Algorithmic Agency in Commerce: Applying Principal-Agent Theory to the Shopper Schism
Author: Paul F. Accornero
ORCID: https://orcid.org/0009-0009-2567-5155
SSRN: Paper Under Review
Affiliation: The AI Praxis
Date: July 01, 2025
Abstract
In agentic commerce, a profound schism emerges between human intention and algorithmic execution. Consumers may express preferences, but the final purchasing decision is often executed by an AI agent. This paper analyzes this dynamic through the established lens of principal-agent theory, framing the human user as the principal and the AI as the agent. We introduce the term "Shopper Schism" to describe the unique manifestation of agency problems—specifically information asymmetry and moral hazard—that arise in this context. Drawing on emerging empirical research and illustrative mini-case studies of systems like Amazon's "Subscribe & Save," we explore how consumer choice is mediated and potentially redirected by algorithms. The paper contributes by extending agency theory to the novel domain of autonomous, non-human commercial agents. We conclude with managerial implications for designing trustworthy AI systems and a call for further research into the economic and behavioral impacts of delegated digital consumption.
1. Introduction
For a century, the architecture of commerce has rested on the fusion of two roles within a single human actor: the consumer who holds a need and the shopper who executes the purchase. This historical fusion of intention and execution is now breaking apart with the rise of the Algorithmic Shopper—an autonomous AI agent that translates a human’s goals into transactions.
This paper analyzes this emerging dynamic through the established theoretical framework of principal-agent theory (Eisenhardt, 1989). We posit that the relationship between a human user and their AI shopping assistant represents a new and critical form of the principal-agent problem. The human acts as the principal, delegating a purchasing task. The AI acts as the agent, executing that task on the principal's behalf.
We introduce the term "Shopper Schism" not as a new theory, but as a descriptive label for the unique manifestation of agency problems that arise from this delegation. The schism is the structural separation between a human’s often nuanced, high-level intention and the algorithm’s logical, data-driven execution. Recent empirical work confirms that different AI agents make fundamentally different choices, concentrating markets and responding to signals in non-human ways, highlighting the gravity of this new delegated relationship (Allouah et al., 2025). This paper will define and deconstruct the Shopper Schism, analyze its managerial implications through mini-case studies, and propose a new agenda for strategy and research in an era of delegated commerce.
2. Methodology
This paper develops a conceptual framework by applying established principal-agent theory as an analogical model to the nascent field of agentic commerce. The framework's propositions are grounded through a synthesis of emerging empirical research on AI agent behavior (e.g., Allouah et al., 2025) and refined through the analysis of two illustrative mini-case studies: Amazon's "Subscribe & Save" auto-replenishment system and the delegated purchasing capabilities within automotive systems like Tesla's. This method allows for the extension of robust theory to a novel technological context, providing a structured lens for analysis and future inquiry.
3. The Principal-Agent Problem in Algorithmic Commerce
The core of agency theory revolves around problems that can occur when a principal delegates work to an agent, particularly when goals are not perfectly aligned or when there is an imbalance of information (Eisenhardt, 1989). The Shopper Schism brings two classic agency problems to the forefront in a new, high-tech context.
1. Information Asymmetry: The agent possesses information that the principal does not. In this case, the AI agent's decision-making process—its complex, multi-variable trade-off analysis across thousands of data points—is opaque to the human user. The user sees the outcome (a product is purchased) but not the rationale or the alternatives that were discarded. They do not know if the agent's choice was truly optimal or merely the result of a flawed or biased algorithm.
2. Moral Hazard: This is the risk that the agent will not act in the principal's best interest. With an AI agent, this risk is not born of malice but of misaligned objectives. The agent's goal might be to rigidly adhere to a budget, causing it to substitute a trusted brand for a cheaper, lower-quality alternative to save a few cents. More critically, the agent's logic may be influenced by the goals of its platform provider (e.g., to promote its own private-label products), which may not align with the consumer's goal of getting the best possible product.
4. Illustrative Mini-Case Studies of the Schism
4.1 Case Study: Amazon's "Subscribe & Save"
Amazon's Subscribe & Save program is a "proto-agentic" system that clearly illustrates the schism.
