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人工智能

市场调查报告书

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1684785

製造业人工智慧市场机会、成长动力、产业趋势分析及 2025 - 2034 年预测

AI in Manufacturing Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025 - 2034

出版日期: 2025年01月16日 | 出版商:

Global Market Insights Inc. | 英文 180 Pages | 商品交期: 2-3个工作天内

价格

简介目录

2024 年全球製造业人工智慧市场价值为 42 亿美元，预计 2025 年至 2034 年期间的复合年增长率为 31.2%。製造业对精简外包解决方案的需求日益增加，推动了人工智慧的采用。企业正在整合人工智慧，透过自动化生产控制、检查和库存管理等流程来提高生产效率、降低成本并扩大营运规模。人工智慧解决方案的日益普及，使从大型製造商到中小型企业等各种规模的企业受益。世界各国政府都优先考虑人工智慧的研究和开发，并提供资助计画、税收减免和监管支援等财政激励措施来促进人工智慧的实施。这些措施旨在推动各行业的创新、提高生产力并降低成本。

市场根据组件分为硬体、软体和服务。 2024 年，硬体领域的市占率超过 55%，预计到 2034 年将超过 320 亿美元。对先进计算硬体的不断增长的需求推动了这一增长，因为製造业中的人工智慧应用（例如机器人、预测性维护和品质控制）需要高效能组件进行即时资料处理。机器学习和深度学习演算法也在推动对强大硬体的需求，以提高人工智慧的效能。资料处理能力的快速进步实现了更高程度的自动化、更强的生产力和更好的决策。

市场范围
起始年份	2024
预测年份	2025-2034
起始值	42亿美元
预测值	607亿美元
复合年增长率	31.2％

根据部署模式，市场分为内部部署和云端解决方案。 2024年，云端运算部分约占市场的43%。随着各行各业的公司纷纷拥抱数位转型，对基于云端的人工智慧解决方案的需求不断上升，从而增强了製造业的竞争力。云端运算提供灵活性和可扩展性，降低营运成本并简化流程。此外，远端实施可以增强资料储存和处理，这对于依赖大量资料集的人工智慧应用至关重要。基于云端的解决方案还支援製造商、供应商和客户之间的即时协作，从而改善决策并加快产品上市时间。

市场也按技术细分，包括机器学习、电脑视觉、自然语言处理和情境感知计算。机器学习引领市场，预计到 2034 年将创造约 190 亿美元的市场价值。这一增长归因于机器学习在智慧自动化和数据驱动决策中的应用日益增加。人工智慧驱动的品质控制解决方案提高了产品检测准确性，最大限度地减少了生产损失。物联网技术的兴起也推动了製造业机器学习的应用，物联网技术可以收集、分析和处理资料以优化营运。

市场根据应用进一步划分，包括品质管理、预测性维护、库存管理、能源管理、工业机器人等。预测性维护在 2024 年占据最大份额，约 25%。人工智慧预测性维护解决方案使用机器学习演算法即时监控和评估设备效能，帮助企业预防故障、降低维护成本并最大限度地减少生产中断。对更高生产力和减少停机时间的不断增长的需求推动了对这些系统的需求。

2024年美国引领北美製造业人工智慧市场，占有约75%的区域份额。中国政府对人工智慧驱动的智慧製造的大力支持是市场成长的关键因素。政策制定者优先考虑自动化和先进技术，以增强国家製造业的竞争力。此外，对加强供应链弹性和优化生产效率的关注进一步推动了产业对人工智慧的应用。

产业生态系统分析
- 硬体提供者
- 软体供应商
- 服务提供者
- 技术提供者
- 最终客户
供应商概况
利润率分析
技术与创新格局
专利分析
重要新闻及倡议
监管格局
製造业人工智慧的演变
使用案例
衝击力
- 成长动力
  - 自动化需求日益增长
  - 机器学习技术的快速发展
  - 采用人工智慧预测性维护解决方案
  - 增加工业自动化的投资
- 产业陷阱与挑战
  - 资料隐私问题
  - 缺乏熟练的专业人员
成长潜力分析
波特的分析
PESTEL 分析

第四章：竞争格局

介绍
公司市占率分析
竞争定位矩阵
战略展望矩阵

第五章：市场估计与预测：按组件，2021 - 2034 年

主要趋势
硬体
- 处理器
  - 中央处理器 (CPU)
  - 图形处理单元 (GPU)
  - 现场可程式闸阵列 (FPGA)
  - 专用积体电路 (ASIC)
  - 张量处理单元 (TPU)
- 记忆体和储存
- 网路硬体
软体
服务
- 专业服务
- 託管服务

