Despite the dual pressures of Red Sea logistical disruptions and a projected 9–10 per cent contraction in exports to the US for 2026, the Indian textile industry is transitioning toward a high-growth trajectory.
Speaking at the ITAMMA Awards in Coimbatore on March 7, 2026, industry leaders emphasized, the sector has moved past its recessionary phase. The optimistic outlook is supported by a robust policy framework, including the removal of anti-dumping duties on man-made fiber (MMF) raw materials and the alignment of the MMF value chain under a unified 5per cent GST slab. These structural corrections, alongside newly effective Free Trade Agreements with the UK and UAE, are essential levers for India to capture market share under the global ‘China+1’ sourcing strategy.
Balancing automation with human-centric innovation
The next phase of industrial evolution is being defined by a strategic blend of advanced technology and human capital. S Krishnakumar, Deputy Chairman, SIMA, notes, the time has come to perform by way of innovation taking advantage of AI, highlighting the necessity of smart manufacturing to maintain global competitiveness. D Venkadesan, CEO, Sri Jayajothi and Company, cautioned, technology remains a ‘crutch’ without empowered personnel. This perspective shifts the focus toward a culture of continuous improvement where AI serves as a tool for human ingenuity. With the Union Budget 2026-27 introducing five mega schemes to boost productivity, the industry is positioned to bridge infrastructure deficits and achieve its $100 billion export target by 2030 through value-added, sustainable manufacturing.
The Indian Textile Accessories and Machinery Manufacturers' Association (ITAMMA) has supported the textile engineering sector since 1948. Representing a diverse membership across spinning, weaving, and processing segments, the association fosters global competitiveness through export excellence initiatives and ‘Make in India’ benchmarks. ITAMMA continues to drive innovation by integrating modern automation and AI into traditional manufacturing frameworks.
