The Rise of Agentic AI and the Coming Disintermediation of Retail
The holiday shopping season of 2025 is revealing a seismic shift in consumer behavior, one not driven by traditional marketing but by a new class of digital helpers: agentic artificial intelligence. These autonomous systems, which can act on a user’s behalf from research to final purchase, are reshaping the fundamental economics of retail. They threaten to overturn long established relationships between brands, multibrand retailers, and consumers. As consumers increasingly begin their shopping journeys with general AI assistants like ChatGPT or Google’s AI enabled search, the traditional marketing and sales funnel is already being upended. In some cases, AI now accounts for up to a quarter of all referral traffic to certain retailers, signaling a monumental transformation in discovery and attribution.
Agentic AI systems are designed to go beyond simple product suggestions, integrating memory, reasoning, and tool use to execute complex, semi or fully autonomous actions across the entire shopping journey. This evolution from basic generative AI tools, which 30 percent to 45 percent of US consumers already use for product research, is forcing industry leaders to confront a high stakes dilemma. At one end of the disruption spectrum, agentic AI could merely disrupt the top of the funnel, making paid search less attributable. At the other, agents could entirely disintermediate retailers, becoming next generation marketplaces that control transactions, compress margins, and capture invaluable customer data, effectively relegating traditional merchants to little more than fulfillment mechanisms.
The Three Classes of Retail AI and Their Distinct Threats
The emerging AI landscape is currently defined by three distinct types of agents, each possessing unique implications for the retail ecosystem.
The greatest immediate challenge comes from third party “objective” agents such as Perplexity and Gemini. These platforms crawl retail sites, aggregate listings, compare prices, and synthesize reviews to deliver agent curated product answers. This rapid acceleration of offsite discovery is profound; shopping referrals from platforms like ChatGPT have multiplied by over seven times in the US in the past year. Retailers who resist this trend risk losing visibility, but those who engage without a robust, differentiated value proposition risk becoming commoditized data sources.
In response, retailers are developing their own on site agents. These proprietary AI assistants, exemplified by Amazon’s conversational shopping assistant Rufus or the Brazilian giant Magalu’s Lu in WhatsApp, are designed to enhance conversion within the retailer’s own ecosystem. A key advantage for these retailer owned agents is the collection of proprietary data, including return rates, expert reviews, and comprehensive purchase histories, which generalist third party agents cannot access. Amazon, a pioneer in this space, projects that its on site assistant could boost annual sales by an extra $10 billion.
Finally, a few retailers are building off site agents to extend their influence beyond their proprietary inventory. Amazon’s “Buy for Me” agent, for instance, can make purchases on other brands’ sites. This strategic maneuver underscores the competitive pressure, as the same retailers restrict other third party agents from scraping their own proprietary listings.
Retailer Trust as a Short Term Competitive Moat
The current battleground provides a short window of opportunity for retailers. Shoppers have expressed a significant preference for retailer run agents, reporting that they trust them three times more than third party agents. This trust gap, however, is likely to narrow as agentic technology matures and consumers become more accustomed to automated transactions. Retailers must rapidly develop sophisticated on site capabilities that leverage this trust advantage before it erodes.
The core of a winning AI strategy must be rooted in customer intent and purchase complexity. For simple, spec defined shopping missions, the most disruptive agents will focus on where to buy specific items. For highly considered shopping, like complex home improvement projects, AI’s value is in time and cost savings. Home Depot, for example, is leveraging its deep product and project expertise to create “Magic Apron,” an AI companion that offers specialized support, drawing high value customers onto the site for complex purchases.
In other areas, collaboration over competition is the necessary path. Alliances, such as those forged between OpenAI and major players like Walmart and Shopify, allow retailers to exert influence over the emerging rules of engagement. By partnering, retailers can negotiate terms that retain ownership of critical customer data and purchase signals, or ensure the use of their own checkout gateway, maintaining control over the final mile of the transaction.
Strategic Imperatives for the Agentic Era
To prepare for 2026 and beyond, leading retailers must make three strategic moves now to protect their market position and revenue streams against the forces of disintermediation.
Protecting the Customer Moat. The primary defense against third party agents siphoning off high value, direct traffic is to create irresistible reasons for consumers to visit the retailer’s own site. This means introducing exclusive products, offering premium bundles, rewarding direct purchases with loyalty point multipliers, or reserving value added services, such as installation or protection plans, solely for on site transactions. Best Buy, for example, allows its product data to appear on AI platforms but reserves its proprietary Geek Squad services for its own ecosystem.
Reinventing Retail Media Monetization. With direct site traffic at risk, the $65 billion retail media industry, currently reliant on on site sponsored search, must evolve. Metadata is becoming the new advertising asset. Retailers must collaborate with brands to structure product catalogs in a way that ensures third party agents surface their content accurately and place them on the agents’ short lists. As AI rewires search, new monetization models will emerge on site, including sponsored agent recommendations and agent influence fees. This is already visible with Amazon serving sponsored ads within its Rufus chats and Google incorporating sponsored products into its AI Overviews. The key will be to prove to brands that these new advertising opportunities offer superior value compared to traditional keyword search.
Retaining Control Over Data and Fulfillment. Retailers must avoid being relegated to a “dumb fulfillment pipe.” They must use watermarking, tiered access to critical software, and tracking to preserve the value of first party data, even when third party agents close transactions. It is paramount to maintain ownership of last mile logistics and, if possible, the checkout process. If agents must handle transactions, partnerships should be structured to retain full visibility into consumer behavior and purchase signals, preventing the wholesale loss of customer intelligence.
The core challenge presented by agentic AI is a shift in consumer loyalty away from brands and retailers toward simple, efficient outcomes. The next generation of enduring retail leaders will be those who can make their unique value proposition apparent to both the human shopper and the autonomous agent, ensuring their survival in an increasingly transparent and comparison fueled marketplace. Their actions now will determine the rules for everyone else.
