Artificial Intelligence in Retail

The teen models in Mango's latest campaign have perfect poses, perfect lighting, and one small detail: they don't exist. This Spanish fashion giant launched their Sunset Dream collection using entirely AI-generated models across 95 markets. Not a single human model was photographed. Here's how they did it: 📌 Took photos of real clothes on display stands 📌 Fed these pictures to their AI system 📌 Created model images in minutes 📌 Rolled out everywhere at once The business impact is massive. Fashion brands typically save 60-80% by leveraging AI photoshoots. Those savings can now fund innovation, better pricing, or faster expansion. But cost isn't the real story here. Speed is. While competitors wait weeks for campaign photos, MANGO creates, tests, and launches collections in days. No weather delays. No scheduling conflicts. No reshoots. This wasn't luck. Since 2018, Mango has built 15 different AI platforms across their business. They've been preparing for this moment. The result? Their 2024 turnover reached 3.3 billion euros in 2024, growing 7.6% from 2023. What makes this significant is that Mango proved AI-generated content can drive real sales. Their teen customers embraced these virtual models without hesitation. Fashion's biggest players are watching. If Mango's approach succeeds long-term, traditional photography could become a thing of the past for e-commerce. The brands that adapt now will set industry standards. Those that don't might find themselves competing against companies moving at AI speed. Which fashion tradition do you think AI will disrupt next?

Amazon announced it would be rolling out drones for customer delivery in 2 US cities, while Walmart is expanding drone coverage to 8 cities, serving 1 in 10 shoppers. Physical AI is having its ChatGPT moment. Two-thirds of all Walmart stores and 55% of its fulfillment center volume will move through automated distribution hubs by early next year. Amazon is completely rebuilding its warehouse and supply chain operating model around automation. Walmart is testing out automated construction technology to expand its stores and build new ones. Amazon has multiple partners to augment its delivery fleet with autonomous trucks. Physical AI transformations aren’t years out. They are in the late stages of implementation. Walmart and Amazon are already reporting higher margins and improved customer service levels. The agentic paradigm includes physical agents with the ability to act in the real world. That’s why NVIDIA built Cosmos, and Salesforce is expanding Agentforce with physical AI partners. Customer service is being extended through drones, autonomous vehicles, and robotics-enabled order fulfillment. Agents answering the phone or supporting the website are just a small part of the workflow. Physical AI is orders of magnitude BIGGER than the LLM market, its impacts are just as broad, and the transformation cycle is already in full swing. Most firms are still struggling to implement their data strategies and come to terms with the implications of generative AI. Businesses need an AI strategy that’s platform-centric to manage multiple technology waves. Efficient implementation frameworks are critical. Strategy can’t take 2 years to implement because technology waves are breaking faster. Businesses that can’t continuously transform won’t survive the next 3 years.

What is the potential of technology to meaningfully reduce fresh food waste, and in doing so significantly alter a grocery retailer’s P&L? Heading into Groceryshop later this month the challenge of escalating shrink is top of many minds. Much focus is understandably on increasing theft and the impacts of organized crime on retailers and their employees. The largest source of loss for many grocery retailers, though, remains fresh food wastage. Fresh food waste can cost up to 3% of total turnover for some grocers, therefore significant reductions here have the potential to transform the economics of grocery stores that run on such wafer-thin margins. And there’s a greater opportunity, as between 40-60% of fresh produce grown globally is wasted. There’s a clear sustainability and moral imperative to do better. Around the world we’re observing a range of technologies emerging that seek to reduce fresh food waste, and which fall into four broad buckets: 1. Dynamic Pricing tools that utilize AI to automate the mark-down price to ensure products sell out before date expiry, like Ahold Delhaize's Albert Heijn chain is trialing in the Netherlands 2. Produce coatings or protective stickers, that utilize natural antimicrobial compounds to protect against disease and extend shelf life, like Apeel, AgroSustain SA or Stixfresh 3. Ordering or inventory management tools powered by AI that optimize order quantities, manage in-store positions or empower store teams to efficiently allocate rescue channels, such as those from Picadeli, Afresh or Smartway.AI 4. Hydroponic vertical farms, located in-store to dramatically shorten the supply chain and respond quickly to changing demand, like SweGreen currently in ICA Gruppen Sweden and now expanding in EDEKA ZENTRALE Stiftung & Co. KG supermarkets in Germany I’d love to hear your thoughts and other solutions you’re seeing or trialing. Let's chat at Groceryshop!

