scenario Analysis
  • 13.3.1. Cisco Live 2024 in Las Vegas reveals USD 1B AI investment fund and cutting-edge networking security
  • 13.3.2. Nile announces advanced solution architecture for nile access service
  • 13.3.3. HPE to acquire Juniper Networks for USD 14 Billion in all-cash deal
• 13.4. Strategy Analysis & Recommendation

Companies Mentioned

• 1. Alibaba Group Holding Limited
• 2. Amazon Web Services, Inc.
• 3. Arista Networks, Inc.
• 4. Atos SE
• 5. Baidu, Inc.
• 6. Check Point Software Technologies Ltd.
• 7. Ciena Corporation
• 8. Cisco Systems, Inc.
• 9. Dell Technologies Inc.
• 10. Ericsson AB
• 11. F5 Networks, Inc.
• 12. Fortinet, Inc.
• 13. Fujitsu Limited
• 14. Google LLC
• 15. Hewlett Packard Enterprise Company
• 16. Huawei Technologies Co., Ltd.
• 17. Intel Corporation
• 18. International Business Machines Corporation
• 19. Juniper Networks, Inc.
• 20. Microsoft Corporation
• 21. NetApp, Inc.
• 22. Nokia Corporation
• 23. Nvidia Corporation
• 24. Palo Alto Networks, Inc.
• 25. Qualcomm Incorporated
• 26. Salesforce.com, Inc.
• 27. SAP SE
• 28. Telefonaktiebolaget LM Ericsson
• 29. Tencent Holdings Limited
• 30. VMware, Inc.