工業人工智慧市場報告：2031 年趨勢、預測與競爭分析

全球工業人工智慧市場前景光明，在玻璃製造、半導體製造、汽車、機械、化學、石油和天然氣以及包裝市場都存在機會。預計全球工業人工智慧市場從 2025 年到 2031 年的複合年成長率將達到 30.4%。該市場的主要驅動力是工業領域對自動化和效率的需求不斷增加、工業環境中感測器的使用不斷增加以及工業 4.0 技術的採用不斷增加。

• 根據類型，Lucintel 預測軟體領域將在預測期內見證高速成長。
• 從應用角度來看，玻璃製造預計將實現最高成長。
• 根據地區來看，預計亞太地區將在預測期內實現最高成長。

工業人工智慧市場的策略成長機會

在技​​術進步和不斷發展的工業需求的推動下，工業人工智慧市場在關鍵應用領域呈現出多項策略成長機會。

• 擴大預測性維護：人工智慧主導的預測性維護具有巨大的成長潛力。透過減少設備停機時間和維護成本，該應用將極大地造福製造業和能源業等各種行業。
• 智慧製造的成長：智慧製造技術的興起為人工智慧的融合創造了機會。人工智慧可以增強流程自動化、品管和即時監控，使製造營運更有效率、更有效率。
• 供應鏈最佳化的進步：透過人工智慧進行供應鏈最佳化是一個關鍵的成長領域。人工智慧改善了需求預測、庫存管理和物流，從而實現了更有效率、更靈活的供應鏈。
• 人工智慧機器人的發展：人工智慧在機器人組裝和檢查等任務中的應用將提供成長機會。人工智慧機器人可以提高工業流程的精度、靈活性和效率。
• 增強流程最佳化：用於流程最佳化的 AI 解決方案越來越受歡迎。透過分析大量資料，人工智慧可以識別效率低下的問題並提出改進建議。

這些策略成長機會凸顯了工業人工智慧在一系列應用領域推動創新和效率的潛力。專注於預測性維護、智慧製造、供應鏈最佳化、機器人和流程最佳化將使公司能夠利用新的市場趨勢和需求。

工業人工智慧市場的促進因素與挑戰

工業人工智慧市場受到各種促進因素​​和挑戰的影響，這些因素和挑戰正在影響其成長和市場發展。這些因素包括技術、經濟和監管方面的考慮。

推動工業人工智慧市場的因素包括：

• 人工智慧技術的進步：人工智慧演算法和機器學習模型的不斷改進正在推動工業人工智慧的發展。這些進步將增強人工智慧在各個產業領域的能力和應用。
• 提高物聯網的採用率：人工智慧與物聯網設備的整合是關鍵促進因素。物聯網可以實現即時資料收集和分析，與人工智慧相結合可以增強工業流程的監控、控制和最佳化。
• 對業務效率的需求：提高業務效率的需求正在推動工業人工智慧的採用。人工智慧解決方案改善了流程最佳化、預測性維護和自動化，從而節省了成本並提高了生產力。
• 研發投入：研發投入的增加正在推動工業人工智慧的創新。資金籌措和合作支持新技術和應用的開發，推動產業發展。
• 重視資料驅動的決策：資料主導的決策正在推動工業人工智慧的發展。人工智慧透過資料分析提供寶貴的見解，使工業營運能夠做出更明智、更具策略性的決策。

工業人工智慧市場面臨的挑戰是：

• 整合複雜性：將人工智慧與現有工業系統整合可能很複雜且具有挑戰性。確保相容性和無縫操作需要大量的努力和專業知識。
• 實施成本高：人工智慧解決方案的實施成本可能很高。這包括技術收購、系統整合和培訓方面的成本，這對一些組織來說可能是一個障礙。
• 資料隱私和安全問題：資料隱私和安全問題是關鍵問題。確保人工智慧系統遵守法規並保護敏感資訊對於贏得信任和維護安全至關重要。

