시장보고서
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1935491

제조용 인공지능(AI) 시장 규모, 점유율, 동향 및 성장 분석 보고서(2026-2034년)

Global Artificial Intelligence In Manufacturing Market Size, Share, Trends & Growth Analysis Report 2026-2034

발행일: | 리서치사: Value Market Research | 페이지 정보: 영문 162 Pages | 배송안내 : 1-2일 (영업일 기준)

    
    
    




※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.

제조용 인공지능(AI) 시장 규모는 2025년 79억 1,000만 달러에서 2026년부터 2034년까지 CAGR 45.87%로 성장하여 2034년에는 2,364억 1,000만 달러에 달할 것으로 예측됩니다.

제조에 인공지능(AI)의 통합은 업무 효율성과 제품 품질에 혁명을 가져올 것으로 예상됩니다. 산업 분야에서 스마트 기술 도입이 확대되고 있는 가운데, AI 기반 솔루션은 예지보전 강화, 공급망 최적화, 실시간 데이터 분석 촉진 등을 실현하고 있습니다. 이러한 변화는 운영 비용 절감뿐만 아니라 생산 일정 단축을 촉진하여 제조업체가 시장 요구에 신속하게 대응할 수 있게 해줍니다. 향후 AI 알고리즘의 고도화, 자동화 확대, 방대한 데이터세트의 분석 능력 향상으로 정보에 입각한 의사결정 프로세스가 촉진될 것으로 예상됩니다.

또한, 인더스트리 4.0의 도래는 AI와 사물인터넷(IoT)의 융합을 촉진하고, 생산성과 혁신성을 높이는 상호연결 시스템을 만들어내고 있습니다. AI 기능을 갖춘 스마트 팩토리는 설비 상태 모니터링, 고장 예측, 일상 업무 자동화를 실현하여 다운타임을 크게 줄일 수 있습니다. AI와 IoT의 시너지를 통해 소비자의 취향과 시장 환경의 변화에 전례 없는 속도와 정확도로 적응할 수 있는 보다 민첩한 제조 환경을 조성할 수 있습니다. 그 결과, 이러한 기술을 활용하는 조직은 경쟁 우위를 확보하고 빠르게 진화하는 시장에서 리더로 자리매김할 수 있을 것입니다.

향후 지속가능한 관행과 업무의 회복력 강화의 필요성으로 인해 제조업의 AI 수요는 급증할 것으로 예상됩니다. 제조업체들이 환경 규제와 지속가능성에 대한 소비자의 기대에 부응하기 위해 노력하는 가운데, AI는 자원 활용을 최적화하고 폐기물을 줄이는 데 중요한 역할을 할 수 있습니다. 생산 공정을 시뮬레이션하고 환경에 미치는 영향을 평가할 수 있는 능력을 통해 기업은 보다 지속가능한 선택을 할 수 있습니다. 따라서 제조업에서 AI의 미래는 단순한 효율화에 그치지 않습니다. 이는 혁신과 지속가능성을 촉진하고, 점점 더 복잡해지는 세계 환경에서 산업이 계속 번창할 수 있도록 보장합니다.

목차

제1장 소개

제2장 주요 요약

제3장 시장 변수, 동향, 프레임워크

제4장 세계의 제조용 인공지능(AI) 시장 : 제공별

제5장 세계의 제조용 인공지능(AI) 시장 : 기술별

제6장 세계의 제조용 인공지능(AI) 시장 : 용도별

제7장 세계의 제조용 인공지능(AI) 시장 : 산업별

제8장 세계의 제조용 인공지능(AI) 시장 : 지역별

제9장 경쟁 구도

제10장 기업 개요

KSM

The Artificial Intelligence In Manufacturing Market size is expected to reach USD 236.41 Billion in 2034 from USD 7.91 Billion (2025) growing at a CAGR of 45.87% during 2026-2034.

The integration of artificial intelligence (AI) within the manufacturing sector is poised to revolutionize operational efficiencies and product quality. As industries increasingly adopt smart technologies, AI-driven solutions are enhancing predictive maintenance, optimizing supply chains, and facilitating real-time data analytics. This shift not only reduces operational costs but also accelerates production timelines, enabling manufacturers to respond swiftly to market demands. The future landscape will likely see AI algorithms becoming more sophisticated, allowing for greater automation and the ability to analyze vast datasets, thus driving informed decision-making processes.

