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We\u2019ve held off on discussing AI as long as we could, but we\u2019re only human. It was <\/em>the topic of 2025 (not only in retail), and its impact on the industry\u2019s ecosystem looks set to expand even further in 2026. Agentic AI already is reshaping shopping behaviors, giving consumers a streamlined path to purchase but also potentially cutting some retailers and brands out of the consideration loop. Internal AI applications are promising to enhance everything from streamlining the supply chain to reducing returns. And even as AI becomes more ubiquitous, many of our forecasters are warning that retailers can\u2019t afford to lose the human touch.<\/em><\/p>\n Read on for expert predictions from leaders at Shopify, Deloitte, Commerce, Publicis Sapient and more on how AI in retail will evolve in 2026, and check out <\/em>Part 1<\/em> and <\/em>Part 2<\/em> of our 2026 forecast series to see what other trends will shape the year.<\/em><\/p>\n Agentic AI\u2019s ability to not simply provide recommendations but also complete transactions is being heralded as a major improvement to the online commerce experience, but many retail experts are concerned that it also will diminish retailers\u2019 roles \u2014 at least until they figure out how to be \u201cfound\u201d by AI agents.<\/em><\/p>\n \u201cThe biggest impact will be on discovering and decisioning. AI is going to sit between the shopper and the shelf \u2014 whether that shelf is physical or digital.<\/strong> Instead of typing \u2018best moisturizer\u2019 or scrolling endlessly, consumers will increasingly rely on AI to surface options, compare prices, check ingredients and personalize recommendations based on context \u2014 and the shopper\u2019s personal history.<\/strong> We can look forward to more curated experiences, higher conversion from personalized results and smarter replenishment and predictive commerce.\u201d \u201cAfter years of \u2018being everywhere,\u2019 the pendulum is swinging toward being consistent everywhere. Shoppers move fluidly between marketplaces, social feeds and storefronts, but they expect brands to show up with one identity. That means unified pricing, synchronized product content and context-aware messaging that feels personal, not patched together. AI is leading this necessity, with 58%<\/strong> of consumers now beginning product discovery on AI tools, and unified data orchestration will be the conductor behind this harmony. Imagine a homeware brand automatically swapping product imagery to match regional d\u00e9cor trends or a grocery retailer hiding unavailable items in real time across every channel.<\/strong>\u201d \u201cWhat excites me about 2026 is how retailers are moving away from a narrative of \u2018What can AI do?\u2019 to \u2018How do we redesign our business model around AI and value?\u2019 This is an unprecedented moment where everyone is learning in real time what agentic shopping and AI-driven commerce looks like. I believe the higher-ROI applications of AI will be those, like agentic commerce, that focus primarily on driving topline growth, rather than those that are limited to operational productivity alone. While streamlining operations is important, AI-driven solutions that enable new forms of customer engagement, digital discovery and sales growth will ultimately unlock the biggest wins.<\/strong> Done well, these applications do not just generate revenue. They also lay the groundwork for improvements in productivity and operational efficiency down the line.\u201d While AI first made its mark in the creative aspects of marketing, 2026 will see it expand into a widening array of operational areas \u2014 particularly in data-intensive functions such as demand forecasting and inventory management, providing deeper insights delivered in real time.<\/em><\/p>\n \u201cOn the operational side, AI will play a vital role in facilitating a necessary \u2018flight to profitability.\u2019 Retailers will harness AI for inventory and merchandising, predicting demand with greater accuracy to cut inventory carrying costs and redefining return policies by using algorithms to deny or apply charges to certain shoppers selectively. AI-driven workforce automation will optimize scheduling and automate repetitive tasks across fulfillment centers and stores, <\/strong>enabling retailers to address labor shortages and significantly reduce operating costs.\u201d \u201cThere\u2019s still so much opportunity when it comes to merchandise planning\/demand forecasting and data strategy. We will definitely be tripling down on the AI-enabled capabilities we offer for more accurate, nuanced and real-time inventory management<\/strong>, as well as for streamlined and secure data governance.\u201d \u201cAutomation of trade document processing, customs clearance and renewed efforts to apply technology to paper-based processes will be areas where AI will have a substantive impact on supply chain and logistics operations. This will be driven by increased funding available for customs enforcement, changing tariff rates and efforts to bring transparency to supply chains across the board.