● Human Intention (The Principal): The user's intent is one of convenience and cost-savings. They delegate the recurring task of purchasing a staple item (e.g., coffee, diapers) to Amazon's system.
● Algorithmic Execution (The Agent): The system automatically executes the purchase at a set interval. However, a schism occurs because the agent's execution is rigid. It does not account for changes in the user's consumption rate, nor does it dynamically check competitors for a better price at the time of purchase. The user intends "convenience," but the execution can lead to stockpiles of unneeded items or missed opportunities for savings—a classic agency problem where the agent's simplistic execution diverges from the principal's holistic intent.
4.2 Case Study: Tesla's In-Car Purchasing
Tesla vehicles function as agents with delegated purchasing authority.
● Human Intention (The Principal): The owner pre-authorizes the car to make purchases by linking a credit card. The intent is a frictionless experience for services like software upgrades (e.g., Full Self-Driving) or Supercharging.
● Algorithmic Execution (The Agent): The car itself executes the transaction. When a driver pulls up to a Supercharger, the car communicates with the network and autonomously pays for the electricity used. This is a near-perfect alignment of intent and execution. However, a potential schism emerges with software upgrades. The agent (the car's OS) may present an offer for a new feature. The execution (a one-click purchase) is seamless, but it relies on the user trusting that the agent's description of the feature's value is accurate and not simply an effective piece of platform-owned marketing.
5. Managerial Implications of the Schism
This separation of intention from execution fundamentally rewrites the rules of commercial strategy.
1. Marketing to Intent vs. Optimizing for Execution: Companies must now fight a two-front war. They must continue to use high-level branding to influence the human’s intention—so that "fair-trade coffee" is part of the initial prompt. Simultaneously, they must engage in AIO to optimize their structured data for the agent’s execution—so their product is the one chosen when the agent runs its logical audit.
2. Bridging the "Gulf of Delegation": While Norman's (1988) "gulf of execution" traditionally refers to user interface design, the Shopper Schism creates a new, automated "gulf of delegation." The strategic opportunity for brands is to help bridge this gulf. This involves providing transparent, easily digestible data that helps the human principal verify that the agent's execution was trustworthy, reinforcing the principles of human-centered AI design (Shneiderman, 2020).
3. Building "Agent Trust": The new strategic imperative is to become the brand that is consistently the agent's most reliable and optimal choice. This requires a shift from building emotional connection with humans to building systemic, data-proven reliability for machines.
6. Future Research Directions
The Shopper Schism opens critical questions for future research:
● Consumer Trust and Technology Acceptance: What factors, according to the Technology Acceptance Model (TAM), will drive consumer trust and adoption of delegated agents, especially given the risks of misalignment?
● Interface Design for Oversight: How can Human-Computer Interaction (HCI) principles be used to design agentic interfaces that give users meaningful oversight and control over the agent’s execution without re-introducing friction?
● Long-Term Economic Impacts: What are the market impacts of this new principal-agent relationship at scale on pricing power, brand equity, and market concentration? Will it empower consumers or the platform gatekeepers who design the agents (Parker et al., 2016)?
7. Conclusion
The Shopper Schism is a fundamental restructuring of the path to purchase and a defining feature of agentic commerce. The fusion of human intention and execution in a single shopper is over. By applying the lens of principal-agent theory, we can see this new dynamic not as an entirely alien phenomenon, but as a high-stakes evolution of a classic economic relationship. This shift challenges leaders to move beyond a singular focus on the human consumer. Success in this new landscape requires a dual strategy: continue to build a brand that inspires human intention, while simultaneously architecting a data-driven operation that wins the logic of algorithmic execution.
Author Note: The author confirms sole intellectual ownership of the concepts, frameworks, and all substantive arguments developed herein. AI was used as an assistive tool in research and drafting certain portions of the manuscript, but all original theoretical contributions are those of the author, who retains full responsibility for content and conclusions. Disclosure is provided in line with current academic and publishing ethics guidelines. The author is currently expanding these theoretical frameworks in a forthcoming book on algorithmic commerce under contract with St. Martin's Press, expected 2027.
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