Moreover, the advent of Industry 4.0 is catalyzing the convergence of AI with the Internet of Things (IoT), creating interconnected systems that enhance productivity and innovation. Smart factories equipped with AI capabilities can monitor equipment health, predict failures, and automate routine tasks, leading to a significant reduction in downtime. This synergy between AI and IoT will foster a more agile manufacturing environment, where companies can adapt to changes in consumer preferences and market conditions with unprecedented speed and accuracy. As a result, organizations that leverage these technologies will gain a competitive edge, positioning themselves as leaders in a rapidly evolving marketplace.

Looking ahead, the demand for AI in manufacturing is expected to surge, driven by the need for sustainable practices and enhanced operational resilience. As manufacturers strive to meet environmental regulations and consumer expectations for sustainability, AI will play a crucial role in optimizing resource utilization and minimizing waste. The ability to simulate production processes and assess their environmental impact will empower companies to make more sustainable choices. Consequently, the future of AI in manufacturing is not merely about efficiency; it is about fostering innovation and sustainability, ensuring that the industry can thrive in an increasingly complex global landscape.

Our reports are meticulously crafted to provide clients with comprehensive and actionable insights into various industries and markets. Each report encompasses several critical components to ensure a thorough understanding of the market landscape:

Market Overview: A detailed introduction to the market, including definitions, classifications, and an overview of the industry's current state.

Market Dynamics: In-depth analysis of key drivers, restraints, opportunities, and challenges influencing market growth. This section examines factors such as technological advancements, regulatory changes, and emerging trends.

Segmentation Analysis: Breakdown of the market into distinct segments based on criteria like product type, application, end-user, and geography. This analysis highlights the performance and potential of each segment.

Competitive Landscape: Comprehensive assessment of major market players, including their market share, product portfolio, strategic initiatives, and financial performance. This section provides insights into the competitive dynamics and key strategies adopted by leading companies.

Market Forecast: Projections of market size and growth trends over a specified period, based on historical data and current market conditions. This includes quantitative analyses and graphical representations to illustrate future market trajectories.

Regional Analysis: Evaluation of market performance across different geographical regions, identifying key markets and regional trends. This helps in understanding regional market dynamics and opportunities.

Emerging Trends and Opportunities: Identification of current and emerging market trends, technological innovations, and potential areas for investment. This section offers insights into future market developments and growth prospects.

MARKET SEGMENTATION

By Offering

  • Hardware
  • Software
  • Services

By Technology

  • Machine Learning
  • Natural Language Processing
  • Aware Computing
  • Computer Vision

By Application

  • Predictive Maintenance and Machinery Inspection
  • Inventory Optimization
  • Production Planning
  • Field Services
  • Quality Control
  • Cybersecurity
  • Industrial Robots
  • Reclamation
  • BY Industry
  • Automotive
  • Energy and Power
  • Metals and Heavy Machinery
  • Semiconductor & Electronics
  • Food & Beverage
  • Pharma
  • Mining
  • Others

COMPANIES PROFILED

  • AIBrain Inc, Amazon Web Services, Aquant Inc, Cisco Systems Inc, General Electric Company, General Vision Inc, Google LLC Alphabet Inc, IBM Corporation, Intel Corporation, Micron Technology Inc, Microsoft Corporation, Mitsubishi Electric Corporation, NVIDIA Corporation, Oracle Corporation, Rockwell Automation Inc

We can customise the report as per your requriements

TABLE OF CONTENTS

Chapter 1. PREFACE

  • 1.1. Market Segmentation & Scope
  • 1.2. Market Definition
  • 1.3. Information Procurement
    • 1.3.1 Information Analysis
    • 1.3.2 Market Formulation & Data Visualization
    • 1.3.3 Data Validation & Publishing
  • 1.4. Research Scope and Assumptions
    • 1.4.1 List of Data Sources

Chapter 2. EXECUTIVE SUMMARY

  • 2.1. Market Snapshot
  • 2.2. Segmental Outlook
  • 2.3. Competitive Outlook

Chapter 3. MARKET VARIABLES, TRENDS, FRAMEWORK

  • 3.1. Market Lineage Outlook
  • 3.2. Penetration & Growth Prospect Mapping
  • 3.3. Value Chain Analysis
  • 3.4. Regulatory Framework
    • 3.4.1 Standards & Compliance
    • 3.4.2 Regulatory Impact Analysis
  • 3.5. Market Dynamics
    • 3.5.1 Market Drivers
    • 3.5.2 Market Restraints
    • 3.5.3 Market Opportunities
    • 3.5.4 Market Challenges
  • 3.6. Porter's Five Forces Analysis
  • 3.7. PESTLE Analysis

Chapter 4. GLOBAL ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET: BY OFFERING 2022-2034 (USD MN)