Walmart turns AI traffic into a checkout weapon — and FMCG brands should be watching A silent shift is unfolding in digital commerce — one that could reshape the balance between retailers, search engines, and FMCG brands. In August 2025, The Sales Mind (an AI-driven discovery platform) generated 20% of referral traffic to Walmart and Etsy Shop, ~15% to Target, and 10% to eBay. Just a month earlier, these shares were far lower. While AI referrals still account for under 5% of total site visits, the growth trajectory is unmistakable. Consumers are no longer searching — they’re chatting. Instead of typing “best detergent for cold wash” into Google, users now ask ChatGPT. The AI then filters and recommends products based on trust, relevance, and data — not ad spend. That’s where Walmart’s new ChatGPT “Instant Checkout” integration becomes a strategic weapon. With 420 million SKUs accessible and 60% of US shoppers already using GenAI for shopping (Omnisend, Aug 2025), the retailer is positioned to convert AI traffic directly into sales — within the chat interface itself. Unlike traditional e-commerce search, this is agentic commerce — proactive, predictive, and closed-loop. Users ask. AI suggests. Checkout happens instantly. Walmart owns the funnel from intent to purchase, bypassing Google and traditional search entirely. For FMCG brands, the implications are serious: – Shelf visibility no longer guarantees discoverability. – SEO and paid search lose influence as AI agents decide what’s relevant. – Retailer data-sharing policies determine whether a brand is even “seen.” Amazon, which restricted AI crawlers, saw an 18% drop in The Sales Mind-driven traffic in August — while Walmart and Target surged. With 2.5 billion ChatGPT prompts per day and ~50 million shopping-related queries, the new shelf is conversational. Retailers that integrate checkout directly into AI ecosystems will dominate the next era of digital commerce. Background: Walmart Inc. (USA) is the world’s largest retailer, operating in 19 countries with over 10,500 stores and a growing digital ecosystem exceeding $100 billion in annual e-commerce revenue. Its partnership with OpenAI positions it at the center of this behavioral and technological shift. #retail #fmcg #ecommerce #ai #chatgpt #openai #walmart #agenticcommerce #digitalcommerce #retaitech #foodtech #generativeai #omnichannel #innovation #marketing #sales #search #retailtech #data #automation #consumerbehavior #shopping #startups #investment #businessstrategy #usa #northamerica #aiinretail #futureofretail #retailinnovation #customerexperience

ThrillingTechTrends #13 - Carbon Intelligence ♻️ is redefining what’s possible. Measuring freshness is great. But measuring freshness with impact is even greater: Using a combination of real-time IoT sensor data, AI-based route prediction, and lifecycle-based emission models, it’s becoming possible to measure and manage CO₂ output across every leg of the fresh supply chain — from pre-cooling and storage to multimodal transport and last-mile delivery. Here’s what’s happening behind the scenes: ✅ Telematics & Sensor Fusion: Temperature, humidity, energy consumption, and fuel data are aggregated via connected devices on trucks, containers, and warehouses. ✅ Edge Analytics: Emission data is processed on the move to detect anomalies, idle times, and inefficient cooling cycles — enabling instant optimization. ✅ AI-Driven Carbon Forecasting: Predictive models simulate carbon impact under different routing, timing, and packaging scenarios to support low-emission decisions in real time. ✅ Dynamic CO₂ Attribution: Each product unit can be assigned a precise carbon footprint based on actual transport conditions, not static averages — enabling true product-level transparency. The result? A smarter cold chain that keeps food fresh and carbon footprints low. Decarbonizing fresh logistics is no longer an ambition — it’s getting reality & will make our world better. 🌎 #CarbonIntelligence #FreshLogistics #ColdChainTech #SupplyChainInnovation #IoT #SustainableLogistics #AIinLogistics #GreenTech

Shift your focus from “technology for technology’s sake” to practical, integrated solutions in the restaurant industry. Why? The future is here, and it's more efficient than flashy. Recent advancements show how robots and AI are redefining restaurant operations: - RobotLab's new systems like Robot on Call and ServeSwift enhance staff efficiency by enabling remote control and task delegation. - Picnic Works' partnership with Roboworx aims to streamline automated pizza-making nationwide. - AI platforms from Givex and Brightloom are personalizing customer engagements, driving higher retention and loyalty. - QR technology and loyalty integrations, such as NCR Voyix's Aloha Pay and Thanx-Bite collaboration, keep customer experiences seamless and rewarding. How will these shifts impact your customer service and operational efficiency? Let’s discuss the balance between tech adoption and practical utility. #RestaurantTech #AI #Automation #Robotics #CustomerEngagement #Innovation

Thirty two percent of shoppers now hit a marketplace right after asking an AI tool what to buy. That shift lands faster than most brands can refresh their content. The funnel is mutating in real time. People chat with an AI assistant, get a product idea, then sprint straight to Amazon bol Zalando or whoever has stock and a decent price. The discovery moment no longer happens on the marketplace. The marketplace just cashes in on the validation step. This creates a very odd tension. Brands fight for visibility on the platforms while the actual decision spark happens somewhere completely different. The winning listing is simply the one that looks trustworthy enough when the AI referred shopper arrives. Think about what that does to competition. The ranking battle becomes less about intent harvesting and more about intent intercepting. If the product is not AI friendly it may never appear in those upstream conversations. Here is where operators can get a real edge 👇 🧲 Treat AI platforms as a traffic channel by enriching metadata and specs 📚 Build deeper review signals so AI tools can surface credible social proof 🔧 Fix inconsistencies across marketplaces because AI models punish messy data 🧭 Track referral shifts from AI based tools and match content gaps to conversion drops 🎯 Use faster content refresh cycles to keep feeds aligned with AI scraped info The new game is simple. The shopper arrives pre convinced and there is no second chance to catch them if the listing fails to match what the AI promised. #ecommerce #marketplaces #dtc #retail #ai

