According to the latest report published by Global Market Insights Inc., global AI in the manufacturing market was valued at US$4.2 billion in 2024 and is projected to grow at a CAGR of 31.2% between 2025 and 2034.
The growing need for streamlined outsourcing solutions within the manufacturing sector is driving AI adoption. Companies are consolidating AI to automate processes such as production control, inspection and inventory management to enhance production efficiency, cost of reduction and operation at scale. The increasing availability of AI-powered solutions is profiting businesses of all sizes, from large manufacturers to small and medium-sized businesses. Governments around the world prioritize AI research and development and provide financial incentives such as funding programs, tax credits and regulatory assistance to increase AI implementation. These initiatives are designed to drive innovation, increase productivity and reduce costs across a variety of industries.
The market is segmented into hardware, software and services based on components. In 2024, the hardware segment holds a market share of over 55%, and is expected to exceed US$32 billion by 2034. The growing demand for advanced computing hardware is driving this growth as AI applications such as robotics, predictive maintenance, and quality control require high-performance components for real-time data processing. Machine learning and deep learning algorithms also promote the need for powerful hardware to improve AI performance. Rapid advances in data processing capabilities enable you to improve automation, increase productivity and improve decision-making.
Depending on the deployment model, the market is divided into on-premises and cloud solutions. In 2024, the crowdsegment accounted for around 43% of the market. As businesses across the industry adopt digital transformation, the demand for cloud-based AI solutions is growing, making manufacturing more competitive. Cloud computing offers flexibility and scalability, reduces operational costs and provides a streamlining process. Additionally, remote implementations enhance data storage and processing. This is important for AI applications that rely on a wide range of datasets. Cloud-based solutions also allow real-time collaboration between manufacturers, suppliers and customers, allowing for improved decision-making and accelerated time to market.
The market is segmented by technology, including machine learning, computer vision, natural language processing, and context-aware computing. Machine learning is expected to lead the market and generate around US$19 billion by 2034. This growth is attributed to the increased use of machine learning for intelligent automation and data-driven decision-making. AI-driven quality control solutions improve product inspection accuracy and minimize production losses. The adoption of machine learning in manufacturing is also driven by the rise of IoT technologies that collect, analyze, and process data for optimized operations.
The market is further divided by applications, including quality control, predictive maintenance, inventory control, energy management, industrial robotics. Predictive maintenance held its largest share at around 25% in 2024. AI-powered predictive maintenance solutions Use machine learning algorithms to monitor and evaluate equipment performance in real time, preventing business failures, reducing maintenance costs and minimizing production disruptions. The growing need for increased productivity and reduced downtime is driving demand for these systems.
The US led North American AI in the manufacturing market in 2024, holding approximately 75% of its regional share. The country's strong government support for AI-driven smart manufacturing is a key factor in market growth. Policymakers prioritize automation and advanced technologies to enhance the competitiveness of the country's manufacturing sector. Furthermore, the focus on strengthening supply chain resilience and optimizing production efficiency is to further promote the adoption of AI in the industry.
