人工智慧物联网平台市场报告：趋势、预测和竞争分析（至 2031 年）

全球人工智慧物联网平台市场前景光明，製造业、医疗保健、能源和公用事业市场都存在机会。预计全球人工智慧物联网平台市场从 2025 年到 2031 年的复合年增长率将达到 24.8%。该市场的主要驱动力是人工智慧在资料分析和决策中的应用日益广泛、各行各业对自动化和优化的日益关注，以及对连网型设备和智慧技术的需求不断增长。

• Lucintel预测，按类型划分，智慧终端产品预计将在预测期内实现高速成长。
• 从应用来看，製造业预计将实现最高成长。
• 根据地区来看，预计亚太地区将在预测期内实现最高成长。

AI物联网平台市场的策略性成长机会

人工智慧物联网平台市场由技术进步和市场需求驱动，在各个应用领域呈现多种策略成长机会。

• 智慧城市：智慧城市计画为人工智慧物联网平台提供了巨大的成长机会。这些平台透过即时资料分析和自动化实现城市基础设施、交通和公共服务的管理。投资智慧城市计划将提高城市的效率、永续性和生活品质。
• 工业IoT(IIoT)：工业IoT领域透过将人工智慧融入製造和工业流程来提供成长机会。 AI IoT 平台可增强预测性维护、流程最佳化和供应链管理。该行业将受益于效率的提高、停机时间的减少和成本的节省。
• 医疗保健和远端监控：人工智慧物联网平台正在透过远端患者监护和智慧医疗设备的应用彻底改变医疗保健。这些平台能够即时收集和分析健康资料，从而改善医疗机构的患者照护和业务效率。对远端医疗和个人化医疗日益增长的需求正在推动这一机会。
• 农业和精密农业：人工智慧物联网平台在农业中的融合为精密农业和智慧灌溉提供了机会。这些平台提供资料主导的洞察，以优化作物管理、资源利用和产量预测。永续和高效农业的趋势正在支持这个不断发展的行业。
• 智慧家庭和建筑：随着人工智慧物联网平台的采用，智慧家庭和建筑市场正在扩大。这些平台为家庭自动化、能源管理和安全系统提供动力。对互联高效生活空间的需求不断增长，为该应用领域创造了成长机会。

这些策略性成长机会凸显了AI物联网平台的多样化应用和潜力。专注于智慧城市、工业IoT、医疗保健、农业和智慧家居将使企业能够接触不断扩大的市场并满足新的需求，推动人工智慧物联网领域的创新和成长。

AI物联网平台市场的驱动因素与挑战

AI物联网平台市场受到各种驱动因素​​和挑战的影响，包括技术、经济和监管因素。

推动AI物联网平台市场发展的因素有：

• 技术进步：人工智慧和物联网技术的快速进步将透过增强平台能力和扩大应用领域来推动市场成长。边缘运算、先进演算法和智慧感测器等技术创新将提高人工智慧物联网平台的效能和功能，刺激其应用和发展。
• 自动化需求不断增长：製造业、医疗保健和智慧城市等各个领域对自动化的需求不断增长，推动了人工智慧物联网平台的采用。这些平台实现了高效的自动化流程，降低了人事费用并提高了业务效率。
• 智慧基础设施的扩展：智慧城市和智慧基础设施的发展将创造对人工智慧物联网平台的需求。这些平台支援城市资源、交通和公共服务的管理和最佳化，推动市场成长。
• 更重视资料分析：对资料主导的决策和分析的日益重视正在推动对人工智慧物联网平台的需求。这些平台提供的先进分析功能使企业能够获得可行的见解、提高绩效并获得竞争优势。
• 支持性的政府政策：推动数位转型、智慧基础设施和永续技术的政府倡议和政策正在支持人工智慧物联网平台市场的成长。技术开发的资金筹措和奖励促进了创新和市场扩张。

AI物联网平台市场面临的挑战如下：

• 网路安全疑虑：网路安全威胁和漏洞对AI物联网平台市场构成重大挑战。确保资料保护并防止未授权存取需要强有力的安全措施和持续的警惕，这影响物联网解决方案的开发和采用。
• 整合和互通性挑战：随着组织部署各种物联网设备和平台，整合和互通性挑战随之出现。不同系统和标准之间的无缝通讯和相容对于AI物联网解决方案的有效实施至关重要。
• 部署成本高：人工智慧物联网平台的部署成本（包括硬体、软体和基础设施）可能会成为采用的障碍。高昂的初始投资和持续的维护成本可能会阻碍一些组织采用这种技术。

