세계의 무선 기술용 AI 시장 : 컴포넌트, 프로토콜, 기능 모듈, 최종 사용자, 용도별 예측(2025-2030년)

The AI for Wireless Technology Market was valued at USD 32.01 billion in 2023, expected to reach USD 36.14 billion in 2024, and is projected to grow at a CAGR of 13.27%, to USD 76.61 billion by 2030.

Artificial Intelligence (AI) has significantly transformed wireless technology, revolutionizing how data is transmitted, managed, and utilized. The scope of AI in wireless technology encompasses enhancing network efficiency, optimizing resource allocation, improving data security, and facilitating predictive analytics for network maintenance. The necessity of AI in this sector arises from the increasing complexity of wireless networks driven by IoT proliferation, 5G rollout, and the growing demands for high-data transfer rates and low-latency communications. Applications of AI in wireless networks include automated network management, dynamic spectrum sharing, anomaly detection, and user experience optimization. The end-use scope extends to telecommunications, smart cities, autonomous vehicles, healthcare, and industrial automation. Core market growth factors include the continuous evolution of telecommunications infrastructure, heightened need for efficient spectrum management, and increasing investments in AI and machine learning technologies. The shift towards 6G and the expansion of IoT ecosystems present potent opportunities alongside emerging markets significantly adopting these technologies. However, the market faces challenges such as high initial deployment costs, technical integration complexity, data privacy concerns, and regulatory hurdles. To navigate these challenges and harness growth opportunities, innovations in AI-driven dynamic spectrum allocation, edge AI processing, AI for network security, and efficient network resource management must be prioritized. Research and development should focus on enhancing AI algorithms for real-time data processing, improved energy efficiency in AI operations, and seamless interoperability across devices and networks. Businesses can benefit from predictive maintenance, customer behavior analytics, and tailored service offerings. The market is competitive yet ripe for disruption by firms that can offer scalable and flexible AI solutions that address the dynamic needs of wireless technology infrastructure. Strategic partnerships and cross-sector collaborations may further accelerate market penetration and innovation.

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving AI for Wireless Technology Market

The AI for Wireless Technology 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
  • Exponential surge in wireless data traffic, necessitating efficient network management solutions
  • Advancements in machine learning and deep learning technologies leading to innovation in wireless technologies
  • The proliferation of smart devices and IoT applications across industries
• Market Restraints
  • Data privacy and security concerns related to AI for Wireless technology
• Market Opportunities
  • Advancements in AI-based predictive analytics for improving network reliability and performance
  • Integration of AI in the development and deployment of next-generation wireless technologies such as 6G technology
• Market Challenges
  • The complexity and cost of integrating AI into existing wireless infrastructures

Porter's Five Forces: A Strategic Tool for Navigating the AI for Wireless Technology Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the AI for Wireless Technology 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 AI for Wireless Technology Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the AI for Wireless Technology 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 AI for Wireless Technology Market

A detailed market share analysis in the AI for Wireless Technology 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 AI for Wireless Technology Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the AI for Wireless Technology 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 AI for Wireless Technology Market

A strategic analysis of the AI for Wireless Technology 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 AI for Wireless Technology Market, highlighting leading vendors and their innovative profiles. These include Apple Inc., AT&T, Inc., Broadcom Inc., Cisco Systems, Inc., Google LLC by Alphabet Inc., Huawei Technologies Co., Ltd., Hughes Systique Corporation., IBM Corporation, Intel Connectivity, Juniper Networks, Inc., Keysight Technologies, Inc., Marvell Technology, Inc., MediaTek Inc., Microsoft Corporation, Nokia Corporation, NTT Docomo, Inc., Nvidia Corporation, Qualcomm Technologies, Inc., Rakuten Mobile, Inc., Samsung Electronics Co., Ltd., Silicon Laboratories by Skyworks Solutions, Inc., Telefonica, S.A., Wyebot, and ZTE Corporation.

Market Segmentation & Coverage

This research report categorizes the AI for Wireless Technology Market to forecast the revenues and analyze trends in each of the following sub-markets:

• Based on Components, market is studied across Hardware, Services, and Software. The Hardware is further studied across AI-enabled Chips, Antennas, and Sensors. The Services is further studied across Consulting, Integration, and Maintenance. The Software is further studied across AI algorithms and Machine Learning Models.
• Based on Protocol, market is studied across 5G and Beyond, Bluetooth Low Energy, Constrained Application Protocol, LoRaWAN, Message Queuing Telemetry Transport, Wi-Fi 6, and Zigbee.
• Based on Functional Module, market is studied across AI-Driven Spectrum Management, AI-Powered Beamforming & Multiple Input Multiple Output, Cognitive Radio Systems, Machine Learning for Wireless Signal Processing, and Neural Network-Based Interference Mitigation.
• Based on End Users, market is studied across Government & Defense, Healthcare, Manufacturing, Telecommunications, and Transportation.
• Based on Applications, market is studied across Network Optimization & Management, Predictive Maintenance, Security & Threat Detection, Spectrum Management, and Traffic Analysis & Optimization.
• 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. Exponential surge in wireless data traffic, necessitating efficient network management solutions
    • 5.1.1.2. Advancements in machine learning and deep learning technologies leading to innovation in wireless technologies
    • 5.1.1.3. The proliferation of smart devices and IoT applications across industries
  • 5.1.2. Restraints
    • 5.1.2.1. Data privacy and security concerns related to AI for Wireless technology
  • 5.1.3. Opportunities
    • 5.1.3.1. Advancements in AI-based predictive analytics for improving network reliability and performance
    • 5.1.3.2. Integration of AI in the development and deployment of next-generation wireless technologies such as 6G technology
  • 5.1.4. Challenges
    • 5.1.4.1. The complexity and cost of integrating AI into existing wireless infrastructures
• 5.2. Market Segmentation Analysis
  • 5.2.1. Protocol: Advances of AI in wireless technology protocols
  • 5.2.2. End Users: Diverse applications across end-use industries
• 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. AI for Wireless Technology Market, by Components