\u201d \u201cThe encouraging news is that technology has never been more democratized. The tools that once required enterprise-level budgets and dedicated teams are now accessible to businesses of all sizes.<\/strong> Take storefront experimentation: historically, smaller merchants couldn\u2019t run proper tests because they simply didn\u2019t have enough traffic to generate meaningful results. Now, with tools like Shopify\u2019s SimGym (now in research preview), they can use AI shoppers to simulate buyer behavior and stress-test changes before real customers see them. That levels the playing field in a profound way. When a smaller brand can get the same caliber of insights as an established retailer, it gives them the confidence to be brave, and I think that bravery will define the businesses that thrive in 2026.<\/strong>\u201d Concerns about the downsides of AI (yes, there are quite a few) fall into two general categories. One is of companies underinvesting \u2014 or not investing at all \u2014 in the technology, leaving them on the wrong side of a widening tech divide. Second, there\u2019s worry that consumers will begin to lose trust in their AI interactions. And as retailers know, it only takes a few (sometimes just one) screw-ups to lose a shopper for life.<\/em><\/p>\n \u201cI\u2019m most concerned about the widening gap between companies that know how to deploy AI effectively and those that don\u2019t. We\u2019re heading toward a two-speed retail economy: brands with modern data infrastructure and AI governance will accelerate, while legacy organizations will fall behind faster than they expect.<\/strong> Layered on top of this is consumer trust. If retailers over-automate, cut human support too aggressively, or use AI in ways that feel invasive, they risk brand damage at scale. The technology is powerful \u2014 but missteps will be visible immediately.<\/strong>\u201d \u201cThe \u2018AI Data Divide\u2019 is a major worry. While 90%<\/strong> of retailers are using or exploring AI, only a small percentage are prepared to scale it. Siloed, fragmented and poor-quality customer data could render enormous AI investments ineffective, resulting in poor customer experiences and inaccurate automation.<\/strong> Additionally, the rise of cyber threats poses a growing risk. The use of sophisticated AI by malicious actors, such as the creation of advanced \u2018deepfakes\u2019 to target executives or the development of polymorphic malware is anticipated to significantly escalate the risk and cost of cybersecurity across retail operations and supply chains.\u201d \u201cI\u2019m just deeply hoping that none of the AI platforms begin monetizing search results. Our data repeatedly shows consumers\u2019 concern with biased outputs, and if AI platforms monetize results, it will completely diminish the power of the shopping experience it\u2019s meant to facilitate<\/strong>.\u201d \u201cMy greatest concern as we look ahead to 2026 is how the rise of AI could unintentionally erode the essential human touch. Reddit is built on unfiltered conversations, genuine connections and shared experiences that only real people can bring. While we understand the power of AI to enhance and make discovery better, these tools must serve and empower organic, human-driven discussions, not overshadow them.<\/strong> In a landscape increasingly defined by algorithms and AI, it\u2019s still authentic human conversation that sparks discovery, refines consideration and ultimately converts interest into action.\u201d Don\u2019t miss Part 1 and Part 2 of our 2026 forecast series, focused on consumer trends and legislative priorities that will shape the year.<\/p>\n<\/p><\/div>\nGrowth of Agentic AI Could Erode Brand Loyalty<\/strong><\/h3>\n
\u2013<\/em><\/strong>Melissa Burdick, Co-founder and President, <\/em>Pacvue<\/em><\/strong><\/p>\n
-Al Williams, SVP and GM of B2C, <\/em>Commerce<\/em><\/strong><\/p>\n
-Brian McCarthy, Retail and Consumer Products Strategy Leader, <\/em>Deloitte<\/em><\/strong><\/p>\nInternal AI Applications Expected to Scale<\/strong><\/h3>\n
-Sudip Mazumder, SVP, Retail Industry Lead, North America, <\/em>Publicis Sapient<\/em><\/strong><\/p>\n
-Melissa Minkow, Global Director, Retail Strategy and Insights, <\/em>CI&T<\/em><\/strong><\/p>\n
\u2013Mike Babbitt, Head of Trade and Supply Chain Finance Origination, <\/em>Synovus<\/em><\/strong><\/p>\n
-Deann Evans, Managing Director, EMEA, <\/em>Shopify<\/em><\/strong><\/p>\nWhat Could go Wrong?<\/strong><\/h3>\n
-Nick Drabicky, SVP and GM, Client Services, <\/em>January Digital<\/em><\/strong><\/p>\n
-Sudip Mazumder, SVP, Retail Industry Lead, North America, <\/em>Publicis Sapient<\/em><\/strong><\/p>\n
-Melissa Minkow, Global Director, Retail Strategy and Insights, <\/em>CI&T<\/em><\/strong><\/p>\n
-Anna Haffner, Director of Large Customer Sales, <\/em>Reddit<\/em><\/strong><\/p>\n