Navigating a New Demand Paradigm and Its Two-Sided Imperative

The rise of agentic commerce, where AI agents could potentially execute purchases for consumers, signals more than an evolutionary step in e-commerce; it represents the emergence of a new type of demand: a direct customer buy order, theoretically complete with payment authorization. This presents a two-sided imperative for retailers. Firstly, ensuring your products are discoverable and favorably considered by these AI agents an “SEO for the agentic era.” Secondly, developing the organizational capacity to act on this demand, potentially bypassing traditional e-commerce pathways for direct fulfillment via APIs, with updates to fraud and risk screening.

While the full realization of this paradigm is not immediate (see prior analysis), understanding its structure is crucial for strategic preparation. Currently, agentic functionalities often resemble advanced search rather than fully autonomous purchasing systems.

Current Environment: Foundations for a New Demand Model Amidst Existing Barriers

Recent announcements, particularly from tech giants like Google, are accelerating the move towards an agent-driven marketplace. At its recent I/O conference, Google unveiled several AI-powered features directly related to “agentic commerce” within its search and shopping experiences. These innovations aim to make online shopping more seamless and efficient, including virtual try-on capabilities and even “agentic checkout” functionalities. A key aspect of this is Google’s new “AI Mode,” where consumers can grant permission for their data to be used by AI to refine search results, all powered by its massive shopping graph containing a reported 50 billion items. 

All of this lays the groundwork for this new demand model with established platforms (with established use and real time data) transforming how consumers begin their shopping journey. This occurs within a landscape where Amazon still leads US initial product searches (56%), with Google (42%) and Walmart (29%) following, underscoring that consumer journeys often start outside retailers’ direct control.

However, significant obstacles hinder the realization of agentic “buy orders.” As previously detailed, agent interactions can be complex, and agents face limitations in direct transaction execution due to e-commerce authentication (and device based risk) infrastructure. The lack of clear merchant economic models and retailer reluctance towards new intermediaries also temper a 2025 waterfall. Within my Retailer Agentic survey, one CMO quipped “There is no way we will enable a new Google do disintermediate us, we want to use our data for our own benefit”.  While merchants are not jumping for joy at the thought of an agentic future, you must plan for it as all retailers must BE where their customer ARE (not where they want them to be). 

While Google’s innovations aim to address these issues, the progression from enhanced search to accepting and fulfilling widespread, independent agent-driven “buy orders with payment” is not a 2025 trend, but may be one next year. The data and personalization capabilities are foundational, but the mechanisms for this new demand type are still developing.

Impact Assessment: From Enhanced Search to Potential “Buy Orders”

In the near term, agentic AI will primarily refine information retrieval. For example within the travel segment, agents streamline complex itinerary searches, though direct booking often requires user intervention. This illustrates the “discovery” side of the imperative, but the “direct fulfillment” of an agent-initiated paid order is less mature.

Long-tail retail presents another type of opportunity as agents can improve discovery of local inventory (new and used. see Battle of the Cloud Part 6 – Data Games). While this addresses the “SEO for agents” aspect, the transition to an agent autonomously executing a purchase with payment requires overcoming significant trust, authentication, and processing hurdles (Which Visa is addressing – See Product Drop). The enjoyment of shopping in certain categories also means agents currently serve more as sophisticated research tools than direct purchasing conduits.

Large retailers will certainly invest in creating a better customer experience with their own proprietary AI, focusing on internal search and personalization. Collaborative platforms may emerge (ex Google Cloud), but externally, CMOs should assess opportunities for optimizing agent based discovery, and assessing the approaches to agentic platform integration for this new demand (ie direct agent-originated paid orders).

Strategic Imperatives: Addressing the Two-Sided Challenge

To prepare for this nascent demand paradigm:

1. Recognize Agentic Requests as a new type of demand: “Buy Orders”: View inquiries from AI agents as precursors to direct, paid demand. While currently more like highly qualified leads, this is the foundational input for the new model.
2. Optimize for Agentic Discovery (The New SEO): Your products must be discoverable and well-represented to AI agents. This means robust, structured product data, clear attribute tagging, and adapting content strategies for machine interpretation—the “SEO for agents” imperative. Platforms like Google Merchant Center and services promoting local inventory are vital. Adapting to platforms capturing consumer intent is key.
3. Develop Direct Fulfillment Capabilities (The New Order Processing): There’s no reason a verified “buy order with payment” from an authenticated agent platform must traverse your standard e-commerce site. Explore direct connect APIs for receiving and processing such orders. This requires:
   1. New Fraud and Risk Screening: Agent-originated transactions will lack traditional device fingerprints, demanding novel authentication and risk assessment models.
   2. New agentic capable buy APIs with authentication (SRC, GPay, Link, …etc)
   3. Product search and availability
4. Selectively Engage with New Interaction Models: Support features like virtual try-on where they enhance agent-led discovery and product evaluation, feeding the “consideration” phase.
5. Continuously Analyze Customer Journey Data: Track how agent-influenced discovery and (eventually) transactions evolve to refine your approach to both sides of the imperative.
6. Fortify Value Propositions Beyond Price: As agents streamline comparison, differentiate through factors AI may deprioritize: unique assortments, delivery speed/reliability, service, and brand trust.
7. Recognize that real time data and intent is the most powerful driver of action and find ways to connect to it. Also recognize the data footprint of partners across the Customer data Venn (pic below)
8. Define Partnership and Data Governance for This New Channel: Establish clear protocols for engaging with agentic platforms, focusing on data exchange for discovery and the secure handling of potential future transactions.

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Agentic commerce, conceptualized as a new type of direct, paid demand, presents a significant strategic horizon. While its full transactional capabilities are still emerging, retailers must prepare for both ensuring their offerings are “chosen” by agents and developing the distinct infrastructure to fulfill these orders efficiently and securely.