세계의 IoT용 인공지능 시장 : 부문별 예측(2025-2030년)

The Artificial Intelligence in IoT Market was valued at USD 9.17 billion in 2023, expected to reach USD 10.75 billion in 2024, and is projected to grow at a CAGR of 17.35%, to USD 28.11 billion by 2030.

The scope and definition of Artificial Intelligence (AI) in the Internet of Things (IoT) encompass the integration of AI technologies, like machine learning and deep learning, with IoT-connected devices to enhance operational efficiency, data analytics, decision-making, and automation. The necessity for AI in IoT stems from the exponential growth of connected devices generating vast amounts of data that require intelligent processing to extract meaningful insights. Applications span numerous sectors, including smart homes, industrial IoT, healthcare, automotive, and retail, facilitating predictive maintenance, real-time analytics, personalized experiences, and enhanced security. The end-use scope incorporates enterprises looking to streamline operations, reduce costs, and enable advanced analytics. Key growth factors include advances in AI capabilities, reduction in IoT device costs, and increasing demand for efficient handling of big data. However, market challenges such as data privacy concerns, integration complexities, and high initial deployment costs persist. Opportunities lie in developing AI algorithms that can operate efficiently on edge devices, enhancing real-time data processing, and leveraging AI for improving cybersecurity of IoT networks. There's a rising demand for AI-driven analytics in smart city projects and industrial applications, creating fertile ground for innovation. Businesses are recommended to invest in solutions that combine AI with IoT to improve interoperability and develop scalable platforms that address industry-specific needs. The market nature is competitive with rapid technological advancements, requiring continuous R&D investments to stay ahead. Limitations include the dependency on a robust infrastructure and skilled workforce for AI implementation, potentially slowing down adoption in segments with lesser resources. While challenges remain in areas like data standardization and regulatory compliance, exploring breakthroughs in autonomous IoT systems and focusing on user-centric design for AI-driven IoT applications provide significant innovation potential for growth.

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

The Artificial Intelligence in IoT 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
  • Need to manage huge volumes of data without any complexity in operation
  • Growing demand for process automation in diverse sectors
  • Rising need form manufacturing sector attributed to increasing adoption of sensors and integrated devices
• Market Restraints
  • Highly cost of implementation of AI systems
• Market Opportunities
  • Government and private sector funding to encourage AI research and development in IoT
  • Increasing need for real-time processing and decision-making to improve consumer experience
• Market Challenges
  • Dearth of knowledge to expand the application among consumers

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

Porter's five forces framework is a critical tool for understanding the competitive landscape of the Artificial Intelligence in IoT 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 IoT Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the Artificial Intelligence in IoT 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 IoT Market

A detailed market share analysis in the Artificial Intelligence in IoT 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 IoT Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the Artificial Intelligence in IoT 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 IoT Market

A strategic analysis of the Artificial Intelligence in IoT 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 IoT Market, highlighting leading vendors and their innovative profiles. These include Amazon Web Services, Inc., Autoplant System India Pvt. Ltd., C3.ai, Inc., General Electric company, Google LLC by Alphabet Inc., Hitachi, Ltd., Imagimob AB, International Business Machines Corporation, Microsoft Corporation, Oracle Corporation, PTC Inc., Salesforce.com, Inc., SAP SE, SAS Institute Inc., and Softweb Solutions Inc..

Market Segmentation & Coverage

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

• Based on Component, market is studied across Platform, Services, and Software. The Platform is further studied across Application Management, Connectivity Management, and Device Management. The Services is further studied across Deployment & Integration, Managed Services, Support & Maintenance, and Training & Consulting. The Software is further studied across Data Management, Edge Solution, Network Bandwidth Management, Real-Time Streaming Analytics, Remote Monitoring, and Security.
• Based on Technology, market is studied across Ml & Deep Learning and Natural Language Processing.
• Based on Vertical, market is studied across Banking, Financial Services & Insurance, Energy & Utilities, Government & Defense, Healthcare & Life Sciences, Manufacturing, Retail, and Transportation & Mobility. The Banking, Financial Services & Insurance is further studied across Fraud & Risk Management, Investment Prediction, and Payment Transaction Security. The Energy & Utilities is further studied across Power Usage Analytics and Smart Grid Management. The Government & Defense is further studied across Autonomous Defense System and Smart Cities. The Healthcare & Life Sciences is further studied across Personalized Treatment and Remote Patient Monitoring. The Manufacturing is further studied across Predictive Maintenance, Process Optimization, and Supply Chain Management. The Retail is further studied across Inventory Planning, Smart Stores, and Upsell & Cross-Channel Marketing. The Transportation & Mobility is further studied across Asset Tracking & Performance Management, Connected Vehicles, and Fleet Management.
• 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. Need to manage huge volumes of data without any complexity in operation
    • 5.1.1.2. Growing demand for process automation in diverse sectors
    • 5.1.1.3. Rising need form manufacturing sector attributed to increasing adoption of sensors and integrated devices
  • 5.1.2. Restraints
    • 5.1.2.1. Highly cost of implementation of AI systems
  • 5.1.3. Opportunities
    • 5.1.3.1. Government and private sector funding to encourage AI research and development in IoT
    • 5.1.3.2. Increasing need for real-time processing and decision-making to improve consumer experience
  • 5.1.4. Challenges
    • 5.1.4.1. Dearth of knowledge to expand the application among consumers
• 5.2. Market Segmentation Analysis
• 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 IoT Market, by Component

