How AI Will Shape Consumer Trends

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.

Your marketing playbook just expired. AI has rewritten every rule while most brands are still playing by 2019 strategies. The companies adapting fastest aren't the ones with bigger budgets or better tech teams. They're the ones who understand how AI has fundamentally changed customer behaviour. Here's what the winners are doing differently: 1. The New Search Landscape: SEO meets LLM Traditional keywords are the past. Conversational queries are everything. Example: REI shifted from keyword-stuffed descriptions to contextual content addressing specific use cases, increasing AI-summarised results visibility by 47%. Reality check: Google's AI Overviews now appear in nearly half of all search results. 2. AI Assistants as Gatekeepers Your brand must be recognised by AI as a category leader to enter consideration sets. Example: Best Buy organised product attributes to match natural customer questions, achieving 35% increase in organic traffic from voice searches. The shift: AI now filters options before consumers see them. 3. Attention Compression Consumer attention spans shrink as AI summarises everything instantly. Action point: Front-load your value proposition in all communications. The pattern: Customers want to digest information about products quickly, not hunt to understand what’s in it for them. 4. Hyper-Personalisation Without Creepiness AI enables true 1:1 marketing at scale, but only if you balance customisation with transparency. Example: Sephora's Skin IQ tool provides personalised skincare recommendations, driving 35% growth in skincare sales. The principle: Use preference-based content sequencing with full transparency about data usage. 5. Multi-Modal Content Strategy AI-driven consumers expect seamless experiences across text, voice, and visual channels. Example: Domino's "AnyWare" approach allows ordering through voice assistants, text, social media, and apps. The requirement: Build centralised content hubs ensuring consistent messaging across all channels. 6. The Human Advantage As AI handles transactions, authentic human connection becomes your competitive edge. Example: Lululemon's in-store community events resulted in 25% higher repeat purchase rates compared to online-only shoppers. The opportunity: Community-building programs generate 23% higher customer lifetime value. The brands that thrive won't be those with the most sophisticated AI tools. They'll be the ones that use AI to enhance human connection rather than replace it. Which of these shifts will you implement first? ♻️ Found this helpful? Repost to share with your network.  ⚡ Want more content like this? Hit follow Maya Moufarek.

The AI shopping revolution is happening faster than we think! New research from Cognizant reveals that by 2030, AI-enthusiastic consumers will control 55% of all purchasing activity - that's $4.4 trillion in the US alone. But here's what caught my attention:- consumers aren't embracing AI equally across the shopping journey. The surprising pattern:- LEARN phase:- High comfort (people love AI for product discovery). BUY phase:- Major hesitation (nobody wants AI clicking "purchase" for them). USE phase:- Strong rebound (consumers want smart products that maintain themselves). This creates a fascinating paradox - we're happy to let AI recommend what to buy and help us use it, but we draw the line at the actual transaction. The business implications are massive:- Companies that win the "Learn" phase today will build the trust needed to eventually win the "Buy" phase tomorrow. It's not about forcing AI into purchasing decisions - it's about earning consumer confidence through value in discovery and post-sale support. Three waves ahead:- 2025-2027: AI-powered discovery takes off. 2027-2029: Smart products and aftersales become the battleground. 2030+: The "agentic internet" where AI agents negotiate on our behalf. For those of us building agentic AI solutions, this research validates what we're seeing in the field - consumers want AI that amplifies their decision-making, not replaces it. The question isn't whether this transformation is coming? It's whether your business will be ready? What's your take? Are we moving too fast toward AI-driven commerce, or not fast enough? #AI #AgenticAI #Ecommerce #DigitalTransformation #ConsumerBehavior #BusinessStrategy #Innovation #RetailTech #CustomerExperience #FutureOfCommerce #AIAgents #MarketResearch

