Clement Guillon’s Post

⌛ Just a few weeks left before 2026, and #AI is already at the core of leading retailers’ strategies. What about yours? We’ve all heard the buzz about AI, but which use cases will truly reshape fashion and apparel? Our new eBook, Top AI Use Cases for Fashion & Apparel, helps you find the gold at the end of the rainbow 🌈, highlighting the most impactful, ready-to-deploy applications delivering measurable results today. Here’s a sneak peek at what’s inside: ✔️ Assortment & Demand Planning – Plan with precision, cut overstock ✔️ Sourcing & Production Automation – Shorten lead times, boost margins ✔️ Auto Compliance Checking – Catch non-compliant products early ✔️ Auto Attribution – Enrich product data instantly ✔️ Auto HTS Classification – Simplify trade with automated coding …and much more! Explore the full set here 👉 https://lnkd.in/erNS7-b9 #AI #FashionTech #RetailInnovation #DigitalTransformation #BambooRose #ApparelIndustry

📦 AI-Driven Supply Chain Visibility: Transparency from Factory to Consumer Modern fashion supply chains are complex — spanning factories, warehouses, stores, and e-commerce platforms. AI provides a single source of truth for every step. 📊 Real-Time Tracking: AI consolidates data from suppliers, production lines, logistics providers, and retail outlets, giving brands a unified view of inventory and shipments. 🧠 Predictive Alerts: Algorithms identify potential bottlenecks or delays before they impact operations, enabling proactive decisions. 💡 Operational Efficiency: AI optimizes routing, production schedules, and stock replenishment, reducing costs and delivery times while improving service levels. 🌟 Business Impact: Brands gain better control over inventory, reduce overproduction, and ensure timely product availability for customers. 💬 Pro tip: Integrate AI supply chain insights with demand forecasting to align production and distribution with market trends, avoiding excess stock or shortages.

In retail, product returns are often seen as an unavoidable cost of doing business. But with AI, I see them as one of the greatest opportunities for growth. Across U.S. e-commerce, return rates average 17%, and in apparel and footwear they climb to 24–26% -- sometimes even 50% during peak seasons. In 2023 alone, that meant $38B in returned merchandise and another $25B in processing costs. AI is helping us move from reacting to returns to preventing them. Here’s how: - Mining returns data: Using natural language processing to analyze return codes, product reviews, and sales data helps identify exactly why items are coming back—whether it’s inconsistent sizing, misleading imagery, or gaps in product descriptions. - Personalized guidance: AI-powered tools improve product descriptions, offer smarter sizing recommendations, and even use AR/VR to set clearer expectations. - Turning cost into loyalty: When customers feel confident about what they’re buying, they’re less likely to send it back. That means stronger trust and better margins. Returns will never disappear, but with AI, they don’t have to erode profitability. They can actually build smarter, leaner, more trusted brands. Read more here: https://lnkd.in/eWH2PhZW #retailinnovation #aiinretail #newmine #productreturns

Great insights Rich! Using AI to mine and understand merchandise returns data is a huge opportunity for all retailers - but especially so for apparel retailers as we head into peak. A McKinsey survey indicated that as much as 70% of apparel returns were driven by fit and style issues. Diving into fit and style misalignments with customers has allowed some apparel retailers to reduce their returns by over 30%. You don't need AI to calculate the impact of a 20% - 30% returns rate improvement at your gross margin line! The potential prize is too big to ignore! Deploying AI tools to understand returns? Great advice - thank you Rich!

A new MIT/Harvard study just explained how AI agents can collapse coordination costs, and solve fashion's low fullprice sell-through / overproduction crisis. The real barrier to demand-driven buying isn't technology. It's the tedious process of responsive ordering. Moving from 4-season buying to 52-week responsive ordering means 8x more purchase orders. That's 8x more supplier coordination, SKU decisions, delivery scheduling - tasks so tedious they've kept the entire industry locked into overproduction cycles. Shahidi et al., 2025's paper on AI agents in markets crystallizes why this changes now: "AI agents enable undertakings that would not have been attempted at all. By lowering the cost of exploration and execution, they expand the feasible set of options and reduce the threshold of 'worth doing.'" Placing micro-orders at high frequency is the exact use case agents are built for: — Low-stakes decisions (unlike strategic sourcing) — Low dimensionality (supplier, SKU, quantity, timing) — High volume, repetitive (perfect for compute vs. human time) — Historical data-rich (existing POs train agent preferences) Here's what this means practically: Instead of your merchandising team spending weeks consolidating 4 seasonal buys, an agent places optimized orders weekly based on real sell-through data. The agent handles: — Monitoring inventory levels across channels — Generating order recommendations per supplier — Negotiating standard terms — Scheduling deliveries — Tracking PO status The human role shifts to oversight and exception-handling, not administrative execution. We're looking for 2 forward-thinking fashion brands to pilot this approach. If your team is frustrated by the lag between customer demand and inventory response, let's experiment together. 📄 Full paper: "The Coasean Singularity? Demand, Supply, and Market Design with AI Agents" — https://lnkd.in/eSyF94K2 (Next post: why the supplier side is the real unlock—and harder problem to solve)