🥬 How automated vegetable de-coring leads to 90% less waste..⁉️ Conventional systems cannot adapt to natural variation in fresh produce: ➡️ No two heads of lettuce are the same ➡️ Shape and size vary ➡️ Each lettuce is positioned slightly differently on the conveyor belt To ensure the core is completely removed, traditional systems compensate by cutting too wide, resulting in significant and unnecessary product loss. Powered by seamlessly integrating Vision inspection & AI : ✅ Up to 90% less waste: waste rate reduced from 30-40% to only 3-5%. ✅ Higher efficiency: thanks to AI-driven control, the system runs more stably and consistently 24/7. ✅ Data insight: the machine collects valuable data on performance and product variations. ✅ Scalable solution: the approach is easily applicable in other Extractacore machines. by Bram de Vrught & QING | Food Automation & Robovision #automation Lukas M. Ziegler Peter Wirth

If your biggest competitive advantage on Amazon is “we’re really good at bid management and keyword research,” you’re already behind. And that gap is widening. unBoxed made one thing painfully clear: The future of retail media isn’t keyword-first. It’s demand-driven, audience-led, and creative-powered. Brands who keep obsessing over micro-bids and negations are optimizing for a world that no longer exists. Amazon rolled out tools that fundamentally shift how brands will grow on this platform: ⭐ Competitive Advantages Going Forward 🔶 AMC Audiences Audience-level intent layered on top of search is the new frontier. You’re no longer just bidding on “electrolytes.” You’re bidding differently when the right audience is searching for electrolytes. 🔶 Expanded Video + Creative Sponsored Products Video is here… with more inventory, thumbnails, and disruptive placement. If you don’t have creative assets ready, Creative Studio’s Agentic Partner is now producing streaming-TV-quality videos on demand. No excuses. 🔶 Sponsored Prompts AI-powered product expertise inside customer journeys. Think Rufus meets automated, contextual recommendations that are sponsored. Discovery will look nothing like keyword-only search. Other Key unBoxed Rollouts - 🔶 Ad Agent Audiences — Agentic partner that recommends targeting based on campaign context, refined by natural language or document upload. 🔶 Sponsored Ad Prompts — Conversational AI ad extensions that let your product meet the customer at their question, not just their keyword. 🔶 Sponsored Products Video — Thumbnail-based engagement, AI-assisted variations, and a massive increase in video inventory. 🔶 Full-Funnel Campaigns — Unified, AI-powered activation across the entire customer journey, fueled by Amazon’s commerce + streaming insights. 🔶 Unified Reporting Experience — 15-month lookback across SP/SB/DSP in one view. Massive operational unlock. Your competitors aren’t beating you because they have better bid logic. They’re beating you because they’re: • Building audiences • Crafting better creative • Going full-funnel • Leveraging AI to scale what used to take teams Retail media is evolving into brand-building + audience intelligence, not keyword harvesting. If you want to win the next era of ecommerce, you must be able to: → Drive demand, not just capture it. → Speak to audiences, not algorithms. → Lead with creative, not bids. This is the advantage our team is leaning into every single day.

Amazon rolled out a lot of updates at Accelerate this year, but most people are missing what’s actually important. Let me break down what sellers really need to pay attention to: 1. Product Launches are NEVER going to be the same. Launching on Amazon used to be expensive and risky. That’s changing. • FBA New Selection = no storage fees + FREE liquidation for 6 months. • Regional Launch = start small, test fast, scale what works. You can now test products with lower inventory risk and clearer signals. This is a HUGE win for operators who know how to execute. 2. AI Is Now Embedded in Seller Central Amazon’s AI tools are evolving fast. This AI can actually DO stuff now, not just recommend. It flags listing issues, optimizes inventory, and suggests promotions automatically. And they improved their AI Creative Studio. Now it can spin up copy, imagery, and video in minutes. This is a HUGE time saver! But if your creative sucks or your data’s a mess, AI just helps you fail faster. 3. Real Customer Journey Analytics You can now track customer behavior down to the ASIN level. 100 real-time metrics across sales, inventory, and ads. All customizable. Finally, data that doesn't require three different tools and a spreadsheet to understand. Amazon is pushing toward speed, automation, and scale, but it doesn’t mean success is easier. You still need operational excellence, real demand data, compelling creative, and strategic paid media. Amazon wants you to test more, and they’re giving you the structure to do it. But it only works if your strategy is solid. ♻️ Found this helpful? Repost to your network. Need help with your Amazon strategy? 🔗 Click the link on my profile to connect with Prime Team Agency.