📈 New Adobe data just dropped: generative AI traffic to retail sites surged 4,700% year-over-year in July 2025. But it's not the growth, while impressive, that has me thinking...it's what happens next. Here's what caught my attention and what I think marketing leaders need to pay attention to: AI-referred shoppers spend 32% more time on sites, view 10% more pages, and bounce 27% less. These aren't casual browsers. They're research-driven consumers who arrive knowing exactly what they're looking for. Three things brands need to start thinking about, because the shift in consumer behavior in the Agentic Web is happening fast: - We're optimizing for the wrong thing. 73% of AI users cite LLMs as their primary research source. Keywords won't cut it anymore. Brands need to be the authoritative source that AI systems reference when customers ask questions. - The attribution models are broken. AI traffic converts 23% less but generates 84% more revenue per visit than six months ago. These customers research through AI, then convert elsewhere. How are we tracking that journey? - The infrastructure shift is real. Consumer Electronics and Tech lead in AI visit share because complex purchases benefit most from AI research. But every category will follow. The question isn't if—it's when. For brands who have built great visibility in the current digital economy and are wondering what is happening to their metrics, It feels like the early days of digital all over again, equal parts terrifying and exhilarating. We're not just adding another channel. We're witnessing the emergence of the Agentic Era where AI agents become the new front door to discovery. The brands that recognize this shift and adapt their content, measurement, and customer journey strategies now will own the next decade. Read the full insights from our team at Adobe Digital Insights: https://lnkd.in/g2mGVGud What are you seeing in your data? How are you preparing for this shift? #MarketingStrategy #GenerativeAI #CustomerJourney #DigitalTransformation #AEO #GEO #AISearch #AdobeLLMOptimizer

If AI Doesn’t Recommend You, You Won’t Be Found AI is now the start for high-intent shopping journeys. This isn’t a quirk. It reflects a structural shift in how consumers shop. Adobe reports AI-driven retail traffic is up 1,200% YoY, and this traffic arrives more engaged, with lower bounce rates, and is closer to purchasing. Consumers no longer search “Nike vs Asics”. They ask: “Best running shoe for 20km/week on concrete under $200?” By the time a shopper reaches your site, their decision is mostly made. The journey becomes: AI research → AI shortlist → PDP → checkout The homepage is no longer the front door, the PDP is. This is a material shift and creates a set of fundamental changes for how brands operate. I see three areas that all brands should be considering: 1. Winning the LLMs understanding (AEO) LLMs reward brands with: • High-quality, recent reviews (vendors like Yotpo become invaluable) • Expert & creator consensus (independent authoritative voices) • High-signal open-web content (Reddit, YouTube, TikTok, comparison sites) • Machine-visible loyalty (“my go to”, “I always repurchase”) • Structured product data (fit, materials, ingredients, performance, compatibility, occasion) This is how you earn more AI-qualified traffic. 2. Winning the consumer’s search intent To be listed, you must shape how consumers describe their needs when they ask AI. This comes from: clear category framing, distinctive brand assets, credible creators, sustained proof, and PDPs that explain why this product is the right solution. Influencing the query dramatically increases the chance of AI pointing to your brand. 3. Brands need a different team to win AI-driven traffic If discovery now happens in AI, your resourcing must shift with it. My three predictions for how this impacts resourcing are: a) I don’t see SEO easily evolving into AEO. SEO was about optimising your site for Google. AEO is about shaping the open web so that AI models understand, trust, and recommend you. Different skills. Different instincts. Different people. b) Community management returns, but as reputation engineering. Not posting memes or moderating comments. You need operators who can spark high-signal conversations, activate advocates, and generate the retention cues (“my third bottle”, “I always repurchase”) that models weight heavily. c) Brand Marketing & PR will wrestle budget from Performance Marketing. Performance Marketing dominated the last decade because it had clean ROI. You can’t buy your way into an LLM recommendation, you earn it. In an AI-driven funnel, Brand suddenly has a direct, measurable impact on discovery and revenue. Performance won’t vanish, but it loses its monopoly on growth. Retailers who don’t rewire their talent for this reality won’t just fall behind; they won’t show up at all.

