Artificial Intelligence in Retail

Many business leaders that I’ve spoken to assume that their technological choices are invisible to consumers. In fact, the opposite is true when it comes to #GenAI! This means that business leaders need to factor in #consumer views front and centre when deploying this technology at scale. Yet there is little known on how consumers perceive GenAI. BCG’s Center for Customer Insight (CCI) sought to fix that with our latest work.   We surveyed 21,000 consumers from 21 countries on six continents, and they have a message to companies deploying new #AI and #generativeAI technology: “we see you”. Our study finds that over 80% of respondents globally are aware of GenAI, and nearly a quarter are already trying out this technology. The 80% is a staggering figure given how new this technology is. Secondly, there is an inherent polarization in consumer perceptions. While 43% of consumers are excited about the possibilities AI and GenAI present, 29% are worried about its potential downsides such as privacy concerns. Levels of enthusiasm vary from market to market – and here we find another surprise. Receptiveness to GenAI is entirely disconnected to the maturity of the market - in fact, markets like China, Indonesia and India see higher net positive scores on GenAI perception than US, France and Australia.   This means that companies need to adopt honest and objective communication with their consumers to generate trust as they deploy GenAI solutions at scale. Responsible AI is a mandatory consideration from day 1.   Read more in our new article, Consumers Know More About AI than Business Leaders Think: https://lnkd.in/g4CCgh9x.

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 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

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!

For many, AI has become synonymous with efficiency. Across industries, AI has proven its ability to reduce costs, streamline workflows, and deliver services faster and cheaper—whether it’s automating customer service, optimizing marketing campaigns, or enhancing sales processes. These productivity gains are invaluable and should undoubtedly be embraced. But focusing solely on productivity misses the bigger picture. The true potential of AI lies in its ability to drive top-line growth by powering innovation that resonates with consumers. Consumers Want AI-Driven Innovation The demand for AI goes beyond speed and savings. According to a survey by Prophet, 69% of consumers are excited about brands that use generative AI tools to improve their experience. This excitement reflects a shift in expectations: people aren’t just looking for brands that are faster or more cost-efficient. They’re looking for brands that innovate in meaningful, transformative ways—brands that redefine the customer experience and create entirely new value propositions through AI. To truly differentiate and grow, companies must go further by embedding AI into their core strategies for innovation. Here are three ways to do that: 1. Reimagine the Customer Experience AI offers unprecedented opportunities to personalize and elevate customer interactions. Generative AI, for example, can create hyper-personalized recommendations, design immersive virtual experiences, or enable entirely new ways for customers to interact with products and services. Think of AI not just as a tool for answering questions or speeding up processes, but as a catalyst for delighting customers in ways they’ve never experienced before. 2. Drive Breakthrough Product Innovation From drug discovery to sustainable materials, AI is enabling breakthroughs that were previously unimaginable. Companies that integrate AI into their R&D processes can bring truly novel products to market faster, setting themselves apart from competitors focused solely on incremental improvements. 3. Create New Business Models AI can help companies move beyond traditional revenue streams. For example, manufacturers can leverage AI-powered predictive analytics to shift from selling products to offering subscription-based services. Retailers can use AI to build immersive digital environments that blend physical and virtual shopping experiences. By using AI to rethink what they offer and how they offer it, companies can unlock entirely new growth opportunities. Leveraging AI for top-line growth requires more than just adopting the latest tools. It demands a mindset shift—a willingness to experiment, take risks, and think beyond the obvious. Bold leadership will define the winners of this new era.

AI + supply chain data cut food waste by 87% in 12 weeks Interesting stuff from Nestlé who worked with startups and partners to track short-dated stock across their supply chain. By identifying surplus early and redirecting it through redistribution partners, they cut edible food waste by 87% across 15 sites. All in under three months. Some thoughts reading this that can apply to lots of big business challenges; ➡️ Start with the problem: This began with a clear operational issue: waste. The solution was built around fixing that, not showcasing technology. Work across the system ➡️The right people were involved; Nestlé, Sustainable Ventures, Zest (formerly The Wonki Collective) and others. Everyone working towards the same outcome. ➡️Short and simple. Clear priorities, a short-term (effective) pilot. If the problem is real and the partners are aligned, you can move faster than you think. More on the article in the comments

Did you know that 40% of food produced never even makes it to a supermarket shelf? And 7x more waste happens during manufacturing vs at a retail level. That waste costs food processors £7.6 billion every year in the UK alone. At Climate Tech Time, Dini McGrath from Zest (formerly The Wonki Collective) shared how her team is optimising the unseen, using AI to empower food & drink manufacturers to take action against food waste. Here’s how they do it: 🔎 They offer real-time visualisation of waste streams ⚡ Smart identification of waste hotspots alerting you to when action needs to be taken 📉 Redistribution of surplus back to the industry or food charities (when it’s unavoidable) In a Nestlé pilot, their system redistributed 87% of edible ingredients from one factory in just two weeks. My take? This is a fantastic case study for how innovation can make sustainability profitable. 👏 🎥 Curious and want to learn more? Watch Dini’s full talk here: https://lnkd.in/dZ4Kk7sR #FoodWaste #ClimateTech #SupplyChains

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

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