• 6.1. Introduction
• 6.2. Platform
  • 6.2.1. Application Management
  • 6.2.2. Connectivity Management
  • 6.2.3. Device Management
• 6.3. Services
  • 6.3.1. Deployment & Integration
  • 6.3.2. Managed Services
  • 6.3.3. Support & Maintenance
  • 6.3.4. Training & Consulting
• 6.4. Software
  • 6.4.1. Data Management
  • 6.4.2. Edge Solution
  • 6.4.3. Network Bandwidth Management
  • 6.4.4. Real-Time Streaming Analytics
  • 6.4.5. Remote Monitoring
  • 6.4.6. Security

7. Artificial Intelligence in IoT Market, by Technology

• 7.1. Introduction
• 7.2. Ml & Deep Learning
• 7.3. Natural Language Processing

8. Artificial Intelligence in IoT Market, by Vertical

• 8.1. Introduction
• 8.2. Banking, Financial Services & Insurance
  • 8.2.1. Fraud & Risk Management
  • 8.2.2. Investment Prediction
  • 8.2.3. Payment Transaction Security
• 8.3. Energy & Utilities
  • 8.3.1. Power Usage Analytics
  • 8.3.2. Smart Grid Management
• 8.4. Government & Defense
  • 8.4.1. Autonomous Defense System
  • 8.4.2. Smart Cities
• 8.5. Healthcare & Life Sciences
  • 8.5.1. Personalized Treatment
  • 8.5.2. Remote Patient Monitoring
• 8.6. Manufacturing
  • 8.6.1. Predictive Maintenance
  • 8.6.2. Process Optimization
  • 8.6.3. Supply Chain Management
• 8.7. Retail
  • 8.7.1. Inventory Planning
  • 8.7.2. Smart Stores
  • 8.7.3. Upsell & Cross-Channel Marketing
• 8.8. Transportation & Mobility
  • 8.8.1. Asset Tracking & Performance Management
  • 8.8.2. Connected Vehicles
  • 8.8.3. Fleet Management

9. Americas Artificial Intelligence in IoT Market

• 9.1. Introduction
• 9.2. Argentina
• 9.3. Brazil
• 9.4. Canada
• 9.5. Mexico
• 9.6. United States

10. Asia-Pacific Artificial Intelligence in IoT Market

• 10.1. Introduction
• 10.2. Australia
• 10.3. China
• 10.4. India
• 10.5. Indonesia
• 10.6. Japan
• 10.7. Malaysia
• 10.8. Philippines
• 10.9. Singapore
• 10.10. South Korea
• 10.11. Taiwan
• 10.12. Thailand
• 10.13. Vietnam

11. Europe, Middle East & Africa Artificial Intelligence in IoT Market

• 11.1. Introduction
• 11.2. Denmark
• 11.3. Egypt
• 11.4. Finland
• 11.5. France
• 11.6. Germany
• 11.7. Israel
• 11.8. Italy
• 11.9. Netherlands
• 11.10. Nigeria
• 11.11. Norway
• 11.12. Poland
• 11.13. Qatar
• 11.14. Russia
• 11.15. Saudi Arabia
• 11.16. South Africa
• 11.17. Spain
• 11.18. Sweden
• 11.19. Switzerland
• 11.20. Turkey
• 11.21. United Arab Emirates
• 11.22. United Kingdom

12. Competitive Landscape

• 12.1. Market Share Analysis, 2023
• 12.2. FPNV Positioning Matrix, 2023
• 12.3. Competitive Scenario Analysis
• 12.4. Strategy Analysis & Recommendation

Companies Mentioned

• 1. Amazon Web Services, Inc.
• 2. Autoplant System India Pvt. Ltd.
• 3. C3.ai, Inc.
• 4. General Electric company
• 5. Google LLC by Alphabet Inc.
• 6. Hitachi, Ltd.
• 7. Imagimob AB
• 8. International Business Machines Corporation
• 9. Microsoft Corporation
• 10. Oracle Corporation
• 11. PTC Inc.
• 12. Salesforce.com, Inc.
• 13. SAP SE
• 14. SAS Institute Inc.
• 15. Softweb Solutions Inc.