GenAI has the fastest adoption curve in consumer tech history—and it’s forcing a rethink of how brands influence decision journeys. ChatGPT reached 100M users in ~2 months, versus more than 4 years for Facebook and ~2.5 years for Instagram. BCG's Center for Customer Insight research shows this speed has already translated into scale, with GenAI usage reaching roughly half of consumers in some markets and two-thirds using it weekly. The real shift is that GenAI is no longer just an information source. It’s becoming a decision interface that actively shapes what consumers buy. Shopping-related GenAI use grew 35% between February and November 2025, with consumers relying on it to compare options, clarify tradeoffs, and build confidence before they buy. For frequent users, GenAI is already among the most influential touchpoints in the purchase journey. This shift puts brand consistency and AI readiness at the center of competitive advantage. Consumers now stitch together AI, search, social, in-store, and other brand touchpoints—and expect the answers to line up. That raises the bar on brand identity:  • Facts, positioning, and proof points must be consistent across every surface AI draws from.  • Brands need Answer Engine Optimization (AEO) so information can be interpreted, compared, and returned clearly when consumers are deciding. The businesses that adapt most quickly will secure visibility and preference in the increasingly frequent moments when GenAI influences demand and choice. Read more on global trends and stats, as well as direct consumer quotes: https://lnkd.in/eV23VAEp Greg McRoskey Lauren Taylor Ben Eppler Gabriela Barrios Karen Lellouche Tordjman #GenAI #ConsumerInsights #CustomerExperience #RetailInnovation #MarketingLeadership

I remember presenting to the Bed Bath & Beyond Board in the mid-2000s and walking through how customer behavior was changing. At the time, the shift was driven by search. Customers were no longer starting their journey in a store or with a circular. They were: 🔎 searching on Google 🔎 reading reviews 🔎 asking friends 🔎 and then deciding whether to visit a store or buy online. That model reshaped retail over the next decade. Today, we’re watching another front-door shift.....this time driven by AI and algorithmic discovery. Consumers are increasingly starting with: 👉 “Which air fryer should I buy?” 👉“What’s the best moisturizer for sensitive skin?” 👉“Where can I get this delivered fastest?” And instead of scrolling through pages of results, they’re receiving synthesized answers, ranked recommendations, and direct purchase paths. The implication isn’t just a marketing shift. It’s a structural one. If AI systems and social platforms are now mediating discovery, then: ➡️ product data quality ➡️ content depth ➡️ review signals ➡️ and fulfillment reliability... .....become inputs not just for SEO, but for machine decisioning (now GEO/AEO). I’ve seen this pattern before: when the front door moves, the retailers who recognize it early redesign their operating model around it. The ones who don’t often keep optimizing the last era’s traffic patterns, until they wonder where demand went. #RetailStrategy #AIDrivenCommerce #DigitalTransformation #CustomerJourney #FutureOfRetail

By July 2025, traffic from generative AI to retail sites in the U.S. surged 4,700%. Consumers landing from ChatGPT, Claude, and Perplexity links are:   ➡️ Spending 32% more time on site ➡️ Viewing 10% more pages ➡️ Bouncing 27% less often   And Adobe’s latest analysis is clear: AI isn’t just shaping how products are described. It’s shaping where shoppers go, what they trust, and how they decide.   We’re not in a “future of shopping” moment. We’re in a present where AI is becoming a distribution channel.   These are snapshots of how discovery, trust, and conversion are being redefined.   💡 The AI shopper isn’t searching the way we think. They’re not typing keywords and browsing pages of results. They’re asking, and trusting, an answer.   But that means sellers need to rethink how they structure their catalogs and content:   🔹 AI is not SEO 2.0 It doesn’t rank results, it interprets and recommends. Your data isn’t about keyword stuffing, it’s about credibility and clarity when summarized by a model.   🔹 Trust is compressed Instead of spreading traffic across ten blue links, AI concentrates attention on one or two recommendations. Being the “chosen” option is the new top of search.   🔹 Catalog = Language Listings are no longer just for human eyes. They’re a language that models parse to decide what to highlight or ignore. If your attributes aren’t structured, you’re invisible.   🔹 The invisible margin In AI-driven answers, the model might push a multipack, bundle, or alternative configuration. If your catalog isn’t built to support those, you hand that margin to someone else.   🔹 The cultural flip Shopping used to begin with an intentional search. Now, AI starts the search for the shopper. Discovery is becoming mediated, and the assistant is often the first filter between you and the buyer.   The world doesn’t just need better ad campaigns. It needs sellers who understand how AI “reads” a listing and how that interpretation changes sales velocity and margins.   That’s the strategic gap: sellers optimizing only for Amazon search will miss the parallel channel AI is building across retail.   The takeaway: Generative AI isn’t just a productivity tool. It’s fast becoming a demand driver. If your catalog isn’t ready to be “read” by AI, you’ll be invisible in the very places shaping the next wave of retail traffic.   #AmazonSellers #AmazonAI #GenerativeAI #MarketplaceGrowth

