製造業における人工知能市場：オファリング別、技術別、エンドユーザー産業別、地域別、2024年～2031年

製造業における人工知能市場の評価、2024年～2031年

AIは製品開発サイクルを高速化し、製造業のイノベーションを促進しています。そのため、製品開発とイノベーションの加速により、市場規模は2024年に23億1,000万米ドルを突破し、2031年には359億米ドルの評価額に達します。

AIは、より正確で効率的な欠陥検出を可能にすることで、製造業の品質管理に革命をもたらしています。したがって、品質管理プロセスの強化により、市場は2024年から2031年にかけてCAGR 47.80％で成長します。

製造業の人工知能市場定義/概要

人工知能（AI）は、高度なアルゴリズムと機械学習を活用して効率、生産、意思決定を強化することで、製造業を変革しています。ニューラル・ネットワーク、コンピュータ・ビジョン、ロボット工学などの技術は、予知保全、品質管理、サプライ・チェーンの最適化など、人間の知能を模倣したタスクを機械に実行させる。

製造業では、AIが機器の故障を事前に予測することでダウンタイムとコストを削減し、全体的な業務効率を向上させる。機械学習モデルは欠陥を検出して品質管理を確実にし、ロボットは正確さと一貫性が求められる精密な反復作業に導入されます。また、AIを活用したシステムは、需要予測、在庫管理、ロジスティクスの合理化によってサプライチェーン管理を最適化し、無駄の削減と効率化を実現します。

AIが進化を続けるにつれ、人間の介入を最小限に抑えた、より自律的な工場の開発が推進されると思われます。モノのインターネット（IoT）の統合によって促進されるリアルタイムのデータ収集と分析により、製造業者はより柔軟で迅速な操業が可能になります。これはまた、俊敏な生産のための高度なカスタマイズをサポートし、企業が変化する市場の需要に迅速に適応することを可能にします。最終的に、AIは製造業における革新性、持続可能性、回復力を促進し、より効率的で適応性の高い生産システムにつながります。

製造業におけるAI技術の急速な導入は、製造市場における人工知能の成長をどのように加速させるのか？

機械学習、コンピュータビジョン、ビッグデータ分析などのAI技術は、製造業で急速に普及しています。これらの技術はリアルタイムのデータ処理と分析を提供し、より良い意思決定、最適化されたオペレーション、より高い製品品質をもたらします。マッキンゼー・世界・インスティテュートのレポートによると、AIは製造業とサプライチェーン・プランニングの分野で1兆2,000億米ドルから2兆米ドルの価値を生み出す可能性があるといいます。世界経済フォーラムは、2025年までに、人間、機械、アルゴリズムの分業により、9,700万人の新たな雇用が生まれる可能性があると予測しています。

AIを活用した予知保全は、製造業においてダウンタイムと保全コストを削減するために不可欠になりつつあります。米国エネルギー省の報告によると、予知保全によって保全コストを30％削減し、故障を70％なくし、ダウンタイムを40％削減できるといいます。米国品質学会の調査によると、品質管理にAIを導入することで、不良率を最大50％削減できるといいます。キャップジェミニ・リサーチ・インスティテュートによると、欧州の製造業の51％がAIを活用した品質管理ソリューションを導入しており、そのうち28％が生産性を30％向上させたと報告しています。

AIは予測精度と業務効率を向上させることで、サプライチェーン管理を変革しています。IBMの調査によると、サプライチェーンリーダーの85％が、今後3～5年の間にAIがサプライチェーンのパフォーマンスに大きな影響を及ぼすと考えています。ガートナーによると、2024年までにサプライチェーン組織の50％が、人工知能と高度な分析機能をサポートするアプリケーションに投資するといいます。PwCの調査によると、現在、製造業者の35％が製品の革新にAIを利用しており、さらに42％がまもなくAIを利用する予定だといいます。世界知的所有権機関（WIPO）によると、AI関連の特許出願は2010年から2020年にかけて400％以上増加しており、この分野における急速な技術革新がうかがえます。AIは、製造工程をよりエネルギー効率が高く、持続可能なものにする上で重要な役割を果たしています。米国エネルギー省の報告によると、AIを搭載したシステムは製造工場のエネルギー消費を最大20％削減できるといいます。

