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?

Google just announced a suite of AI-driven shopping tools designed to transform the online retail experience 💥 Here’s what’s coming: 🧠 AI Shopping Mode: A conversational search tool that understands natural language and context. Think: “best dress for a trip to Cannes in May” – and it will deliver results tailored to weather, location, and purpose. 👗 Virtual Try-On 2.0: Shoppers can now upload full-body photos to see how items actually look on them — including drape, fit, and texture across different body types. A game-changer for apparel conversion rates. 💸 Agentic Checkout + Price Alerts: Users can set price targets, and when an item hits the right price, Google will notify them — or even auto-checkout via Google Pay. What this means for eComm marketers: ▪️ SEO and product data quality will become even more critical ▪️ Conversion will increasingly depend on visual assets (UGC, try-ons, real models) ▪️ Brands need to prep for a world where shopping journeys are conversation-first Currently, these features are being rolled out in the U.S. via Google Search Labs, with plans for broader availability in the future.

AI is changing how we shop and how retail jobs are done. More than 15 million Americans work in retail (BLS). It’s one of the largest sectors in the economy and one where both consumers and frontline workers are starting to interact with AI in real ways. As the 2025 holiday season is in full swing, Rachel Brown on my team looked at new data on how AI is showing up in retail: from what shoppers are doing with it, to how it’s changing day-to-day work on the floor. Shoppers are using AI and converting at higher rates Nearly 60% of U.S. adults report using AI to help them shop this year. Some use it to compare prices. Others turn to tools like ChatGPT for gift ideas or product reviews. One signal that stood out: shoppers who land on retail sites via an AI assistant are 38% more likely to make a purchase (Adobe Analytics). That could reflect better targeting or that consumers are turning to AI when they already have high intent to buy. Even though most online purchases now happen on mobile, the vast majority of AI-generated traffic is still coming from desktops. That may change as interfaces evolve. AI is shaping how people expect to shop Consumers are getting used to more conversational search. Some even say they trust AI more than friends for product advice (Cian, 2025). But they also express concerns around scams, data privacy, and losing the “human touch.” That presents a real design and trust challenge for retailers. There’s a fine line between providing real value and being seen as using AI to optimize margin at the customer’s expense. On the retail floor, AI is starting to augment AI is showing up in inventory systems, virtual assistants, and mobile tools for frontline workers. Lowe’s, for example, is using its MyLow Companion to give associates real-time answers on products or stock without needing to radio for help. In addition to adding tools, AI is changing roles. A survey of employers found 62% plan to retrain or upskill retail workers for new tasks as AI adoption increases (TotalRetail). One case worth watching: Ikea. When call center jobs were automated, they retrained 8,500 workers to become virtual interior design advisors. That team generated $1.4B in revenue in 2022 alone (Reuters). What this tells us about AI and frontline work It’s early, but retail offers a useful testbed for AI’s broader impact on consumer-facing industries. The risks are real. But we’re also seeing evidence that, with investment in training and thoughtful role design, AI can support both better customer experiences and new forms of frontline work.