It was the best of search, it was the worst of search. It was the age of instant answers, it was the age of disappearing links. It was the epoch of personalization, it was the epoch of lost discovery. It was the season of AI-driven clarity, it was the season of algorithmic opacity. It was the spring of conversational commerce, it was the winter of ten blue links. According to Adobe Analytics, U.S. retail websites saw a 1,200% increase in traffic from generative AI sources between July 2024 and February 2025. During the 2024 holiday season alone, this figure jumped 1,300% year-over-year, with Cyber Monday traffic spiking 1,950% compared to 2023. Consumer adoption is driving the shift. A survey of 5,000 U.S. shoppers found that 39% have used generative AI for online shopping, with 53% planning to do so this year. Users rely on AI for product research (55%), recommendations (47%), deal-hunting (43%), gift ideas (35%), product discovery (35%), and shopping list creation (33%). AI-generated traffic isn’t just growing—it’s more engaged than traditional sources. Visitors spend 8% more time on-site, view 12% more pages per visit, and have a 23% lower bounce rate than those from search or social media. Conversational AI interfaces are improving consumer confidence and making online shopping more intuitive. That said, conversion rates for AI-driven traffic still lag behind traditional sources by 9%, but the gap is closing. In July 2024, the difference was 43%, signaling growing consumer trust in AI-assisted purchases. Another key insight: AI-assisted shopping is happening on desktops, not mobile. Between November 2024 and February 2025, 86% of AI-driven traffic came from desktop users—suggesting that consumers prefer larger screens for complex, AI-guided shopping experiences. While the numbers are compelling, they only hint at what’s coming. AI-driven agents won’t just assist shoppers—they’ll shop for them. The way consumers find, evaluate, and purchase products is shifting fast, and this data is just beginning to tell the story. -s

AI assisted shopping is already normal. Our recent IBM Institute for Business Value 2026 Consumer Research Study ‘Own the agentic commerce experience - Consumers are ready’ found that: Nearly three quarters of consumers still shop in store. But AI is quietly reshaping the front end of decisions. ▫️41% use AI assistants to research ▫️33% use them to scan reviews ▫️31% use them to search for deals AI usage spans far beyond novelty. ▫️45% say they have used AI to personalise or design products ▫️33% to evaluate trade offs ▫️31% to track orders ▫️26% to support sustainability choices Adoption is particularly strong in Asia. AI assisted shopping usage sits at: ▫️29% in Singapore ▫️28% in India ▫️28% in the UAE ▫️26% in China What stands out is how unremarkable this now feels to consumers. AI is not the destination. It is already the quiet helper. ——— The IBM #IBV is the global number one rated consulting thought leader that delivers research led insight at the crosshairs of business, technology and society. Sign up to the IBV here: https://lnkd.in/eav5Dc6R Our Consumer 2026 report combines surveys of 18,000 consumers across 23 countries and 200 retail and consumer products executives across 11 countries to examine how AI enabled shopping, trust and precision spending are reshaping commerce. Read the report here: https://lnkd.in/eCvGijDa The paper was authored by me and Dee Waddell, Richard Berkman, Hiroshi Hasegawa, Carlos Capps, Sabu Gopinath, Joe Dittmar, Milad Safadi, Jeremy (Jez) Bassinder, Shantha Farris and led by the inimitable Jane Cheung, our Global Leader for #ConsumerIndustries at the IBV. We are extremely grateful to the industry leaders who contributed to this report including Katherine Cullen of TheNational Retail Federation, Byron Ells of Sobeys, Matthieu Houle, CIO at ALDO Group, and Stanislas Vignon, Head of Insights at Louis Vuitton Moët Hennessy (LVMH), as well as the many other clients who were interviewed. Also the IBM contributors Hugo Catarino, Pierre Charchaflian, Kostas Didaskalou, Karl Haller, Mark Innes, Colm O'Brien, Mary Wallace, and the IBM Institute for Business Value team Sara Aboulhosn, Steve Ballou, Douna Daou, Kathy Martin, Thiago Sartori and Joanna Wilkins #AgenticCommerce #AIinRetail #ConsumerBehaviour #AI #Retail #ConsumerProducts #CommerceStrategy #Luxury #RetailInnovation #AICommerce #DigitalCommerce #CustomerExperience #ItsAGreatTimeToBeAnIBMer #IBMIBV #Consumer2026