The Next Retail Revolution Is Agentic Commerce

Agentic AI Commerce: The Next Retail Revolution Is Already Underway

Retailers must place their strategic bets now before autonomous AI agents redraw the competitive map of commerce entirely.

The last time retail faced a disruption of this magnitude, the internet had just arrived. In the late 1990s, every established retailer faced the same existential question: resist the digital wave or ride it? Those that clung to their brick-and-mortar identities while dismissing e-commerce as a fad lost ground they never fully recovered. Those who invested early and with conviction in digital platforms and omnichannel presence built durable advantages that still compound today.

Now that question is back, rewritten for a new era: how should retailers respond to agentic AI? AI agents, software systems that can autonomously plan and complete tasks on a user's behalf, are beginning to reshape how consumers discover, compare, and purchase products. In the near term, these agents streamline the research process. In the longer term, full agent-to-agent (A2A) commerce becomes possible: a buyer's AI agent communicates directly with a retailer's AI agent, negotiates terms, and closes a transaction, all without a human ever visiting a product page. At that point, the traditional retail website, with its curated homepage and carefully engineered checkout funnel, could be bypassed entirely.

For consumers, the appeal is obvious. A well-calibrated agent can surface the best available offer across dozens of retailers in seconds, filtering by price, shipping speed, loyalty rewards, sustainability criteria, or any other preference the user has expressed. Shopping becomes less of an activity and more of a background process. Consumers delegate, agents execute.

For retailers, though, the calculus is considerably more complicated.

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A Disruption With No Neutral Positions

The economics of agentic commerce cut in two directions simultaneously. On one hand, retailers that open their catalogs to third-party agents gain exposure to consumers they might never have reached through organic search or paid media. Discovery improves. Conversion rates on clearly differentiated products rise. For smaller or niche brands with limited marketing budgets, AI-powered distribution channels could prove transformative.

On the other hand, agents are efficient price-comparison machines. They create market transparency, giving the cheapest, fastest, and most accessible option an edge. Where retailers once competed on the look of their website or loyalty programs, agents reduce every transaction to its core variables. Brand equity, which took years to build, can be undercut by algorithms.

This is not a theoretical concern. Santiago & Company research indicates that 30% to 45% of U.S. consumers already use generative AI to research and compare products, a figure drawn from Santiago & Company's Consumer GenAI Survey. These are not early adopters living on the technological frontier; they are mainstream consumers integrating AI tools into ordinary shopping routines. Meanwhile, platforms such as ChatGPT, Microsoft Copilot, and Gemini have begun enabling direct purchase and checkout functionality. The infrastructure for A2A commerce is forming faster than most retailers realize.

About half of consumers say they are not ready to give full purchasing authority to an AI agent without oversight. Santiago & Company analysts believe the real proportion of cautious shoppers is likely higher. Many consumers underreport reluctance in surveys. Still, the direction is clear. As trust in agents deepens and technology proves reliable, adoption will accelerate. Retailers have a short window to set their strategies before A2A commerce becomes the norm

Three Strategic Positions And the Trade-offs Each Carries

Retailers navigating this shift face a choice like that of the early e-commerce era: how open, and how fast? Santiago & Company identifies three broad strategic positions. Each has distinct trade-offs.

Embrace Third-Party Agents

The most permissive approach allows third-party agents to crawl a retailer's catalog, index products, and facilitate purchases, effectively turning AI intermediaries into a new distribution channel. This strategy suits retailers that lack the brand recognition or marketing reach to drive traffic independently, as well as those that lack the technical capacity to build proprietary agent infrastructure.

For monobrand retailers in particular, third-party agents open access to net-new buyers who may never have encountered the brand through traditional channels. A product that is genuinely superior on its merits, better-priced, faster to ship, and higher-rated will find its natural market more efficiently. The risk is commoditization. When an agent selects among options based purely on measurable attributes, brand identity and emotional resonance carry less weight. Retailers that compete primarily on intangibles face real exposure.

The risk is amplified for multibrand retailers and marketplace operators. Third-party agents increase market transparency in ways that structurally favor high-volume, low-cost, high-speed competitors. The players with the thinnest margins and the fastest fulfillment networks gain disproportionately. Retailers that cannot differentiate on price, assortment, or speed must find another basis for competitive advantage  or risk being gradually crowded out of the agent-mediated market. Marketplace operators face an additional threat: agents may route consumers directly to individual sellers, bypassing the marketplace storefront entirely. The platform becomes invisible. Trust signals, verified reviews, buyer guarantees, and dispute resolution  become the primary defense against disintermediation.