影響工業人工智慧市場的促進因素和挑戰凸顯了持續創新和適應的必要性。有效解決這些因素是利用成長機會和克服市場障礙的關鍵。

目錄

第1章執行摘要

第2章 全球工業人工智慧市場：市場動態

• 簡介、背景和分類
• 供應鏈
• 產業驅動力與挑戰

第3章市場趨勢與預測分析（2019-2031）

• 宏觀經濟趨勢（2019-2024）及預測（2025-2031）
• 全球工業人工智慧市場趨勢（2019-2024）及預測（2025-2031）
• 全球工業人工智慧市場（按類型）
  • 軟體
  • 硬體
• 全球工業人工智慧市場（按應用）
  • 玻璃製造
  • 半導體製造
  • 車
  • 機器
  • 化學
  • 石油和天然氣
  • 包裝
  • 其他

第4章區域市場趨勢與預測分析（2019-2031）

• 全球工業人工智慧市場（按地區）
• 北美工業人工智慧市場
• 歐洲工業人工智慧市場
• 亞太工業人工智慧市場
• 其他地區工業人工智慧市場

第5章 競爭分析

• 產品系列分析
• 營運整合
• 波特五力分析

第6章 成長機會與策略分析

• 成長機會分析
  • 全球工業人工智慧市場成長機會（按類型）
  • 全球工業人工智慧市場的成長機會（按應用）
  • 全球工業人工智慧市場各區域成長機會
• 全球工業人工智慧市場的新趨勢
• 戰略分析
  • 新產品開發
  • 全球工業人工智慧市場產能擴張
  • 全球工業人工智慧市場的企業合併
  • 認證和許可

第7章主要企業簡介

• Siemens
• IBM
• Microsoft
• Cisco Systems
• General Electric Company
• Rockwell Automation

The future of the global industrial AI market looks promising with opportunities in the glass manufacturing, semiconductor manufacturing, automotive, machinery, chemical, oil & gas, and packaging markets. The global industrial AI market is expected to grow with a CAGR of 30.4% from 2025 to 2031. The major drivers for this market are increasing demand for automation and efficiency among industries, growing use of sensors in industrial settings, and rising adoption of industry 4.0 technologies.

• Lucintel forecasts that, within the type category, the software segment is expected to witness higher growth over the forecast period.
• Within the application category, glass 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 Industrial AI Market

Industrial AI is evolving with several key trends that are reshaping how industries operate and leverage technology.

• Increased Use of Edge AI: Edge AI is gaining traction, allowing data processing and decision-making to occur closer to the source. This trend reduces latency and improves real-time response in industrial applications, enhancing operational efficiency and safety.
• Integration of AI with IoT: Combining AI with IoT devices is transforming industrial operations by enabling smarter monitoring and control. This integration enhances predictive maintenance, process optimization, and data-driven decision-making across various industrial sectors.
• Adoption of AI-Driven Robotics: AI-driven robotics are increasingly used in manufacturing for tasks like assembly, inspection, and material handling. These robots offer increased precision, flexibility, and efficiency, contributing to higher productivity and reduced operational costs.
• Focus on Predictive Maintenance: Predictive maintenance powered by AI is becoming a standard practice. By analyzing data from equipment sensors, AI can predict failures before they occur, minimizing downtime and maintenance costs while extending equipment lifespan.
• Enhanced Data Analytics: Advanced data analytics driven by AI are providing deeper insights into industrial processes. This trend enables better decision-making, process optimization, and identification of inefficiencies, leading to more informed strategies and operational improvements.

These emerging trends are significantly reshaping the industrial AI market by enhancing real-time processing, integration, and automation. As these trends advance, they are driving increased efficiency, productivity, and cost-effectiveness across industrial applications.

Recent Developments in the Industrial AI Market

Recent developments in the industrial AI market highlight the sector's rapid evolution and its impact on manufacturing and operational processes.

• Development of Advanced AI Algorithms: Innovations in AI algorithms are improving the accuracy and efficiency of industrial AI applications. These algorithms enhance machine learning models used in predictive maintenance, quality control, and process optimization.
• Expansion of AI-Enabled Robotics: The deployment of AI-enabled robotics is increasing in manufacturing environments. These robots offer advanced capabilities in tasks such as assembly, inspection, and material handling, improving operational efficiency and flexibility.
• Growth in AI-Powered Predictive Maintenance: AI-powered predictive maintenance solutions are becoming more prevalent. These solutions analyze data from equipment to predict failures and optimize maintenance schedules, reducing downtime and maintenance costs.
• Integration with IoT Devices: AI integration with IoT devices is advancing, enabling more intelligent monitoring and control of industrial processes. This integration supports real-time data analysis and enhances process optimization and efficiency.
• Focus on Customizable AI Solutions: There is a growing trend toward developing customizable AI solutions tailored to specific industrial needs. These solutions offer greater flexibility and adaptability, addressing unique challenges and requirements across different sectors.