这些驱动因素和挑战将透过影响成长和市场发展来塑造人工智慧物联网平台市场。技术进步、自动化需求、不断增长的智慧基础设施、对资料分析的关注以及支援政策正在推动市场扩张，而网路安全问题、整合问题和高成本带来了挑战。平衡这些因素是成功部署和采用 AI IoT 平台的关键。

目录

第一章执行摘要

第二章 全球人工智慧物联网平台市场：市场动态

• 简介、背景和分类
• 供应链
• 产业驱动力与挑战

第三章市场趋势与预测分析（2019-2031）

• 宏观经济趋势（2019-2024）及预测（2025-2031）
• 全球人工智慧物联网平台市场趋势（2019-2024）及预测（2025-2031）
• 全球人工智慧物联网平台市场类型
  • 智慧终端产品
  • 技术服务
• 全球人工智慧物联网平台市场（按应用）
  • 製造业
  • 医疗保健
  • 能源与公用事业
  • 其他的

第四章区域市场趋势与预测分析（2019-2031）

• 全球人工智慧物联网平台市场（按地区）
• 北美人工智慧物联网平台市场
• 欧洲人工智慧物联网平台市场
• 亚太地区人工智慧物联网平台市场
• 其他地区人工智慧物联网平台市场

第五章 竞争分析

• 产品系列分析
• 营运整合
• 波特五力分析

第六章 成长机会与策略分析

• 成长机会分析
  • 全球人工智慧物联网平台市场成长机会（按类型）
  • 全球人工智慧物联网平台市场成长机会（按应用）
  • 全球人工智慧物联网平台市场各区域成长机会
• 全球AI物联网平台市场新趋势
• 战略分析
  • 新产品开发
  • 全球AI物联网平台市场产能扩张
  • 全球人工智慧物联网平台市场的企业合併
  • 认证和许可

第七章主要企业简介

• IBM
• Sharp Global
• Google
• AWS
• Microsoft
• Oracle
• HPE
• Cisco
• Intel
• Tencent Cloud

The future of the global AI IoT platform market looks promising with opportunities in the manufacturing, health care, and energy & utility markets. The global AI IoT platform market is expected to grow with a CAGR of 24.8% from 2025 to 2031. The major drivers for this market are the increasing adoption of AI for data analysis & decision-making, rising focus on automation & optimization across industries, and growing demand for connected devices & smart technologies.

• Lucintel forecasts that, within the type category, intelligent terminal product is expected to witness higher growth over the forecast period.
• Within the application category, manufacturing is expected to witness the highest growth.
• In terms of regions, APAC is expected to witness the highest growth over the forecast period.

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Emerging Trends in the AI IoT Platform Market

The AI IoT platform market is influenced by several emerging trends that reflect advancements in technology and shifting market demands.

• Edge Computing Integration: Edge computing is becoming increasingly important as it enables data processing closer to the source of data generation. This reduces latency and bandwidth usage, improving the performance of IoT applications. Integrating edge computing with AI IoT platforms enhances real-time decision-making and supports applications requiring immediate responses, such as autonomous systems and smart manufacturing.
• Increased Focus on Cybersecurity: As IoT devices become more prevalent, the focus on cybersecurity for AI IoT platforms is intensifying. Protecting data integrity and preventing unauthorized access are critical. Advances in AI-driven security solutions are being integrated into IoT platforms to enhance threat detection and response, addressing growing concerns about data breaches and cyberattacks.
• Expansion of AI-Driven Analytics: AI-driven analytics are being increasingly embedded into IoT platforms, providing deeper insights and predictive capabilities. This trend allows organizations to leverage big data and machine learning algorithms for improved decision-making, operational efficiency, and strategic planning. Enhanced analytics capabilities are driving more sophisticated and actionable insights from IoT data.
• Growth of Smart Cities and Infrastructure: The development of smart cities and smart infrastructure is driving demand for AI IoT platforms. These platforms enable efficient management of urban resources, traffic systems, and public services. Integration with AI allows for advanced data analysis and optimization of city operations, improving quality of life and sustainability in urban areas.
• Evolution of AI and IoT Standards: The evolution of standards for AI and IoT is crucial for interoperability and integration. Efforts are underway to develop standardized protocols and frameworks that ensure compatibility across different platforms and devices. This trend facilitates seamless integration and scalability, promoting widespread adoption and innovation in the AI IoT market.

