AI in Textile Market Size to Worth USD 68.44 Billion by 2035: Report
27 May 2026: Global AI in textile market size is calculated at USD 4.12 billion in 2025 and is predicted to increase from USD 5.46 billion in 2026 is expected to be worth around USD 68.44 billion by 2035, growing at a compound annual growth rate (CAGR) of 32.45% over the forecast period 2025 to 2035. The Asia Pacific artificial intelligence (AI) in textile market held the largest share of 50% of the global market in 2024. A study published by Towards Chemical and Materials a sister firm of Precedence Research.
The growth of Artificial Intelligence (AI) in the textile market is primarily driven by rising demand for advanced quality control systems that can detect subtle fabric defects with high precision, along with the need for greater operational efficiency through predictive maintenance and automated process optimization.
What is Meant by Artificial Intelligence (AI) in Textile ?
Artificial Intelligence (AI) in the textile market is rapidly expanding as manufacturers integrate advanced digital technologies to enhance production efficiency and product quality. AI is being used for automated fabric inspection, predictive maintenance, and real-time monitoring, allowing companies to reduce defects and minimize operational downtime. The industry is also leveraging AI-based analytics for demand forecasting, inventory optimization and improved supply-chain planning.
– Levi Strauss & Co. has adopted AI-driven laser technology to finish jeans, which improves design accuracy and significantly reduces water and chemical usage in the finishing process.
– Adidas has used AI-powered robots in its “Speedfactory” to enable the efficient, high-speed, and custom manufacturing of footwear.
– Smartex.ai installs AI and computer vision technology in textile factories to automatically detect fabric defects in real-time, improving quality control and reducing waste.
– Matoha Instrumentation received seed funding led by Archipelago Ventures and the Circular Plastics Accelerator to develop AI-enabled infrared scanners for rapid and accurate sorting of textile waste to aid in recycling efforts.
– Sun Tekstil made a strategic investment in Refabric (Mintgrams Technologies Inc.), an AI-powered design platform, to integrate AI into product development and marketing processes and accelerate digital transformation in fashion.
What are the Key Trends of the Artificial Intelligence (AI) in Textile Market ?
Automation and Smart Manufacturing
AI is driving the adoption of intelligent manufacturing systems and robotics, transforming traditional, labor-intensive processes into automated workflows. This trend improves operational efficiency, increases production speed and consistency, and enables predictive maintenance to minimize costly equipment downtime.
Sustainability and Waste Reduction
Driven by increasing environmental awareness, AI technologies are being utilized to optimize resource consumption and minimize waste throughout the production cycle. AI algorithms optimize fabric cutting patterns to maximize material usage and control dyeing processes to use less water and fewer chemicals, contributing to an eco-friendlier industry.
Personalization and Customization
AI is enabling mass customization by analyzing vast amounts of consumer data to predict fashion trends and understand individual preferences. This data-driven approach allows brands to offer personalized product recommendations and made-to-order garments, which enhances customer satisfaction and reduces the risk of unsold inventory.
Market Opportunity
AI-Driven Smart Textiles: A Transformational Opportunity
One major opportunity in the Artificial Intelligence (AI) in Textile market lies in the rapid expansion of AI-powered smart textiles, which combine embedded sensors, data analytics, and adaptive functionality. These textiles are gaining strong traction in healthcare for continuous monitoring of vital signs, in sports for performance tracking, and in defense for enhanced situational awareness.
Technology Insights
In 2024, the machine learning and deep learning segment dominated the market, due to these technologies enabled highly accurate fabric defect detection, pattern recognition, and predictive maintenance, outperforming traditional inspection methods. Their ability to learn from large volumes of textile data allowed manufacturers to optimize production processes, forecast equipment failures, and reduce operational costs. Deep learning models also supported advanced applications such as trend forecasting, automated design generation and customization, enhancing product innovation.
The computer vision segment is growing fastest in the market, due to it provided unmatched accuracy in detecting fabric defects, color inconsistencies, and pattern deviations at high production speeds. Its ability to analyze images in real time significantly improved quality control, reducing waste and enhancing overall manufacturing efficiency. Computer vision systems also enabled fully automated inspection processes, minimizing reliance on manual labor and increasing consistency in output.
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