These developments are transforming the industrial AI market by enhancing the capabilities and applications of AI technologies. They contribute to improved efficiency, flexibility, and cost-effectiveness in industrial operations.

Strategic Growth Opportunities for the Industrial AI Market

The industrial AI market presents several strategic growth opportunities across key applications, driven by technological advancements and evolving industry needs.

• Expansion in Predictive Maintenance: There is significant potential for growth in AI-driven predictive maintenance. By reducing equipment downtime and maintenance costs, this application offers substantial benefits to various industries, including manufacturing and energy.
• Growth in Smart Manufacturing: The rise of smart manufacturing technologies presents opportunities for AI integration. AI can enhance process automation, quality control, and real-time monitoring, driving efficiency and productivity in manufacturing operations.
• Advancement in Supply Chain Optimization: AI-driven supply chain optimization is a key growth area. AI can improve demand forecasting, inventory management, and logistics, leading to more efficient and responsive supply chains.
• Development of AI-Powered Robotics: The application of AI in robotics for tasks such as assembly and inspection offers growth opportunities. AI-powered robots can increase precision, flexibility, and efficiency in industrial processes.
• Enhancement of Process Optimization: AI solutions for process optimization are gaining traction. By analyzing large volumes of data, AI can identify inefficiencies and recommend improvements, leading to more effective and streamlined operations.

These strategic growth opportunities highlight the potential for industrial AI to drive innovation and efficiency across various applications. By focusing on predictive maintenance, smart manufacturing, supply chain optimization, robotics, and process optimization, companies can capitalize on emerging market trends and needs.

Industrial AI Market Driver and Challenges

The industrial AI market is influenced by various drivers and challenges, impacting its growth and development. These factors include technological, economic, and regulatory considerations.

The factors responsible for driving the industrial AI market include:

• Advancements in AI Technology: Continuous improvements in AI algorithms and machine learning models are driving the growth of industrial AI. These advancements enhance the capabilities and applications of AI in various industrial sectors.
• Increased Adoption of IoT: The integration of AI with IoT devices is a significant driver. IoT enables real-time data collection and analysis, which, when combined with AI, enhances monitoring, control, and optimization of industrial processes.
• Demand for Operational Efficiency: The need for increased operational efficiency is driving the adoption of industrial AI. AI solutions offer improved process optimization, predictive maintenance, and automation, leading to cost savings and higher productivity.
• Investment in R&D: Increased investment in research and development is fostering innovation in industrial AI. Funding and collaboration support the development of new technologies and applications, advancing the industry.
• Focus on Data-Driven Decision Making: The emphasis on data-driven decision-making is driving the growth of industrial AI. AI provides valuable insights from data analysis, enabling more informed and strategic decisions in industrial operations.

Challenges in the industrial AI market are:

• Integration Complexity: Integrating AI with existing industrial systems can be complex and challenging. Ensuring compatibility and seamless operation requires significant effort and expertise.
• High Implementation Costs: The cost of implementing AI solutions can be high. This includes expenses related to technology acquisition, system integration, and training, which can be a barrier for some organizations.
• Data Privacy and Security Concerns: Concerns about data privacy and security are significant challenges. Ensuring that AI systems comply with regulations and protect sensitive information is critical for gaining trust and maintaining security.

The drivers and challenges impacting the industrial AI market highlight the need for ongoing innovation and adaptation. Addressing these factors effectively will be key to leveraging growth opportunities and overcoming market obstacles.

List of Industrial AI Companies

Companies in the market compete based on 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, industrial AI companies cater to increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the industrial AI companies profiled in this report include-

• Siemens
• IBM
• Microsoft
• Cisco Systems
• General Electric Company
• Rockwell Automation

Industrial AI by Segment

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

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

• Software
• Hardware

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

• Glass Manufacturing
• Semiconductor Manufacturing
• Automotive
• Machinery
• Chemical
• Oil & Gas
• Packaging
• Others

Industrial AI 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 Industrial AI Market

Major players in the market are expanding their operations and forming strategic partnerships to strengthen their positions. The image below highlights recent developments by major industrial AI producers in key regions: the USA, China, India, Japan, and Germany.