These trends are reshaping the AI IoT platform market by enhancing performance, security, and functionality. The integration of edge computing, focus on cybersecurity, expansion of AI analytics, growth of smart infrastructure, and development of standards are driving innovation and adoption, leading to more sophisticated and efficient AI IoT solutions.

Recent Developments in the AI IoT Platform Market

Several key developments are shaping the AI IoT platform market, driven by technological advancements and changing industry needs.

• Enhanced Edge AI Capabilities: The development of advanced edge AI capabilities allows for real-time data processing and analysis at the edge of the network. This reduces latency and supports applications requiring immediate decision-making, such as autonomous vehicles and smart manufacturing. Enhanced edge AI capabilities are improving the performance and responsiveness of IoT systems.
• Advanced AI Algorithms for IoT: The integration of advanced AI algorithms with IoT platforms is driving innovation. These algorithms enable more accurate data analysis, predictive maintenance, and automation. The use of sophisticated machine learning models enhances the ability of IoT platforms to provide actionable insights and improve operational efficiency.
• Growth of AI-Powered IoT Security Solutions: The rise of AI-powered security solutions is addressing the growing need for robust cybersecurity in IoT systems. AI-driven tools are enhancing threat detection, response, and prevention, safeguarding IoT devices and data from cyber threats. This development is crucial for protecting sensitive information and ensuring the integrity of IoT networks.
• Expansion of IoT in Smart Cities: The integration of IoT platforms in smart city initiatives is expanding rapidly. These platforms enable efficient management of urban resources, infrastructure, and public services. AI enhances the capabilities of these systems, allowing for better traffic management, energy optimization, and improved public safety in smart cities.
• Standardization Efforts for AI IoT: Efforts to develop standardized protocols and frameworks for AI IoT platforms are advancing. Standardization promotes interoperability and compatibility across different devices and systems, facilitating integration and scalability. This development supports the widespread adoption of AI IoT technologies and encourages innovation within the industry.

These developments highlight the rapid progress and innovation in the AI IoT platform market. Enhanced edge AI capabilities, advanced algorithms, AI-powered security, smart city integration, and standardization efforts are driving growth and shaping the future of AI IoT technologies, leading to more efficient and secure solutions.

Strategic Growth Opportunities for AI IoT Platform Market

The AI IoT platform market presents several strategic growth opportunities across various applications, driven by technological advancements and market needs.

• Smart Cities: Smart city initiatives offer significant growth opportunities for AI IoT platforms. These platforms enable the management of urban infrastructure, traffic, and public services through real-time data analysis and automation. Investing in smart city projects can lead to improved urban efficiency, sustainability, and quality of life.
• Industrial IoT (IIoT): The industrial IoT sector presents opportunities for growth by integrating AI with manufacturing and industrial processes. AI IoT platforms can enhance predictive maintenance, process optimization, and supply chain management. This sector benefits from increased efficiency, reduced downtime, and cost savings.
• Healthcare and Remote Monitoring: AI IoT platforms are revolutionizing healthcare with applications in remote patient monitoring and smart medical devices. These platforms enable real-time health data collection and analysis, improving patient care and operational efficiency in healthcare facilities. The growing demand for telehealth and personalized medicine drives this opportunity.
• Agriculture and Precision Farming: The integration of AI IoT platforms in agriculture offers opportunities for precision farming and smart irrigation. These platforms provide data-driven insights for optimizing crop management, resource use, and yield prediction. The trend toward sustainable and efficient farming practices supports this growth area.
• Smart Homes and Buildings: The market for smart homes and buildings is expanding with the adoption of AI IoT platforms. These platforms enhance home automation, energy management, and security systems. The increasing demand for connected and efficient living spaces presents opportunities for growth in this application area.

These strategic growth opportunities highlight the diverse applications and potential of AI IoT platforms. By focusing on smart cities, industrial IoT, healthcare, agriculture, and smart homes, companies can tap into expanding markets and address emerging needs, driving innovation and growth in the AI IoT sector.

AI IoT Platform Market Driver and Challenges

The AI IoT platform market is influenced by various drivers and challenges, including technological, economic, and regulatory factors.