• 6.1. Introduction
• 6.2. Hardware
  • 6.2.1. AI-enabled Chips
  • 6.2.2. Antennas
  • 6.2.3. Sensors
• 6.3. Services
  • 6.3.1. Consulting
  • 6.3.2. Integration
  • 6.3.3. Maintenance
• 6.4. Software
  • 6.4.1. AI algorithms
  • 6.4.2. Machine Learning Models

7. AI for Wireless Technology Market, by Protocol

• 7.1. Introduction
• 7.2. 5G and Beyond
• 7.3. Bluetooth Low Energy
• 7.4. Constrained Application Protocol
• 7.5. LoRaWAN
• 7.6. Message Queuing Telemetry Transport
• 7.7. Wi-Fi 6
• 7.8. Zigbee

8. AI for Wireless Technology Market, by Functional Module

• 8.1. Introduction
• 8.2. AI-Driven Spectrum Management
• 8.3. AI-Powered Beamforming & Multiple Input Multiple Output
• 8.4. Cognitive Radio Systems
• 8.5. Machine Learning for Wireless Signal Processing
• 8.6. Neural Network-Based Interference Mitigation

9. AI for Wireless Technology Market, by End Users

• 9.1. Introduction
• 9.2. Government & Defense
• 9.3. Healthcare
• 9.4. Manufacturing
• 9.5. Telecommunications
• 9.6. Transportation

10. AI for Wireless Technology Market, by Applications

• 10.1. Introduction
• 10.2. Network Optimization & Management
• 10.3. Predictive Maintenance
• 10.4. Security & Threat Detection
• 10.5. Spectrum Management
• 10.6. Traffic Analysis & Optimization

11. Americas AI for Wireless Technology Market

• 11.1. Introduction
• 11.2. Argentina
• 11.3. Brazil
• 11.4. Canada
• 11.5. Mexico
• 11.6. United States

12. Asia-Pacific AI for Wireless Technology Market

• 12.1. Introduction
• 12.2. Australia
• 12.3. China
• 12.4. India
• 12.5. Indonesia
• 12.6. Japan
• 12.7. Malaysia
• 12.8. Philippines
• 12.9. Singapore
• 12.10. South Korea
• 12.11. Taiwan
• 12.12. Thailand
• 12.13. Vietnam

13. Europe, Middle East & Africa AI for Wireless Technology Market

• 13.1. Introduction
• 13.2. Denmark
• 13.3. Egypt
• 13.4. Finland
• 13.5. France
• 13.6. Germany
• 13.7. Israel
• 13.8. Italy
• 13.9. Netherlands
• 13.10. Nigeria
• 13.11. Norway
• 13.12. Poland
• 13.13. Qatar
• 13.14. Russia
• 13.15. Saudi Arabia
• 13.16. South Africa
• 13.17. Spain
• 13.18. Sweden
• 13.19. Switzerland
• 13.20. Turkey
• 13.21. United Arab Emirates
• 13.22. United Kingdom

14. Competitive Landscape

• 14.1. Market Share Analysis, 2023
• 14.2. FPNV Positioning Matrix, 2023
• 14.3. Competitive Scenario Analysis
  • 14.3.1. Viettel High Tech and DeepSig Announce Industry-First AI/ML-based Neural Receiver Operating in Live 5G Network
  • 14.3.2. Keysight And InterDigital To Demonstrate AI In 6G Systems At Mobile World Congress 2024
  • 14.3.3. NTT Docomo Deploys First AI-Powered 5G Network in Japan
• 14.4. Strategy Analysis & Recommendation

Companies Mentioned

• 1. Apple Inc.
• 2. AT&T, Inc.
• 3. Broadcom Inc.
• 4. Cisco Systems, Inc.
• 5. Google LLC by Alphabet Inc.
• 6. Huawei Technologies Co., Ltd.
• 7. Hughes Systique Corporation.
• 8. IBM Corporation
• 9. Intel Connectivity
• 10. Juniper Networks, Inc.
• 11. Keysight Technologies, Inc.
• 12. Marvell Technology, Inc.
• 13. MediaTek Inc.
• 14. Microsoft Corporation
• 15. Nokia Corporation
• 16. NTT Docomo, Inc.
• 17. Nvidia Corporation
• 18. Qualcomm Technologies, Inc.
• 19. Rakuten Mobile, Inc.
• 20. Samsung Electronics Co., Ltd.
• 21. Silicon Laboratories by Skyworks Solutions, Inc.
• 22. Telefonica, S.A.
• 23. Wyebot
• 24. ZTE Corporation