The most valuable ad slot in retail might not be on a shelf, but inside a chatbot. OpenAI just forecast $102B in ad revenue by 2030. Some retailer media networks might see that as a threat, but the smart ones see opportunity Great to have the chance to kick off the IAB Australia's new 'Perspectives on Retail Media' series with a piece on why AI is retail media's next growth engine. The core argument: AI isn't coming for retail media. It's coming to supercharge it. But only for the retailers and advertisers who move now. A few numbers worth sitting with: 🛒 OpenAI's ad revenue is forecast to jump from $2.4B this year to $102B by 2030. Halfway there still makes ChatGPT a top-five global ad platform. 🛒 Google says some brands using its AI ad tools are seeing up to 80% sales lifts. 🛒 WARC puts agentic commerce at $136B this year, heading to $1.7T by 2030. Most of that AI ad spend will likely be incremental or come out of search, not retail media directly. But there's a second-order effect. If shoppers start product discovery inside ChatGPT, Google's AI Mode, or Perplexity instead of on a retailer's site, retail media's growth ceiling quietly drops. Budgets don't shrink overnight. They just stop compounding. Here's where Australia is already getting interesting. Woolworths Supermarkets launched Olive (powered by Google's Gemini) earlier this year. Bunnings followed weeks later with Buddy, an agentic assistant that builds your deck project from a photo. Both are live. Both are being marketed as better shopping experiences. They're also the most brand-safe, first-party, high-intent ad environments in the country. The strategic question stops being "does our AI assistant improve CX?" and starts being "how do we monetise it without breaking the trust that makes it work?" The infrastructure is already forming. Criteo is building the bridge between retailer chat experiences and sponsored product surfacing. Thrad has launched a product specifically to help retailers monetise their AI assistants. Retailers who define the rules of in-chat advertising on their own terms will own this. The ones who wait will inherit whatever Amazon, Alphabet Inc. and OpenAI decide is fair. For advertisers, the shift is smaller but just as urgent. Product content needs to answer questions, not just match keywords. And last-click attribution will undercount everything AI touches, because conversational discovery sits earlier in the funnel than the attribution models were built for. Push for incrementality. The early-mover window is open. It won't stay open forever. Thanks to Gai Le Roy, Lachlan Brahe and the IAB Australia Retail Media Council for letting me share my thoughts. Full piece linked in the comments 👇 #RetailMedia #CommerceMedia #Advertising #RMN #Retail Woolworths Group Wesfarmers Wesfarmers OneDigital ChatGPT Claude Anthropic

Quick commerce might create new rails for fashion in India. But AI is about to rewrite the stack. It won’t just improve margins or automate workflows. It will reshape how demand is created, what gets made, and how we buy. Here’s my prediction: 1. Search becomes intent-led Nobody wants to scroll through 400 SKUs. AI will learn your taste, body, budget, event, and mood, and surface five things that just work. Think: Spotify-style discovery, but for clothes. Discovery becomes contextual, not chaotic. We’re already seeing this in early interfaces like Perplexity’s shopping copilots. 2. Assortments get micro-targeted Massive catalogs are a liability. AI lets brands adapt SKUs dynamically, by user, region, season, even returns history. Shein scaled fast fashion through supply speed, but never cracked fit. Newme is flipping the model by doing weekly drops of 10–15 SKUs based on real-time feedback As merchandising behaves like content, inventory becomes a live system. 3. Returns are engineered out Returns were the biggest margin killer. Now they’re a solvable product problem through predictive sizing + fit-tech + try-at-home delivery. Zalando and H&M are already running fit-tech integrations + virtual try-ons at scale. Fit-tech will become table stakes. 4. Supply chains go real-time From design to drop to replenish to clear. AI enables live demand forecasting, smarter markdowns and faster reaction cycles. Urbanic, Zara, and Myntra are tightening feedback loops using browsing + returns + trend signals Fashion will respond to signals, not seasons and less dead stock will lead to better margins. 5. Shopping shifts from search to recommendation Shopping will shift from browsing to context-driven nudges. AI copilots will shop with you, not for you. Voice-first agents are already live. AI doesn’t just improve conversion: it changes the loop. The next generation of fashion brands will scale through personalization, fit precision, intelligent curation, and habit-forming UX Fashion will live at the intersection of fast-moving infrastructure and intelligent systems. This wont change how we buy. It will change what gets made.

The Post-Smartphone Customer: Beyond the Screen 📲 Jony Ive and Sam Altman are betting against 17 years of digital strategy. Every marketing leader needs to pay attention. For over a decade, we built customer experience (CX) for the smartphone: tiny screens, quick taps, and app isolation. This new AI-powered companion is "contextual, continuous, and outcome-oriented." This is not just a hardware change; it is a fundamental disruption to marketing and CX design. 👉🏻 The shift is from "Screen-First" to "Experience-First." When the phone disappears, so does your app icon. Companies can no longer rely on visual real estate to win. The goal shifts from getting a tap to delivering an outcome seamlessly. Impact on Customer Experience: 1️⃣ The Zero-Click Economy: Your product interaction must be conversational and automated. If a customer needs to book a flight, the AI should handle it based on context ("I need a flight to Paris next week") without opening your airline app. Success is defined by an immediate, automated solution. 2️⃣ Brand Voice is Your New Interface: In a screenless world, your brand's personality, tone, and reliability are the interface. Marketers must invest heavily in defining the AI persona that represents their brand. The voice of your bank will handle sensitive transactions; it needs to be trustworthy and precise. 3️⃣ Data Strategy must be Proactive: The AI companion operates based on a continuous flow of context. Brands must design systems that feed relevant, real-time data to the AI before the customer asks. This requires moving beyond simple purchase history to predicting intent based on external context. For instance, a retailer needs to know the user's upcoming holiday plans to proactively suggest packing lists via the AI. This moment is the strategic window to define the winners of the post-mobile era. The best brands will redesign their entire service layer to integrate with an intelligence-driven companion. The losers will be stuck chasing clicks on a screen that no longer matters. #customerexperience #AI #futureofmarketing