熟練人材の不足と初期投資・導入コストの高さが、製造市場における人工知能の成長をどのように阻害しているか？

大きな阻害要因は、AIと製造業の両方において必要な専門知識を持つ人材の不足です。このスキルギャップが、製造分野におけるAIの成長と実装を妨げています。世界経済フォーラムの「雇用の未来レポート2020」によると、テクノロジーの導入が進むにつれて、2025年までに全従業員の50％が再教育を必要とし、データアナリストや科学者、AIや機械学習のスペシャリストが新たな職種の上位に挙げられています。AI技術と既存の製造システムへの統合に伴う多額の初期費用は、特に中小企業（SME）にとって大きな障壁となります。情報技術革新財団（ITIF）の報告書によると、産業用ロボットの平均コストは約2万7,000米ドルで、さらにソフトウェア、統合、メンテナンスのコストがかかります。

AIシステムはデータに大きく依存するため、データ・セキュリティ、プライバシー、知的財産権保護に関する懸念が、一部のメーカーがAI技術を全面的に採用することを抑制しています。米国国立標準技術研究所（NIST）の報告によると、製造業はサイバー攻撃の標的として2番目に多い産業であり、全インシデントの23.2％を占めています。

目次

第1章 イントロダクション

• 市場の定義
• 市場セグメンテーション
• 調査手法

第2章 エグゼクティブサマリー

• 主な調査結果
• 市場概要
• 市場ハイライト

第3章 市場概要

• 市場規模と成長の可能性
• 市場動向
• 市場促進要因
• 市場抑制要因
• 市場機会
• ポーターのファイブフォース分析

第4章 製造業における人工知能市場：オファリング別

• ハードウェア
• ソフトウェア
• サービス

第5章 製造業における人工知能市場：技術別

• 機械学習
• コンピュータビジョン
• 自然言語処理（NLP）
• コンテキスト認識

第6章 製造業における人工知能市場：産業別

• 自動車
• 医療機器
• 半導体・エレクトロニクス
• エネルギー・電力
• 重金属・機械製造
• 飲食品
• その他

第7章 地域分析

• 北米
• 米国
• カナダ
• メキシコ
• 欧州
• 英国
• ドイツ
• フランス
• イタリア
• アジア太平洋
• 中国
• 日本
• インド
• オーストラリア
• ラテンアメリカ
• ブラジル
• アルゼンチン
• チリ
• 中東・アフリカ
• 南アフリカ
• サウジアラビア
• アラブ首長国連邦

第8章 市場力学

• 市場促進要因
• 市場抑制要因
• 市場機会
• COVID-19の市場への影響

第9章 競合情勢

• 主要企業
• 市場シェア分析

第10章 企業プロファイル

• Siemens
• IBM
• Intel Corporation
• NVIDIA Corporation
• General Electric Company
• Microsoft Corporation
• Google
• Amazon Web Services
• Rockwell Automation
• Honeywell
• SAP

第11章 市場の展望と機会

• 新興技術
• 今後の市場動向
• 投資機会

第12章 付録

• 略語リスト
• 出典と参考文献

Artificial Intelligence in Manufacturing Market Valuation - 2024-2031

AI is speeding up product development cycles and fostering innovation in manufacturing. Thus, the acceleration of product development and innovation surged the growth of market size surpassing USD 2.31 Billion in 2024 to reach the valuation of USD 35.9 Billion by 2031.

AI is revolutionizing quality control in manufacturing by enabling more accurate and efficient defect detection. Thus, the enhancement of quality control processes enables the market to grow at a CAGR of 47.80% from 2024 to 2031.