The factors responsible for driving the AI IoT platform market include:

• Technological Advancements: Rapid advancements in AI and IoT technologies drive market growth by enhancing platform capabilities and expanding application areas. Innovations such as edge computing, advanced algorithms, and smart sensors improve the performance and functionality of AI IoT platforms, fostering adoption and development.
• Increasing Demand for Automation: The growing demand for automation in various sectors, including manufacturing, healthcare, and smart cities, drives the adoption of AI IoT platforms. These platforms enable efficient, automated processes, reducing labor costs and improving operational efficiency.
• Expansion of Smart Infrastructure: The development of smart cities and smart infrastructure creates a demand for AI IoT platforms. These platforms support the management and optimization of urban resources, transportation, and public services, driving growth in the market.
• Rising Focus on Data Analytics: The increasing emphasis on data-driven decision-making and analytics boosts the demand for AI IoT platforms. Advanced analytics capabilities provided by these platforms enable organizations to derive actionable insights, improve performance, and gain a competitive edge.
• Supportive Government Policies: Government initiatives and policies promoting digital transformation, smart infrastructure, and sustainable technologies support the growth of the AI IoT platform market. Funding and incentives for technology development encourage innovation and market expansion.

Challenges in the AI IoT platform market include:

• Cybersecurity Concerns: Cybersecurity threats and vulnerabilities pose significant challenges to the AI IoT platform market. Ensuring data protection and preventing unauthorized access require robust security measures and constant vigilance, impacting the development and adoption of IoT solutions.
• Integration and Interoperability Issues: Integration and interoperability challenges arise as organizations deploy diverse IoT devices and platforms. Ensuring seamless communication and compatibility across different systems and standards is essential for the effective implementation of AI IoT solutions.
• High Implementation Costs: The cost of implementing AI IoT platforms, including hardware, software, and infrastructure, can be a barrier to adoption. High initial investments and ongoing maintenance costs may deter some organizations from adopting these technologies.

These drivers and challenges shape the AI IoT platform market by influencing growth and development. Technological advancements, automation demand, smart infrastructure expansion, data analytics focus, and supportive policies drive market expansion, while cybersecurity concerns, integration issues, and high costs present challenges. Balancing these factors is crucial for the successful deployment and adoption of AI IoT platforms.

List of AI IoT Platform Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies AI IoT platform companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the AI IoT platform companies profiled in this report include-

• IBM
• Sharp Global
• Google
• AWS
• Microsoft
• Oracle
• HPE
• Cisco
• Intel
• Tencent Cloud

AI IoT Platform by Segment

The study includes a forecast for the global AI IoT platform market by type, application, and region.

AI IoT Platform Market by Type [Analysis by Value from 2019 to 2031]:

• Intelligent Terminal Products
• Technical Services

AI IoT Platform Market by Application [Analysis by Value from 2019 to 2031]:

• Manufacturing
• Health Care
• Energy & Utilities
• Others

AI IoT Platform Market by Region [Analysis by Value from 2019 to 2031]:

• North America
• Europe
• Asia Pacific
• The Rest of the World

Country Wise Outlook for the AI IoT Platform Market

The AI IoT platform market is rapidly evolving as technology advances and organizations seek to harness the power of artificial intelligence (AI) and the Internet of Things (IoT) to drive innovation and efficiency. These platforms integrate AI capabilities with IoT infrastructure, enabling smarter, more automated, and data-driven solutions. Key developments across different regions reflect local priorities and technological progress, influencing how these platforms are used in various industries.

• United States: In the U.S., the AI IoT platform market is marked by significant advancements in AI-driven analytics and edge computing. Companies are increasingly adopting platforms that leverage machine learning and real-time data processing to enhance decision-making and operational efficiency. Integration with cloud services and the expansion of 5G networks are also contributing to growth, enabling faster data transfer and more robust IoT applications.
• China: China is rapidly advancing in the AI IoT platform space, driven by extensive investments in smart cities and industrial automation. Chinese firms are focusing on developing advanced AI algorithms and integrating them with IoT systems for applications in manufacturing, transportation, and urban management. Government policies and funding are supporting the development of these technologies, positioning China as a key player in the global AI IoT landscape.
• Germany: Germany is leading in the AI IoT platform market with a strong emphasis on industrial IoT (IIoT) and smart manufacturing. German companies are adopting platforms that combine AI with IoT to enhance production efficiency, predictive maintenance, and supply chain management. The country's focus on Industry 4.0 and its robust industrial base are driving innovations and applications of AI IoT platforms in the manufacturing and engineering sectors.
• India: In India, the AI IoT platform market is experiencing growth driven by the increasing adoption of smart infrastructure and agricultural technology. Indian firms are leveraging AI IoT platforms for applications in smart cities, energy management, and precision agriculture. The focus is on cost-effective solutions and scalable platforms that address local needs and support the country's rapid urbanization and technological development.
• Japan: Japan is focusing on integrating AI with IoT platforms to advance robotics, smart homes, and autonomous vehicles. Recent developments include sophisticated AI algorithms for enhanced automation and IoT solutions that support Japan's aging population through smart healthcare technologies. Japanese companies are investing in AI IoT platforms to improve efficiency and quality of life through advanced technology applications in both industrial and consumer sectors.