A Zendesk study in 2024 revealed something striking: 83% of leaders in India believe traditional customer experience will be largely replaced by AI-driven interactions within the next three years. 𝐇𝐞𝐫𝐞’𝐬 𝐭𝐡𝐞 𝐭𝐡𝐢𝐧𝐠, 𝐭𝐡𝐨𝐮𝐠𝐡: 𝐀𝐈 𝐚𝐥𝐨𝐧𝐞 𝐢𝐬𝐧’𝐭 𝐭𝐡𝐞 𝐮𝐩𝐠𝐫𝐚𝐝𝐞. 𝐑𝐞𝐥𝐞𝐯𝐚𝐧𝐭, 𝐚𝐜𝐭𝐢𝐨𝐧𝐚𝐛𝐥𝐞 𝐜𝐨𝐧𝐭𝐞𝐱𝐭 𝐢𝐬. For years, customer experience in financial services has been built around information and standardisation. Early digital efforts focused on moving physical workflows online. Over time, the shift moved to digital CX itself. Being a regulated industry meant familiarity often took precedence over creativity, and personalisation rarely went beyond addressing a customer by name. With AI, that lens begins to change. Financial institutions already sit on large volumes of data about customer behaviour. The real opportunity lies in making sense of that information and translating it into relevant actions. This is the next wave of personalisation that AI can support. AI has the ability to interpret signals around behaviour, timing, history, intent, and even hesitation and convert them into interactions that are meaningful. Done well, this moves systems from being reactive to being anticipatory. It was with this thinking, and a clear intent to make finance simpler for customers, that we launched AI Nudges on the ABCD App. Each nudge translates data into an insight, a financial tip, and a relevant next action. SimpliFi, our AI assistant on the ABCD App, responds to customers and nudges them toward healthier financial habits. You can experience this across our Spend, Health, and Credit tracks, a live example of moving from information to interaction. As fintech continues to adopt AI, the winners won’t be the ones who automate the most. They’ll be the ones who use context to help customers make better choices, at the right moments. 𝐁𝐞𝐜𝐚𝐮𝐬𝐞 𝐢𝐧 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝐩𝐡𝐚𝐬𝐞 𝐨𝐟 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞, 𝐜𝐨𝐧𝐭𝐞𝐱𝐭 𝐰𝐨𝐧’𝐭 𝐛𝐞 𝐚𝐧 𝐞𝐧𝐡𝐚𝐧𝐜𝐞𝐦𝐞𝐧𝐭. 𝐈𝐭 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐭𝐡𝐞 𝐞𝐱𝐩𝐞𝐜𝐭𝐚𝐭𝐢𝐨𝐧. #ABCD #AI #Fintech #CX