Build a Proprietary Agent Ecosystem

Retailers with strong brands and organic traffic can build their own agentic ecosystem. Instead of feeding other platforms' agents, they start the consumer journey. Their proprietary agent becomes the way consumers shop, not just in their catalog, but across the market.

Consumer sentiment supports this ambition. Santiago & Company research finds that shoppers trust retailers' own on-site agents approximately three times more than they trust third-party agents, a significant confidence differential that brand-owning retailers can leverage. That trust advantage becomes the foundation for a proprietary commerce platform.

Amazon's "Buy for Me" agent represents the most aggressive version of this strategy in practice. The agent can purchase products from other brands' websites when items are unavailable on Amazon's platform, processing all transactions through Amazon's infrastructure. Amazon retains access to the customer relationship and all associated data. At the same time, Amazon has blocked external agents from interacting with its own site directly, a move that reinforces its role as the origin point for commerce rather than a passive participant in someone else's ecosystem.

Building this capability is not without complexity. A retailer with a proprietary agent must determine how to attract merchants to grant agent access. It must also manage payment processing and fraud risk in third-party transactions. Handling customer service for products not manufactured in-house and protecting its brand when a partner retailer disappoints a shared customer are also key challenges. These are real operational issues requiring investment and organizational capacity. The payoff for those who can execute is control over the consumer relationship, the data, and the platform's economics.

Fortify the Home Site While Selectively Opening to Agents

For many retailers, neither extreme will be appropriate. A middle path, selective openness, combined with deliberate home-site investment, offers a more pragmatic route through the transition.

In practice, this means giving third-party agents access to some products and categories while reserving others for the native shopping experience. Installation services, warranty support, time-limited promotions, and premium loyalty benefits can all be gated behind the brand's own app or website. This selective approach creates a natural division: commodity purchases flow through agent channels, while higher-value or more complex transactions remain on-site. The retailer participates in the agentic ecosystem without surrendering control of the interactions that drive the deepest customer relationships.

Home Depot's Magic Apron illustrates how native agents can anchor the home-site experience. The AI companion, available exclusively on Home Depot's website, provides specialized product guidance and customer support with access to purchase history and account data that third-party agents simply cannot access. The result is a personalization advantage that is structurally difficult to replicate externally  and one that rewards customers for staying within the brand's ecosystem. For a retailer whose products often require installation know-how and whose customers frequently return for related purchases, that depth of service is a genuine differentiator.

This hybrid strategy does not require the resources or market position needed to build a full proprietary ecosystem, but it does require discipline. Retailers must negotiate data-sharing agreements for transactions that close off-platform, and continually invest in making the native experience meaningfully better than any agent can replicate.

What Retailers Must Prioritize Now

The strategic choice of how open to be is only the beginning. Across all three positions, retailers share a set of foundational priorities that will determine how well they navigate the agentic transition.

Control over where transactions close matters enormously. Retailers that lose the ability to process their own payments cede not just revenue but the customer relationship itself, including the data, the loyalty touchpoints, and the service interactions that follow a purchase. Wherever possible, retailers should structure agentic integrations so that final transactions run through their own platforms using their preferred payment processors.

Where that is not feasible, partnerships must fill the gap. Retailers that allow third-party agents to close transactions on their behalf need contractual access to the data generated by those transactions. Without visibility into purchasing behavior, retargeting becomes impossible, repeat-purchase strategies collapse, and the retailer risks becoming nothing more than a fulfillment provider invisible to the consumer and replaceable by any cheaper alternative.

Data optimization for AI consumption is also increasingly non-negotiable. Agents do not browse; they query. Product data that is poorly structured, incomplete, or difficult for AI systems to parse will be deprioritized or ignored entirely. Retailers need to adapt their data architecture, product descriptions, pricing structures, and promotional logic so that agents can accurately represent their offerings in consumer-facing recommendations.

The Strategic Imperative

Agentic AI will not uniformly or instantaneously reshape retail commerce. But the direction is not in doubt. The retailers that act now, making deliberate choices about openness, infrastructure, and home-site differentiation, will be better positioned to capture the benefits of agentic distribution while protecting the customer relationships that sustain long-term value.

The lesson of the e-commerce era is instructive and worth stating plainly: the retailers that survived and flourished were not those that moved fastest for its own sake, nor those that resisted longest. They were those who understood the structural shift underway and made purposeful choices about where to compete, how to differentiate, and which capabilities to build before the market made those decisions for them.

Agentic AI presents a similar moment. The window for strategic choice is open. It will not stay open indefinitely.