📈 Every Small Business Needs an EFFECTIVE AI Strategy NOW — especially in the textile and apparel industries. AI is no longer optional for SMBs. It’s the foundation for smarter operations, better forecasting, and scalable growth. In this video, we explore how small businesses can build and implement an AI strategy using the latest AI tools and automation solutions tailored for the textile and fashion sector. 🔍 Key takeaways: ✅ What makes an AI strategy effective ✅ How to align AI with business goals ✅ Real-world examples from textile and apparel SMBs 🚀 Watch now to learn how AI can transform your business operations and future-proof your growth. #AIforSmallBusiness #ERPforTextile #AIinFashion #DigitalTransformation #SmartManufacturing #TextileInnovation #FashionTechnology #NevasAI #NevasTech You can follow me across these social handles: 🎥YouTube: https://lnkd.in/g-WY--pr 📸 Instagram: https://lnkd.in/ggesiWRG 💼 LinkedIn: https://lnkd.in/gr_a2KWr 📘 Facebook: https://lnkd.in/gXfqPUb5 🐦Twitter: https://lnkd.in/g6tjU7bE 🌟 Please leave a LIKE ❤️ and SUBSCRIBE for more AI content!

📈 Every Small Business Needs an EFFECTIVE AI Strategy NOW — especially in the textile and apparel industries. AI is no longer optional for SMBs. It’s the foundation for smarter operations, better forecasting, and scalable growth. In this video, we explore how small businesses can build and implement an AI strategy using the latest AI tools and automation solutions tailored for the textile and fashion sector. 🔍 Key takeaways: ✅ What makes an AI strategy effective ✅ How to align AI with business goals ✅ Real-world examples from textile and apparel SMBs 🚀 Watch now to learn how AI can transform your business operations and future-proof your growth. #AIforSmallBusiness #ERPforTextile #AIinFashion #DigitalTransformation #SmartManufacturing #TextileInnovation #FashionTechnology #NevasAI #NevasTech You can follow me across these social handles: 🎥YouTube: https://lnkd.in/gKRwzaUx 📸 Instagram: https://lnkd.in/gEkiVEZ4 💼 LinkedIn: https://lnkd.in/gvNEWwgs 📘 Facebook: https://lnkd.in/gCnmNQBY 🐦Twitter: https://lnkd.in/gHAQD-yV 🌟 Please leave a LIKE ❤️ and SUBSCRIBE for more AI content!

🚀 AI isn’t the future of supply chain — it’s happening right now. At ouvar™, we’re seeing AI change the game in marketing logistics: ✅ Invoice auditing to detect overcharges & recover credits ✅ Predictive planning to reduce waste & improve capacity ✅ Packaging optimisation to cut damage, shrink & emissions ✅ Real-time supplier performance visibility ✅ Faster, smarter decision-making with clean data This isn’t about replacing people — it’s about empowering teams with intelligence, reducing manual errors, and creating a supply chain that is transparent, efficient and measurable. The result? 📉 Lower cost. 📦 Faster activation. 🔍 Better visibility. 🌱 Less waste. 🏪 Stronger brand execution in-store. AI won’t solve every problem — but in the hands of the right operators, it eliminates the guesswork so brands can move with confidence. The supply chain isn’t getting simpler. The smartest teams are already using AI to stay ahead. #ouvar #supplychain #AI #marketingoperations #fmcg #retailactivation #logisticsinnovation #data #automation #sustainability

Technology is only as powerful as the humans who shape it. At Shop My Palette, our human + AI colour analysis pipeline bridges data and design — transforming simple product images into intelligent, seasonally tagged fashion data. The process is continuous: AI analyses hue, depth, and clarity; human verification refines the results; and each correction feeds our improvement loop — helping the model learn faster and get smarter over time. This partnership between human insight and machine precision is what makes Shop My Palette different: technology that learns the language of colour. #AIinFashion #FashionTech #SustainableInnovation #RetailIntelligence #ShopMyPalette

Demand Forecasting & Supply Chain - AI in Retail Week 4 In today’s unpredictable world, accurate forecasting isn't just helpful — it’s critical. AI is transforming how retailers forecast demand and manage their supply chains, using real-time data instead of outdated spreadsheets. AI-Powered Forecasting  Uses sales trends, events, weather, and even social media to predict demand at a granular level. Smarter Supply Chains  AI optimizes inventory allocation, shipping routes, and vendor coordination — reducing costs and improving speed. Risk Mitigation  Machine learning flags potential disruptions — like supplier issues or sudden demand spikes — before they hit your bottom line. Human + AI collaboration wins here. Planners still matter — AI just helps them move faster and smarter. #SupplyChainAI #DemandForecasting #RetailTech #RetailOperations