U.S. Artificial Intelligence in Manufacturing Market Size Worth USD 89.98 Billion by 2034 | CAGR: 45.4%

U.S. Artificial Intelligence in Manufacturing Market Size Worth USD 89.98 Billion by 2034 | CAGR: 45.4%


The U.S. artificial intelligence (AI) in manufacturing market size is expected to reach USD 89.98 billion by 2034, according to a new study by Polaris Market Research. The report “U.S. Artificial Intelligence in Manufacturing Market Size, Share, Trends, Industry Analysis Report By Component (Hardware, Software), By Technology, By Application, By End Use – Market Forecast, 2025–2034” gives a detailed insight into current market dynamics and provides analysis on future market growth.

AI in manufacturing refers to the use of artificial intelligence technologies such as machine learning platform, computer vision, and robotics to optimize production processes, improve quality control, and reduce downtime. It enables predictive maintenance, real-time monitoring, and automated decision-making across supply chains and factory operations.

Rising labor costs and a shortage of skilled workers in the U.S. manufacturing sector are prompting companies to invest in AI-driven automation. AI helps fill critical labor gaps by taking over repetitive or dangerous tasks, improving workplace safety and productivity. At the same time, AI-powered systems improve the effectiveness of existing workers by providing real-time data and decision support. This shift is particularly important in regions with aging workforces or where talent is hard to find. AI offers a practical and scalable solution to maintain output without compromising quality or safety as labor challenges persist, thereby driving the growth.

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The U.S. manufacturers are prioritizing supply chain resilience and reshoring efforts following disruptions caused by the COVID-19 pandemic and geopolitical tensions. AI plays a critical role in this shift by improving supply chain visibility, predicting demand fluctuations, and optimizing logistics. Manufacturers are using AI to monitor real-time inventory, automate procurement decisions, and adapt quickly to external shocks. These capabilities are essential for creating agile, responsive supply chains that support local production. The national focus on economic resilience, combined with the need for just-in-time efficiency, makes AI a strategic tool in rebuilding and strengthening U.S.-based manufacturing operations, thereby fueling the adoption of AI in manufacturing.

U.S. Artificial Intelligence in Manufacturing Market Report Highlights

  • The hardware segment led the U.S. market in 2024, driven by increasing demand for high-performance computing systems, AI-enabled sensors, and robotics to enhance manufacturing efficiency and automation.
  • The computer vision segment witness notable growth in 2024, propelled by the rising need for intelligent visual inspection, real-time safety monitoring, and image-based analytics in key industries such as automotive, aerospace, and food manufacturing.
  • The production planning segment is expected to grow significantly as manufacturers prioritize agility and operational efficiency in response to changing consumer preferences, labor constraints, and persistent supply chain disruptions.
  • The medical devices segment accounted for the largest market share in 2024. The dominance is supported by the country’s advanced healthcare sector, strong innovation ecosystem, and strict regulatory requirements that emphasize precision, reliability, and compliance in manufacturing.
  • A few key players in the U.S. AI in manufacturing market are Microsoft Corporation; Mitsubishi Electric Corporation; NVIDIA Corporation; Oracle Corporation; Rethink Robotics; Rockwell Automation Inc; SAP SE; Siemens AG; Sight Machine; and Spark Cognition Inc.

Polaris Market Research has segmented the U.S. artificial intelligence in manufacturing market report based on component, technology, application, and end use:

By Component (Revenue - USD Billion, 2020–2034)

  • Hardware
  • Software
  • Services

By Technology (Revenue - USD Billion, 2020–2034)

  • Machine Learning (ML)
  • Computer Vision
  • Context Awareness
  • Natural Language Processing

By Application (Revenue - USD Billion, 2020–2034)

  • Material Movement
  • Predictive Maintenance & Machinery Inspection
  • Production Planning
  • Field Services
  • Quality Control & Reclamation
  • Others

By End Use (Revenue - USD Billion, 2020–2034)

  • Semiconductor & Electronics
  • Energy & Power
  • Medical devices
  • Automobile
  • Heavy Metal & Machine Manufacturing
  • Others