Black Friday has evolved from panic at the disco store chaos to 24/7 online browsing, but this year marks a different shift: it's the first holiday season where AI is officially part of the shopping ritual. 🛒🤖 Simon-Kucher reported that 54% of consumers plan to use AI for holiday shopping, mostly for product reviews, comparisons, price tracking, and gift ideas. At the same time, 46% say they won’t use AI because they still want a human touch in gift-giving. https://lnkd.in/e97HQKcF That tension is fascinating with tech efficiency colliding with emotional intent. The adoption gap also follows a predictable pattern: Gen Z and Millennials lean in, while Gen X and Boomers hold back. No surprises there. Here's what's interesting to me: 1️⃣ Holiday shopping is now a stress test for retail AI. The past month of reporting shows retailers’ recommendation engines, AI search layers, dynamic pricing systems, and optimization models are all under heavy strain during this holiday shopping season. This is the first real-world trial of whether their AI infrastructure can handle both the volume and the expectations. 2️⃣ The purchase funnel is quietly being rewritten. In IAB Research published in October on AI x shopping, we found 57% of consumers use AI for product comparisons, 53% for product-specific questions and 53% for price tracking and deals. https://lnkd.in/euUFnFGW Deloitte's recent study on AI's effect on holiday shopping also noted price tracking highly at 56% of their study. https://lnkd.in/eT8NkjbT Awareness ➡️ Consideration ➡️ Conversion now sees the consideration phase being collapsed with AI. 3️⃣ The center of gravity is shifting from traditional ads to product data. The most meaningful change isn’t a new ad unit. It’s that brands are now optimizing product data, metadata, structured content, images, and reviews to ensure brand visibility in AI platforms. Visibility now depends on how “AI-ready” your catalog is. 4️⃣ Yes, AI-driven shopping is up, but spending patterns are more complicated. Consumers plan to spend 6% more this year, but Simon-Kucher says this is mostly due to tariffs and higher prices, not because they’re buying more. 5️⃣ And with AI in the mix, trust matters even more. This season is already seeing issues with price camouflage, deal inflation, and scams, a reminder that “AI-powered shopping” needs transparency and consumer protections to scale responsibly. ⭐️ The BIG PICTURE ⭐️ Black Friday 2025 isn’t just about commerce. It’s a preview of what AI-mediated shopping will look like when agents become the default discovery interface. And the brands that win won’t necessarily spend the most on ads...they’ll be the ones whose product data is structured cleanly enough for AI systems to understand and recommend. #ai #shopping #blackfriday

Black Friday 2025 wasn’t just about discounts. It was about AI quietly taking over the checkout. New data shows U.S. shoppers spent a record $11.8B online on Black Friday, up 9.1% vs 2024, while in-store traffic fell around 3–4% year over year. Online is booming. Physical retail is… complicated. At the same time, AI-driven traffic to retail sites exploded. Adobe and others report AI shopping assistants driving 600–800% more visits than last year, as consumers use chatbots and agents to find deals, compare prices, and decide what and where to buy. So what does this mean for AI + ecommerce? 1️⃣ AI is becoming the new homepage More journeys start inside assistants than on your .com. If your catalog, offers, and content aren’t structured for AI, you’re invisible at the moment of decision. 2️⃣ The unit of competition is the offer, not the website Algorithms don’t care about your beautiful hero image. They care about: price, margin, conversion, stock, relevance to that user, right now. 3️⃣ Stores shift from “traffic funnels” to “experience + fulfillment nodes” Foot traffic is down, but the role of stores in pickup, returns, service, and brand experience gets more strategic, not less. If you run an ecommerce brand, your 2025–26 playbook should include: 👉 AI-ready product data (clean attributes, rich descriptions, structured feeds). 👉 Offer architectures designed for algorithms (bundles, dynamic promos, post-purchase cross-sell rails). 👉 New KPIs: not just “sessions” and “ROAS”, but how often you win the AI comparison when a shopper asks, “What’s the best option for me?” Black Friday just confirmed it: the battle for ecommerce is moving from “who gets the click” to who wins the AI recommendation.

Forever 21 is using AI models in their online shop. This video of the model showcasing the clothing piece is AI generated. The photos look uncanny too. Is this a real person? Is the person real, but photos of clothing items are added? Does it matter? When I lived in Williamsburg, for a few years Amazon had a photo studio close by. A conveyor belt of fashion models and a warehouse of endless new clothing items. The metric, I assume, was clothing items per hour. Well, now that's infinity. Zalando makes "digital twins" of models to make marketing photos in infinite new settings to keep up with latest trends. In Q4 last year, they said 70% of editorial campaign images were AI-generated. I'm sure soon it will be 100% and they'll also move past digital twins to digital models. They are not alone. AI generated advertising creative is a solved problem. Shein is notorious for adding thousands of new products every day. That means thousands of real-world photos to showcase them in the catalog. But not for long. And the next thing is going to be tens of thousands of new products every day that don't exist at all. Digital clothes, worn by digital models.