第六章：市场估计与预测：依部署模型，2021 - 2034 年

主要趋势
本地
云

第 7 章：市场估计与预测：按技术，2021 - 2034 年

主要趋势
机器学习
电脑视觉
自然语言处理
情境感知计算

第 8 章：市场估计与预测：按应用，2021 - 2034 年

主要趋势
品质管理
预测性维护
库存管理
能源管理
工业机器人
其他的

第 9 章：市场估计与预测：按最终用途，2021 - 2034 年

主要趋势
汽车
电子产品
药品
重型机械
食品和饮料
航太和国防
其他的

第 10 章：市场估计与预测：按地区，2021 - 2034 年

北美洲
- 我们
- 加拿大
欧洲
- 英国
- 德国
- 法国
- 义大利
- 西班牙
- 俄罗斯
- 北欧
亚太地区
- 中国
- 印度
- 日本
- 澳洲
- 韩国
- 东南亚
拉丁美洲
- 巴西
- 墨西哥
- 阿根廷
中东及非洲
- 阿联酋
- 南非
- 沙乌地阿拉伯

第 11 章：公司简介

ABB
AWS
Cognex
Dassault
Fanuc
GE
Google
Honeywell
IBM
Intel
Microsoft
NVIDIA
Oracle
PTC
Qualcomm
Rockwell
SAP
Schneider
Siemens
Xilinx

简介目录

Product Code: 3124

The Global AI In Manufacturing Market was valued at USD 4.2 billion in 2024 and is projected to grow at a CAGR of 31.2% between 2025 and 2034. The increasing need for streamlined outsourcing solutions within the manufacturing sector is driving AI adoption. Companies are integrating AI to enhance production efficiency, cut costs, and scale operations by automating processes such as production control, inspection, and inventory management. The rising availability of AI-powered solutions is benefiting businesses of all sizes, from large manufacturers to small and medium enterprises. Governments worldwide are prioritizing AI research and development, offering financial incentives such as funding programs, tax breaks, and regulatory support to boost AI implementation. These initiatives are designed to drive innovation, improve productivity, and reduce costs across various industries.

The market is segmented based on components into hardware, software, and services. In 2024, the hardware segment held a market share exceeding 55% and is expected to surpass USD 32 billion by 2034. The rising demand for advanced computing hardware is fueling this growth, as AI applications in manufacturing, such as robotics, predictive maintenance, and quality control, require high-performance components for real-time data processing. Machine learning and deep learning algorithms are also driving the need for powerful hardware to improve AI performance. Rapid advancements in data processing capabilities are enabling greater automation, enhanced productivity, and better decision-making.

Market Scope
Start Year	2024
Forecast Year	2025-2034
Start Value	$4.2 Billion
Forecast Value	$60.7 Billion
CAGR	31.2%

By deployment model, the market is categorized into on-premises and cloud solutions. In 2024, the cloud segment accounted for about 43% of the market. As companies across industries embrace digital transformation, the demand for cloud-based AI solutions is rising, enhancing competitiveness in manufacturing. Cloud computing offers flexibility and scalability, reducing operational costs and streamlining processes. Additionally, remote implementation allows for enhanced data storage and processing, which is critical for AI applications that rely on extensive datasets. Cloud-based solutions also enable real-time collaboration between manufacturers, suppliers, and customers, improving decision-making and accelerating time to market.

The market is also segmented by technology, including machine learning, computer vision, natural language processing, and context-aware computing. Machine learning led the market and is projected to generate around USD 19 billion by 2034. This growth is attributed to the increasing use of machine learning for intelligent automation and data-driven decision-making. AI-driven quality control solutions improve product inspection accuracy, minimizing production losses. Machine learning adoption in manufacturing is also being propelled by the rise of IoT technologies, which collect, analyze, and process data for optimized operations.

The market is further divided by application, including quality management, predictive maintenance, inventory management, energy management, industrial robotics, and others. Predictive maintenance held the largest share in 2024 at approximately 25%. AI-powered predictive maintenance solutions use machine learning algorithms to monitor and assess equipment performance in real-time, helping businesses prevent failures, reduce maintenance costs, and minimize production disruptions. The increasing need for higher productivity and reduced downtime is driving demand for these systems.