Artificial Intelligence in Manufacturing Market: Definition/ Overview

Artificial Intelligence (AI) is transforming manufacturing by leveraging advanced algorithms and machine learning to enhance efficiency, production, and decision-making. Technologies such as neural networks, computer vision, and robotics empower machines to perform tasks that mimic human intelligence, including predictive maintenance, quality control, and supply chain optimization.

In manufacturing, AI helps reduce downtime and costs by predicting equipment failures before they occur, improving overall operational efficiency. Machine learning models can detect defects and ensure quality control, while robots are deployed for precise, repetitive tasks that require accuracy and consistency. AI-driven systems also optimize supply chain management by forecasting demand, managing inventory, and streamlining logistics, leading to reduced waste and enhanced efficiency.

As AI continues to evolve, it will drive the development of more autonomous factories with minimal human intervention. Real-time data collection and analysis, facilitated by Internet of Things (IoT) integration, will enable manufacturers to operate more flexibly and responsively. This will also support advanced customization for agile production, allowing companies to quickly adapt to changing market demands. Ultimately, AI will foster innovation, sustainability, and resilience in manufacturing, leading to more efficient, adaptable production systems.

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How does the Rapid Adoption of AI Technologies in Manufacturing Surge the Growth of Artificial Intelligence in the Manufacturing Market?

AI technologies such as machine learning, computer vision, and big data analytics are rapidly gaining traction in manufacturing. These technologies offer real-time data processing and analysis, resulting in better decision-making, optimized operations, and higher product quality. According to a McKinsey Global Institute report, AI has the potential to create between USD 1.2 Trillion and USD 2 Trillion in value in the manufacturing and supply chain planning sectors. The World Economic Forum predicts that by 2025, 97 million new jobs may emerge in the division of labor between humans, machines, and algorithms.

AI-powered predictive maintenance is becoming crucial in manufacturing to reduce downtime and maintenance costs. The U.S. Department of Energy reports that predictive maintenance can reduce maintenance costs by 30%, eliminate breakdowns by 70%, and reduce downtime by 40%. A study by the American Society for Quality found that implementing AI in quality control can reduce defect rates by up to 50%. According to Capgemini Research Institute, 51% of European manufacturers are implementing AI-powered quality control solutions, with 28% of them reporting a 30% increase in productivity.

AI is transforming supply chain management by improving forecasting accuracy and operational efficiency. A study by IBM found that 85% of supply chain leaders believe AI will significantly impact their supply chain performance in the next three to five years. According to Gartner, by 2024, 50% of supply chain organizations will invest in applications that support artificial intelligence and advanced analytics capabilities. A PwC study found that 35% of manufacturers are currently using AI to innovate products, with an additional 42% planning to do so shortly. According to the World Intellectual Property Organization (WIPO), AI-related patent applications increased by more than 400% from 2010 to 2020, indicating rapid innovation in the field. AI is playing a crucial role in making manufacturing processes more energy-efficient and sustainable. The U.S. Department of Energy reports that AI-powered systems can reduce energy consumption in manufacturing plants by up to 20%.

How the Lack of Skilled Personnel and High Initial Investment and Implementation Costs Impede the Growth of Artificial Intelligence in the Manufacturing Market?

The significant restraint is the shortage of personnel with the necessary expertise in both AI and manufacturing. This skills gap is hampering the growth and implementation of AI in the manufacturing sector. The World Economic Forum's "Future of Jobs Report 2020" found that 50% of all employees will need reskilling by 2025 as the adoption of technology increases, with data analysts and scientists, AI and machine learning specialists among the top emerging jobs. The substantial upfront costs associated with AI technologies and their integration into existing manufacturing systems pose a significant barrier, especially for small and medium-sized enterprises (SMEs). A report by the Information Technology and Innovation Foundation (ITIF) states that the average cost of an industrial robot is around $27,000, with additional costs for software, integration, and maintenance.