• United States: In the U.S., industrial AI is seeing increased adoption in predictive maintenance and supply chain optimization. Companies like GE and Siemens are integrating AI into their industrial systems to enhance operational efficiency and reduce downtime.
• China: China is focusing on AI-driven automation and robotics in manufacturing. Major players like Huawei and Alibaba are investing in AI technologies to improve production processes and boost industrial capabilities, supporting the country's "Made in China 2025" initiative.
• Germany: Germany is leveraging AI for Industry 4.0 initiatives, focusing on smart factories and advanced manufacturing. German firms are deploying AI for real-time process monitoring and quality control, aiming to enhance precision and reduce production costs.
• India: In India, industrial AI is being adopted to improve manufacturing efficiency and resource management. Startups and established companies are using AI to optimize supply chains and enhance production capabilities, supporting the country's industrial growth.
• Japan: Japan is advancing AI in robotics and automation, particularly for precision manufacturing and electronics. Japanese companies are integrating AI into production lines to enhance automation and increase manufacturing accuracy and speed.

Features of the Global Industrial AI Market

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

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

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

Regional Analysis: Industrial AI 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 industrial AI market.

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

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

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This report answers the following 11 key questions:

• Q.1. What are some of the most promising, high-growth opportunities for the industrial AI market by type (software and hardware), application (glass manufacturing, semiconductor manufacturing, automotive, machinery, chemical, oil & gas, packaging, 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 Industrial AI 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 Industrial AI Market Trends (2019-2024) and Forecast (2025-2031)
• 3.3: Global Industrial AI Market by Type
  • 3.3.1: Software
  • 3.3.2: Hardware
• 3.4: Global Industrial AI Market by Application
  • 3.4.1: Glass Manufacturing
  • 3.4.2: Semiconductor Manufacturing
  • 3.4.3: Automotive
  • 3.4.4: Machinery
  • 3.4.5: Chemical
  • 3.4.6: Oil & Gas
  • 3.4.7: Packaging
  • 3.4.8: Others

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

• 4.1: Global Industrial AI Market by Region
• 4.2: North American Industrial AI Market
  • 4.2.1: North American Industrial AI Market by Type: Software and Hardware
  • 4.2.2: North American Industrial AI Market by Application: Glass Manufacturing, Semiconductor Manufacturing, Automotive, Machinery, Chemical, Oil & Gas, Packaging, and Others
• 4.3: European Industrial AI Market
  • 4.3.1: European Industrial AI Market by Type: Software and Hardware
  • 4.3.2: European Industrial AI Market by Application: Glass Manufacturing, Semiconductor Manufacturing, Automotive, Machinery, Chemical, Oil & Gas, Packaging, and Others
• 4.4: APAC Industrial AI Market
  • 4.4.1: APAC Industrial AI Market by Type: Software and Hardware
  • 4.4.2: APAC Industrial AI Market by Application: Glass Manufacturing, Semiconductor Manufacturing, Automotive, Machinery, Chemical, Oil & Gas, Packaging, and Others
• 4.5: ROW Industrial AI Market
  • 4.5.1: ROW Industrial AI Market by Type: Software and Hardware
  • 4.5.2: ROW Industrial AI Market by Application: Glass Manufacturing, Semiconductor Manufacturing, Automotive, Machinery, Chemical, Oil & Gas, Packaging, 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 Industrial AI Market by Type
  • 6.1.2: Growth Opportunities for the Global Industrial AI Market by Application
  • 6.1.3: Growth Opportunities for the Global Industrial AI Market by Region
• 6.2: Emerging Trends in the Global Industrial AI Market
• 6.3: Strategic Analysis
  • 6.3.1: New Product Development
  • 6.3.2: Capacity Expansion of the Global Industrial AI Market
  • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global Industrial AI Market
  • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

• 7.1: Siemens
• 7.2: IBM
• 7.3: Microsoft
• 7.4: Cisco Systems
• 7.5: General Electric Company
• 7.6: Rockwell Automation