For years, digital commerce revolved around optimizing the customer journey for human users: Better storefronts, better search functions, better marketing funnels. Search Engine Optimization (SEO) claimed to be the road to success.
Until recently, when a new participant entered the playing field: the AI agent. One that does not browse visually, respond emotionally or tolerate incomplete information: the AI agent.
AI agents are increasingly becoming intermediaries between consumers and retailers. And by taking this position, they are fundamentally changing how products are discovered and purchased online; forcing retail to adapt quickly.
Market projections explain why the topic is attracting so much attention. Bain & Company forecasts that agentic commerce could account for up to $500 billion in U.S. retail sales by 2030, a quarter of all eCommerce transactions. As a conclusion, Bain states that retailers must from now on serve both – human and AI agent customers.
Gartner also sees an evolution taking place at an enormous speed. The consultancy expects that 20% of all digital commerce transactions will be executed through AI-driven systems within five years from now. Other forecasts from McKinsey, Morgan Stanley and J.P. Morgan point in a similar direction and see AI-assisted purchasing moving rapidly toward mainstream adoption.
Consumers Already Use AI to Shop
For retailers, the time to act has come. Because the shift is accelerating rapidly. Today, fully autonomous purchasing is still rare but consumers are already integrating AI into their shopping behavior. McKinsey estimates that 63% of European shoppers already use AI tools to compare brands, prices and reviews, while more than half use AI to research products and categories.
The shift is particularly visible among younger consumers. Trust in AI-driven purchasing remains limited overall, but Gen Z and millennials are considerably more open to allowing AI systems to place orders on their behalf. Industry observers see this as an early indicator of broader behavioral change where more and more shopping decisions are AI-driven.
At the same time, AI is quickly becoming a preferred interface for product discovery. Surveys show that many consumers now turn to generative AI tools instead of traditional search engines when researching purchases.
The first retailers are already responding accordingly: AI shopping assistants such as Amazon’s Rufus or Walmart’s Sparky are already becoming part of everyday digital retail experiences.
The good news for retailers is that beside these first attempts for a deeper AI integration into retail, the playing field still is largely empty and the transition toward autonomous commerce will not happen overnight because payments, authentication systems and trust frameworks are still underdeveloped for fully automated transactions.
The near future will therefore most likely be defined by hybrid shopping journeys in which AI assists consumers rather than replacing them entirely. But even for that changing behavior, brands and retailers need to adapt their strategies.
A New Traffic Channel Is Emerging
For shopping center operators and retail destinations, this development has implications far beyond eCommerce. As AI increasingly shapes product discovery before consumers ever enter a store, physical retail environments will need to focus even more strongly on experience, service and brand differentiation. Areas where purely machine-driven commerce still has limitations.
One of the strongest signals comes from traffic data. According to Adobe Analytics, AI-driven visits to U.S. retail websites increased by more than 4,700% year-over-year in 2025. During major shopping events such as Black Friday and Prime Day, AI-generated referrals surged dramatically.
Yet the current scale still remains relatively small in absolute terms. AI-generated traffic accounts for less than 0.2% of total eCommerce traffic today. However, its growth rate far exceeds that of traditional acquisition channels, largely driven by large language model platforms such as ChatGPT, Microsoft Copilot and Google’s AI-powered search experiences.
The implication is significant: Retailers may soon need to optimize not only for search engines and social platforms, but also for AI agents acting as intermediaries between consumers and commerce systems. One consequence is that retailers will need to complement SEO with GEO — Generative Engine Optimization.
Why Product Data Suddenly Becomes Strategic
Generative Engine Optimization fundamentally changes how retail content must be structured, because AI systems rely primarily on product data rather than visual presentation.
In traditional machine-to-human online retail, visual merchandising and branding heavily influence purchasing decisions of consumers. AI agents, however, only look for structured and machine-readable information.
What follows is that websites with structured data are cited far more frequently in AI-generated search results and overviews. While incomplete or inconsistent product information may prevent products from being considered altogether by AI systems.
That creates a new competitive reality and requires action.
- Data quality is top priority.
- Product catalogs must become standardized, interoperable and continuously updated across all channels.
- Real-time inventory visibility, structured attributes and API-accessible commerce systems are becoming prerequisites for visibility in AI-assisted commerce environments.
Today, many retailers struggle with inconsistent product information, fragmented systems and outdated inventory data. This is a challenge that becomes significantly more problematic once machines, rather than humans, are making recommendations.
Security Risks Rise With Automation
The rise of agentic commerce will also require new security strategies because not only the valued customer has discovered the new possibilities of AI agents which are capable of operating autonomously and at scale, creating entirely new fraud scenarios.
A report from Accenture indicates growing concern among financial institutions and payment providers. AI-driven fraud attempts are expected to increase significantly and traditional fraud prevention models are not designed for autonomous agents that can imitate human behavior and adapt dynamically.
As a result, the industry is beginning to explore new concepts such as “Know Your Agent” frameworks as McKinsey explains, which aim to verify not only the customer, but also the legitimacy and permissions of the AI systems acting on their behalf.
For retailers and brands, future investments in commerce infrastructure will increasingly involve not only customer experience, but also machine identity management, authorization controls and agent-aware security systems.
The Infrastructure Question
Enterprises that want to remain competitive will need systems capable of supporting machine-driven discovery and transactions. API-first commerce architectures, interoperable data models and real-time commerce capabilities are moving into strategic focus.
Gartner predicts that 40% of enterprise applications will embed AI agents by 2026, underlining how quickly AI is becoming integrated into operational systems.
AI is evolving into a core interface for commerce. Human and machine-driven customer journeys will coexist, and companies that invest early in structured data, flexible architectures and agent-ready systems will be better positioned to benefit from the next phase of digital retail.
In this environment retailers not only need to convince consumers but also need to convince the machines shopping on their behalf.