As AI systems rely heavily on data, concerns about data security, privacy, and intellectual property protection are restraining some manufacturers from fully embracing AI technologies. The U.S. National Institute of Standards and Technology (NIST) reported that manufacturing is the second most targeted industry for cyber-attacks, accounting for 23.2% of all incidents.

Category-Wise Acumens

How does the Increasing Popularity for Advanced Automation Surge the Growth of Computer Vision Segment?

The computer vision segment is poised for significant growth in artificial intelligence in the manufacturing market, driven by its ability to provide accurate and actionable insights for various manufacturing processes. The increasing demand for advanced automation and efficiency in manufacturing. Computer vision's integration with robotics plays a crucial role in process optimization, as it enables robots to "see" and interpret their environment, making production more efficient and precise.

In addition, the growing adoption of robotics across multiple industries, including automotive, electronics, and consumer goods, has further fueled the application of computer vision for process improvement and quality control. As industries continue to embrace automation and intelligent systems, computer vision is expected to play an increasingly vital role in driving efficiency, safety, and optimization within manufacturing environments.

How the Increasing Prevalence of Diseases and Growing Advanced Medical Equipment Foster the Growth of Medical Devices Segment?

The medical devices segment is emerging as a dominant segment in the artificial intelligence (AI) manufacturing market, driven by the rising prevalence of diseases globally and the growing need for advanced medical equipment. As healthcare systems expand and modernize, there is increasing demand for innovative, efficient, and reliable medical devices that can enhance patient outcomes and streamline medical processes. AI plays a pivotal role in this transformation, offering opportunities to manufacture cutting-edge devices that disrupt traditional methods and improve diagnostic and treatment capabilities.

AI integration in the manufacturing of medical equipment allows for the development of smarter, more precise devices that can operate with greater efficiency. From surgical robots to AI-driven diagnostic tools, these advancements are enabling manufacturers to create equipment that delivers real-time insights and enhances patient care. One notable example is Australia-based EMVision, which has harnessed NVIDIA's AI platform and DGX systems to develop a lightweight, portable brain scanner. This AI-powered device can diagnose brain strokes within minutes, revolutionizing stroke care by providing quick, accurate diagnoses in emergencies.

Country/Region-wise Acumens

How the Strong Presence of Tech Giants and AI Startups Foster the Growth of Artificial Intelligence in Manufacturing Market in North America?

North America substantially dominates artificial intelligence in the manufacturing market owing to the strong presence of tech giants and AI startups. North America, particularly the United States, is home to many of the world's leading tech companies and AI startups, driving innovation and adoption in AI manufacturing solutions. According to the National Science Foundation, the United States leads the world in AI research output, producing 27% of all AI research papers globally in 2020. A report by the Center for Data Innovation shows that the US has 1,393 AI companies, compared to 736 in China and 521 in the EU.

Both the U.S. and Canadian governments are making significant investments in AI research and development, as well as in modernizing the manufacturing sector. The U.S. National Science Foundation (NSF) and the National Institute of Standards and Technology (NIST) announced over USD 201 Million in funding for artificial intelligence research institutes in 2021.

According to the U.S. Government Accountability Office, federal agencies obligated USD 1.5 Billion in AI-related research and development spending in fiscal year 2020. North American manufacturers are increasingly embracing Industry 4.0 technologies, including AI, to improve efficiency and competitiveness. A survey by the National Association of Manufacturers found that 77% of manufacturers say increasing productivity is the top reason to adopt new technologies, including AI.

How the Rapid Digitization and Industry 4.0 Adoption Accelerates the Growth of Artificial Intelligence in the Manufacturing Market in Asia Pacific?

