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市場調査レポート
商品コード
1687611
製造業における人工知能(AI)市場規模、シェア、成長分析:提供別、技術別、用途別、業界別、地域別 - 産業予測 2025~2032年Artificial Intelligence (AI) in Manufacturing Market Size, Share, and Growth Analysis, By Offering (Hardware, Software), By Technology (Machine Learning, Natural Language Processing), By Application, By Industry, By Region - Industry Forecast 2025-2032 |
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製造業における人工知能(AI)市場規模、シェア、成長分析:提供別、技術別、用途別、業界別、地域別 - 産業予測 2025~2032年 |
出版日: 2025年03月19日
発行: SkyQuest
ページ情報: 英文 197 Pages
納期: 3~5営業日
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製造業における人工知能(AI) 2023年の市場規模は162億米ドルで、予測期間(2025-2032年)のCAGRは45.6%で、2024年の235億9,000万米ドルから2032年には4,764億米ドルまで成長する見通しです。
2023年10月現在、製造分野では、アナリティクス、拡張知能、バーチャルリアリティ、スマートパッケージング、積層造形などの先進技術に牽引され、人工知能(AI)の導入が大幅に急増しています。柔軟性と持続可能なソリューションへの需要の高まりが、この成長において極めて重要です。さらに、自動化とビッグデータ統合への依存の高まりが市場機会を拡大しています。マシンビジョンカメラはますます普及し、機械追跡、物流、フィールドサービス、品質管理などのアプリケーションを強化しています。この情勢における注目すべき開発は、Databricksが2023年4月に製造業者向けにDatabricks Lakehouseを立ち上げたことです。このDatabricks Lakehouseは、DuPontのような業界リーダーによって成功裏に採用された、事前に開発されたAIソリューションを特徴としています。
Artificial Intelligence (AI) in Manufacturing Market size was valued at USD 16.2 billion in 2023 and is poised to grow from USD 23.59 billion in 2024 to USD 476.4 billion by 2032, growing at a CAGR of 45.6% during the forecast period (2025-2032).
As of October 2023, the manufacturing sector is experiencing a significant surge in artificial intelligence (AI) adoption, driven by advanced technologies such as analytics, augmented reality, virtual reality, smart packaging, and additive manufacturing. Flexibility and a growing demand for sustainable solutions are pivotal in this growth. Additionally, the increasing reliance on automation and big data integration is expanding market opportunities. Machine vision cameras are becoming increasingly prevalent, enhancing applications in machine tracking, logistics, field service, and quality control. A notable development in this landscape is Databricks' launch of the Databricks Lakehouse for manufacturers in April 2023, which features pre-developed AI solutions that have been successfully employed by industry leaders like DuPont.
Top-down and bottom-up approaches were used to estimate and validate the size of the Artificial Intelligence (AI) In Manufacturing market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Artificial Intelligence (AI) In Manufacturing Market Segments Analysis
Global Artificial Intelligence (AI) in Manufacturing Market is segmented by Offering, Technology, Application, Industry and region. Based on Offering, the market is segmented into Hardware, Software and Services. Based on Technology, the market is segmented into Machine Learning, Natural Language Processing, Aware Computing and Computer Vision. Based on Application, the market is segmented into Predictive Maintenance and Machinery Inspection, Inventory Optimization, Production Planning, Field Services, Quality Control, Cybersecurity, Industrial Robots and Reclamation. Based on Industry, the market is segmented into Automotive, Energy and Power, Metals and Heavy Machinery, Semiconductor & Electronics, Food & Beverage, Pharma, Mining and Others. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the Artificial Intelligence (AI) In Manufacturing Market
The implementation of Artificial Intelligence (AI) in the manufacturing sector is set to significantly enhance productivity levels. AI technologies can process vast amounts of data from manufacturing machines in real-time, identifying bottlenecks and streamlining processes to minimize downtime. This leads to improved efficiency and reduced operational costs, making AI an attractive investment for manufacturers aiming to maintain a competitive edge in the industry. As businesses strive for greater productivity and cost savings, the integration of AI solutions becomes increasingly essential, driving the growth and adoption of these advanced technologies in manufacturing operations.
Restraints in the Artificial Intelligence (AI) In Manufacturing Market
A significant barrier to the widespread implementation of artificial intelligence in manufacturing is the substantial initial investment required. Integrating and developing AI systems demands considerable financial resources for hardware, software, and the recruitment of skilled professionals. This challenge is particularly pronounced for small and medium-sized enterprises (SMEs), which often struggle to allocate these essential resources. Consequently, the financial constraints faced by SMEs hinder the broader adoption of AI technologies within the manufacturing sector, affecting their ability to compete and innovate in an increasingly automated industry.
Market Trends of the Artificial Intelligence (AI) In Manufacturing Market
The integration of Artificial Intelligence (AI) with the Internet of Things (IoT) represents a significant market trend in manufacturing, facilitating the advancement of smart manufacturing practices. This synergy harnesses connected devices and sensors to deliver real-time data, which AI algorithms then analyze to streamline production processes and enhance supply chain management. As a result, manufacturers can achieve greater operational efficiency, agility, and scalability in response to fluctuating market demands. This trend is a cornerstone of Industry 4.0, driving innovation and competitiveness in the sector, ultimately shaping a future where manufacturing is increasingly automated, data-driven, and responsive.