The United States led the North America AI in manufacturing market in 2024, holding about 75% of the regional share. The country's strong government support for AI-driven smart manufacturing is a key factor in market growth. Policymakers are prioritizing automation and advanced technologies to enhance the competitiveness of the nation's manufacturing sector. In addition, a focus on strengthening supply chain resilience and optimizing production efficiency is further driving AI adoption in the industry.

Chapter 1 Methodology & Scope

1.1 Research design
- 1.1.1 Research approach
- 1.1.2 Data collection methods
1.2 Base estimates & calculations
- 1.2.1 Base year calculation
- 1.2.2 Key trends for market estimation
1.3 Forecast model
1.4 Primary research and validation
- 1.4.1 Primary sources
- 1.4.2 Data mining sources
1.5 Market scope & definition

Chapter 2 Executive Summary

2.1 Industry 360⁰ synopsis, 2021 - 2034

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
- 3.1.1 Hardware providers
- 3.1.2 Software providers
- 3.1.3 Service providers
- 3.1.4 Technology providers
- 3.1.5 End customers
3.2 Supplier landscape
3.3 Profit margin analysis
3.4 Technology & innovation landscape
3.5 Patent analysis
3.6 Key news & initiatives
3.7 Regulatory landscape
3.8 Evolution of AI in manufacturing
3.9 Use cases
3.10 Impact forces
- 3.10.1 Growth drivers
  - 3.10.1.1 The growing need for automation
  - 3.10.1.2 Rapid developments in machine learning technologies
  - 3.10.1.3 Adoption of AI-powered predictive maintenance solutions
  - 3.10.1.4 Increasing investment in industrial automation
- 3.10.2 Industry pitfalls & challenges
  - 3.10.2.1 Data privacy concerns
  - 3.10.2.2 Lack of skilled professionals
3.11 Growth potential analysis
3.12 Porter’s analysis
3.13 PESTEL analysis

Chapter 4 Competitive Landscape, 2024

4.1 Introduction
4.2 Company market share analysis
4.3 Competitive positioning matrix
4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Component, 2021 - 2034 ($Bn)

5.1 Key trends
5.2 Hardware
- 5.2.1 Processors
  - 5.2.1.1 Central Processing Units (CPU)
  - 5.2.1.2 Graphics Processing Units (GPU)
  - 5.2.1.3 Field Programmable Gate Arrays (FPGA)
  - 5.2.1.4 Application Specific Integrated Circuits (ASIC)
  - 5.2.1.5 Tensor Processing Units (TPU)
- 5.2.2 Memory & storage
- 5.2.3 Networking hardware
5.3 Software
5.4 Services
- 5.4.1 Professional service
- 5.4.2 Managed service

Chapter 6 Market Estimates & Forecast, By Deployment Model, 2021 - 2034 ($Bn)

6.1 Key trends
6.2 On-premise
6.3 Cloud

Chapter 7 Market Estimates & Forecast, By Technology, 2021 - 2034 ($Bn)

7.1 Key trends
7.2 Machine learning
7.3 Computer vision
7.4 Natural language processing
7.5 Context-aware computing

Chapter 8 Market Estimates & Forecast, By Application, 2021 - 2034 ($Bn)

8.1 Key trends
8.2 Quality management
8.3 Predictive maintenance
8.4 Inventory management
8.5 Energy management
8.6 Industrial robotics
8.7 Others

Chapter 9 Market Estimates & Forecast, By End Use, 2021 - 2034 ($Bn)

9.1 Key trends
9.2 Automotive
9.3 Electronics
9.4 Pharmaceuticals
9.5 Heavy machinery
9.6 Food & beverage
9.7 Aerospace & defense
9.8 Others

Chapter 10 Market Estimates & Forecast, By Region, 2021 - 2034 ($Bn)

10.1 North America
- 10.1.1 U.S.
- 10.1.2 Canada
10.2 Europe
- 10.2.1 UK
- 10.2.2 Germany
- 10.2.3 France
- 10.2.4 Italy
- 10.2.5 Spain
- 10.2.6 Russia
- 10.2.7 Nordics
10.3 Asia Pacific
- 10.3.1 China
- 10.3.2 India
- 10.3.3 Japan
- 10.3.4 Australia
- 10.3.5 South Korea
- 10.3.6 Southeast Asia
10.4 Latin America
- 10.4.1 Brazil
- 10.4.2 Mexico
- 10.4.3 Argentina
10.5 MEA
- 10.5.1 UAE
- 10.5.2 South Africa
- 10.5.3 Saudi Arabia