Asia Pacific is anticipated to witness the fastest growth in artificial intelligence in the manufacturing market. The Asia Pacific region is experiencing a swift transition towards digitization and Industry 4.0, driving the adoption of AI in manufacturing. According to a report by McKinsey, Asia could account for 40% of the world's total Industry 4.0 market by 2030. The Asian Development Bank Institute states that the digital economy in Asia Pacific is expected to reach USD 1.7 Trillion by 2025, up from USD 1.35 Trillion in 2019. Many countries in the Asia Pacific region have launched national AI strategies and are heavily investing in smart manufacturing initiatives. China's State Council announced plans to build a USD 150 Billion AI industry by 2030. According to the International Federation of Robotics, five major Asian markets China, Japan, South Korea, Taiwan, and India accounted for 74% of global industrial robot installations in 2020.

The Asia Pacific region's significant manufacturing base, coupled with rising labor costs, is driving the adoption of AI to improve efficiency and reduce expenses. The United Nations Conference on Trade and Development (UNCTAD) reports that Asia's share of global manufacturing output increased from 31.6% in 1990 to 51.1% in 2018. According to the International Labour Organization, average wages in Asia and the Pacific grew by 3.5% in 2019, the highest among all regions globally.

Competitive Landscape

The competitive landscape of the Artificial Intelligence in Manufacturing Market is dynamic and evolving, with a growing number of players vying for market share. The ability to develop and deliver innovative AI solutions that address the specific needs of manufacturing customers will be critical for success in this competitive market.

The organizations are focusing on innovating their product line to serve the vast population in diverse regions. Some of the prominent players operating in the artificial intelligence in the manufacturing market include:

• Siemens
• IBM
• Intel Corporation
• NVIDIA Corporation
• General Electric Company
• Microsoft Corporation
• Google
• Amazon Web Services
• Rockwell Automation

Latest Developments:

• In October 2023, Google Cloud announced the launch of dedicated generative AI solutions for the healthcare and manufacturing industries, to enhance efficiency and promote digital transformation. This technique marked a significant advancement in employing AI to achieve industry-specific solutions.
• In April 2023, Siemens announced the collaboration with Microsoft to enhance industrial AI and transform product lifecycle management. The integration of Siemens Teamcenter software with Microsoft Teams and Azure OpenAI Service's language models is intended to increase creativity and effectiveness.

TABLE OF CONTENTS

1. Introduction

• Market Definition
• Market Segmentation
• Research Methodology

2. Executive Summary

• Key Findings
• Market Overview
• Market Highlights

3. Market Overview

• Market Size and Growth Potential
• Market Trends
• Market Drivers
• Market Restraints
• Market Opportunities
• Porter's Five Forces Analysis

4. Artificial Intelligence In Manufacturing Market, By Offering

• Hardware
• Software
• Services

5. Artificial Intelligence In Manufacturing Market, By Technology

• Machine Learning
• Computer vision
• Natural Language Processing (NLP)
• Context Awareness

6. Artificial Intelligence In Manufacturing Market, By Industry

• Automotive
• Medical Devices
• Semiconductor & Electronics
• Energy & Power
• Heavy Metal & Machine Manufacturing
• Food & Beverages
• Others

7. Regional Analysis

• North America
• United States
• Canada
• Mexico
• Europe
• United Kingdom
• Germany
• France
• Italy
• Asia-Pacific
• China
• Japan
• India
• Australia
• Latin America
• Brazil
• Argentina
• Chile
• Middle East and Africa
• South Africa
• Saudi Arabia
• UAE

8. Market Dynamics

• Market Drivers
• Market Restraints
• Market Opportunities
• Impact of COVID-19 on the Market

9. Competitive Landscape

• Key Players
• Market Share Analysis

10. Company Profiles

• Siemens
• IBM
• Intel Corporation
• NVIDIA Corporation
• General Electric Company
• Microsoft Corporation
• Google
• Amazon Web Services
• Rockwell Automation
• Honeywell
• SAP

11. Market Outlook and Opportunities

• Emerging Technologies
• Future Market Trends
• Investment Opportunities

12. Appendix

• List of Abbreviations
• Sources and References