  • 4.1. Market Analysis, Insights and Forecast Offering
  • 4.2. Hardware Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 4.3. Software Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 4.4. Services Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 5. GLOBAL ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET: BY TECHNOLOGY 2022-2034 (USD MN)

  • 5.1. Market Analysis, Insights and Forecast Technology
  • 5.2. Machine Learning Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 5.3. Natural Language Processing Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 5.4. Aware Computing Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 5.5. Computer Vision Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 6. GLOBAL ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET: BY APPLICATION 2022-2034 (USD MN)

  • 6.1. Market Analysis, Insights and Forecast Application
  • 6.2. Predictive Maintenance and Machinery Inspection Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 6.3. Inventory Optimization Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 6.4. Production Planning Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 6.5. Field Services Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 6.6. Quality Control Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 6.7. Cybersecurity Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 6.8. Industrial Robots Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 6.9. Reclamation Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 7. GLOBAL ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET: BY INDUSTRY 2022-2034 (USD MN)

  • 7.1. Market Analysis, Insights and Forecast Industry
  • 7.2. Automotive Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 7.3. Energy and Power Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 7.4. Metals and Heavy Machinery Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 7.5. Semiconductor & Electronics Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 7.6. Food & Beverage Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 7.7. Pharma Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 7.8. Mining Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 7.9. Others Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 8. GLOBAL ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET: BY REGION 2022-2034(USD MN)

  • 8.1. Regional Outlook
  • 8.2. North America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
    • 8.2.1 By Offering
    • 8.2.2 By Technology
    • 8.2.3 By Application
    • 8.2.4 By Industry
    • 8.2.5 United States
    • 8.2.6 Canada
    • 8.2.7 Mexico
  • 8.3. Europe Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
    • 8.3.1 By Offering
    • 8.3.2 By Technology
    • 8.3.3 By Application
    • 8.3.4 By Industry
    • 8.3.5 United Kingdom
    • 8.3.6 France
    • 8.3.7 Germany
    • 8.3.8 Italy
    • 8.3.9 Russia
    • 8.3.10 Rest Of Europe
  • 8.4. Asia-Pacific Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
    • 8.4.1 By Offering
    • 8.4.2 By Technology
    • 8.4.3 By Application
    • 8.4.4 By Industry
    • 8.4.5 India
    • 8.4.6 Japan
    • 8.4.7 South Korea
    • 8.4.8 Australia
    • 8.4.9 South East Asia
    • 8.4.10 Rest Of Asia Pacific
  • 8.5. Latin America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
    • 8.5.1 By Offering
    • 8.5.2 By Technology
    • 8.5.3 By Application
    • 8.5.4 By Industry
    • 8.5.5 Brazil
    • 8.5.6 Argentina
    • 8.5.7 Peru
    • 8.5.8 Chile
    • 8.5.9 South East Asia
    • 8.5.10 Rest of Latin America
  • 8.6. Middle East & Africa Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
    • 8.6.1 By Offering
    • 8.6.2 By Technology
    • 8.6.3 By Application
    • 8.6.4 By Industry
    • 8.6.5 Saudi Arabia
    • 8.6.6 UAE
    • 8.6.7 Israel
    • 8.6.8 South Africa
    • 8.6.9 Rest of the Middle East And Africa

Chapter 9. COMPETITIVE LANDSCAPE

  • 9.1. Recent Developments
  • 9.2. Company Categorization
  • 9.3. Supply Chain & Channel Partners (based on availability)
  • 9.4. Market Share & Positioning Analysis (based on availability)
  • 9.5. Vendor Landscape (based on availability)
  • 9.6. Strategy Mapping

Chapter 10. COMPANY PROFILES OF GLOBAL ARTIFICIAL INTELLIGENCE IN MANUFACTURING INDUSTRY

  • 10.1. Top Companies Market Share Analysis
  • 10.2. Company Profiles
    • 10.2.1 AIBrain Inc
    • 10.2.2 Amazon Web Services
    • 10.2.3 Aquant Inc
    • 10.2.4 Cisco Systems Inc
    • 10.2.5 General Electric Company
    • 10.2.6 General Vision Inc
    • 10.2.7 Google LLC (Alphabet Inc.)
    • 10.2.8 IBM Corporation
    • 10.2.9 Intel Corporation
    • 10.2.10 Micron Technology Inc
    • 10.2.11 Microsoft Corporation
    • 10.2.12 Mitsubishi Electric Corporation
    • 10.2.13 NVIDIA Corporation
    • 10.2.14 Oracle Corporation
    • 10.2.15 Rockwell Automation Inc
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