Features of the Global AI IoT Platform Market

Market Size Estimates: AI IoT platform market size estimation in terms of value ($B).

Trend and Forecast Analysis: Market trends (2019 to 2024) and forecast (2025 to 2031) by various segments and regions.

Segmentation Analysis: AI IoT platform market size by type, application, and region in terms of value ($B).

Regional Analysis: AI IoT platform market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the AI IoT platform market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the AI IoT platform market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

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This report answers following 11 key questions:

• Q.1. What are some of the most promising, high-growth opportunities for the AI IoT platform market by type (intelligent terminal products and technical services), application (manufacturing, health care, energy & utilities, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
• Q.2. Which segments will grow at a faster pace and why?
• Q.3. Which region will grow at a faster pace and why?
• Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
• Q.5. What are the business risks and competitive threats in this market?
• Q.6. What are the emerging trends in this market and the reasons behind them?
• Q.7. What are some of the changing demands of customers in the market?
• Q.8. What are the new developments in the market? Which companies are leading these developments?
• Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
• Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
• Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Global AI IoT Platform Market : Market Dynamics

• 2.1: Introduction, Background, and Classifications
• 2.2: Supply Chain
• 2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2019 to 2031

• 3.1. Macroeconomic Trends (2019-2024) and Forecast (2025-2031)
• 3.2. Global AI IoT Platform Market Trends (2019-2024) and Forecast (2025-2031)
• 3.3: Global AI IoT Platform Market by Type
  • 3.3.1: Intelligent Terminal Products
  • 3.3.2: Technical Services
• 3.4: Global AI IoT Platform Market by Application
  • 3.4.1: Manufacturing
  • 3.4.2: Health Care
  • 3.4.3: Energy & Utilities
  • 3.4.4: Others

4. Market Trends and Forecast Analysis by Region from 2019 to 2031

• 4.1: Global AI IoT Platform Market by Region
• 4.2: North American AI IoT Platform Market
  • 4.2.1: North American Market by Type: Intelligent Terminal Products and Technical Services
  • 4.2.2: North American Market by Application: Manufacturing, Health Care, Energy & Utilities, and Others
• 4.3: European AI IoT Platform Market
  • 4.3.1: European Market by Type: Intelligent Terminal Products and Technical Services
  • 4.3.2: European Market by Application: Manufacturing, Health Care, Energy & Utilities, and Others
• 4.4: APAC AI IoT Platform Market
  • 4.4.1: APAC Market by Type: Intelligent Terminal Products and Technical Services
  • 4.4.2: APAC Market by Application: Manufacturing, Health Care, Energy & Utilities, and Others
• 4.5: ROW AI IoT Platform Market
  • 4.5.1: ROW Market by Type: Intelligent Terminal Products and Technical Services
  • 4.5.2: ROW Market by Application: Manufacturing, Health Care, Energy & Utilities, and Others

5. Competitor Analysis

• 5.1: Product Portfolio Analysis
• 5.2: Operational Integration
• 5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

• 6.1: Growth Opportunity Analysis
  • 6.1.1: Growth Opportunities for the Global AI IoT Platform Market by Type
  • 6.1.2: Growth Opportunities for the Global AI IoT Platform Market by Application
  • 6.1.3: Growth Opportunities for the Global AI IoT Platform Market by Region
• 6.2: Emerging Trends in the Global AI IoT Platform Market
• 6.3: Strategic Analysis
  • 6.3.1: New Product Development
  • 6.3.2: Capacity Expansion of the Global AI IoT Platform Market
  • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global AI IoT Platform Market
  • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

• 7.1: IBM
• 7.2: Sharp Global
• 7.3: Google
• 7.4: AWS
• 7.5: Microsoft
• 7.6: Oracle
• 7.7: HPE
• 7.8: Cisco
• 7.9: Intel
• 7.10: Tencent Cloud