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1. Digitalisation will support resiliency amid geopolitical turbulence
Amid political instability, shifting trade policies, inflation and labour shortages, Paul F Magel, president at Computer Generated Solutions, stressed: “The bigger picture is this: volatility is the new normal. Supply chains must be built to withstand whatever curveball comes next.”
The key shift is towards AI-enabled decision-making:
real-time, end-to-end visibility combined with “what-if” scenario modelling allows brands to anticipate disruptions rather than react.
As Magel noted: “With the right data, AI can model the cost and operational impact of multiple trade or sourcing scenarios. That means brands can plan in advance, not just react. AI can spot early demand shifts, improve forecasting and even recommend sourcing adjustments to help offset policy changes or cost spikes.”
Yang Yaolin, head of the Innovation Division at the Department of Science and Technology Development, China National Textile and Apparel Council, added that “digitalisation has become a vital pillar for enterprises to enhance resilience” and “Digitalisation will assist enterprises in navigating supply chain volatility.”
2. 5G for machine connectivity sees continued focus and competition
WiFi’s inaccuracy and susceptibility to interruption limit control of advanced equipment across large factory floors, constraining AI adoption. This is driving uptake of private 5G networks, which offer the connectivity required for increasingly complex, data-driven manufacturing.
5G is now emerging as a competitiveness lever: industrial sites are being built with integrated 5G, while Nokia’s new Finnish R&D and manufacturing campus centres on ‘next-generation networks’. National strategies, particularly in China, are accelerating cross-industry 5G integration. A September 2025 report similarly argued 5G will underpin Manufacturing 4.0 in the US, enabling safer, more efficient and innovative factories.
With high speed, low latency and capacity, 5G supports AI deployment, large-scale data analysis and real-time decision-making.
3. Cybersecurity is essential for continued manufacturing growth
Fashion cybersecurity risks are rising as brands adopt AI and GenAI, while attackers simultaneously use AI to scale and adapt attacks. In May 2025,
analysis reported a staggering 50% rise in supply chain attacks in manufacturing, marking cybercrime as the fastest-growing threat.
A key vulnerability lies in legacy and unmanaged OT systems integrated with IT networks, which create entry points for AI-driven attacks. Hackers increasingly deploy automated malware, deepfake social engineering and ransomware, accelerating breach speed and complexity.
A September 2025 study of 1,500 manufacturing leaders found cyber risk is now a top threat to growth, with firms prioritising cyber readiness and using AI to strengthen defence.
4. AI will exponentially proliferate by 2030 – guidelines are needed
AI is driving a perceived ‘next stage’ of textile and fashion innovation, processing vast datasets far faster than humans and enabling material discovery, manufacturing optimisation, process automation, supply chain efficiencies, trend analysis and design innovation.
From predictive maintenance to computer vision, AI reduces costs, speeds innovation and solves problems previously beyond human capacity. Yet, its rapid, paradigm-shifting impact sparks controversy and uncertainty.
Governments are prioritising AI: Thailand aims to use it to “transition the country’s economy and society [towards one] driven by innovation and high-tech industry”, while the US, China and the UK pursue global leadership, with the UK’s AI blueprint aiming to ‘turbocharge AI’. Regulatory efforts include the EU’s AI Act.
Matthew Drinkwater, head of the Fashion Innovation Agency at London College of Fashion, University of Arts London, stresses progress must balance efficiency with “green compute and cultural stewardship”, ensuring systems are “fair and representative ones”.
5. Breakthrough in fabric handling technologies on the periphery
Robot dexterity remains a major bottleneck in textile automation. “Having a good sense of touch is not among [robots’ capabilities],” researchers at the University of Buffalo (UB) note, limiting tasks like sewing and gripping. Adaptive grippers exist, but widespread adoption is constrained by these limitations.
In September 2025, a new AI was introduced enabling robots to skilfully handle objects that change continuously in shape, including clothing, rubber bands and wires. Simultaneously, UB researchers are developing an
electronic textile (e-textile) that mimics human hand nerves, sensing pressure and slip to improve robotic grasping.
These AI-driven advances suggest a potential breakthrough in fabric handling technology is imminent.
Author: Otis Robinson, WTiN
