For more than a century, the central question of marketing has been: How do customers choose products?

Research traditions—from rational choice theory to behavioral economics—have analyzed how individuals search for information, evaluate alternatives, and decide under cognitive, social, and emotional influences.

But the emergence of generative and agentic artificial intelligence, integrated into everyday devices and empowered by generative inference models, is quietly inverting this paradigm. In the near future, the prevailing question will no longer be how customers choose, but rather:

How will products—through Artificial Intelligence (AI) intermediaries—choose their customers?

This inversion does not imply a loss of human autonomy. Instead, it signals a structural reconfiguration of market mediation, where decision-making shifts from human search to machine anticipation, from preference expression to preference prediction, from user-driven comparison to AI-driven selection.

From Search to Anticipation: The Collapse of the Traditional Customer Journey

Traditional marketing models assume a linear or circular “customer journey”: awareness, consideration, evaluation, purchase, loyalty. These stages presuppose active search, where consumers intentionally seek and compare alternatives.

However, agentic AI systems—embedded into devices, homes, vehicles, and operating systems—are removing the need for intentional search. What emerges is a post-search society, where:

• needs are detected before they are consciously formulated;

• alternatives are screened before they are imagined;

• products are shortlisted before the customer expresses a desire.

This new environment moves from search engines responding to queries to personal AI agents initiating actions autonomously.

The shift is not merely technological. It is epistemological: the locus of decision-making migrates from explicit, conscious human choice to implicit, computational inference.

The Case of Lorenzo: A Microcosm of the Paradigm Shift

Consider Lorenzo, a business consultant whose smartphone contains an integrated AI agent capable of analyzing his routines, voice notes, travel patterns, expense history, and contextual data. When his suitcase breaks, Lorenzo does not search for reviews or compare models online.

His AI agent:

• recognizes the problem from a voice memo,

• cross-references it with his travel schedule,

• filters options by durability, price, and weather conditions,

• and orders a replacement proactively.

He is asked only to confirm the color.

This scenario illustrates several emerging features of AI-mediated commerce:

Predictive Inference Instead of Expressed Intent

The system identifies needs through multimodal signals—speech, behavior, patterns—not through explicit queries.

Autonomous Transactional Execution

The AI does not merely recommend; it acts.

Semantic Compression of Choice

The decision space collapses into a short, digestible explanation, replacing comparison with trust in the agent.

This is not fiction. It is the logical extension of current generative and agentic systems: AI becomes not a tool, but a market subject, performing search, evaluation, and transaction on behalf of the human.

When Products Choose Customers: The New Market Architecture

If AI agents represent the consumer, then products and brands will increasingly optimize themselves not for human attention, but for AI selection criteria. Thus emerges a profound inversion:

The Product Competes for the AI, Not the Human

The target audience is no longer the consumer, but the consumer’s AI agent.

This implies:

• new forms of product metadata designed for machine interpretability;

• trust, safety, and reliability signals optimized for algorithmic assessment;

• transparent and verifiable value claims accessible through machine reasoning.

The AI Agent as a Gatekeeper

The agent:

• filters,

• interprets,

• justifies,

• and executes

the selection of products. Human choice becomes supervisory, not exploratory.

From Positioning to Representability

Brands will compete on their semantic clarity:

• consistency across digital sources,

• coherence of their narrative identity,

• robustness of reputational signals.

The brand that is synthetically most interpretable becomes the brand most likely to be selected.

Ethical Ambiguities and Power Concentration

Lorenzo’s unease—“Who really made this decision?”—points to a deeper academic concern: autonomy, transparency, and agency in AI-mediated consumption.

Agency Ambiguity

Who is the decision-maker?

• the consumer?

• the AI agent?

• the algorithms ranking alternatives?

• the commercial actors influencing those algorithms?

Marketing, once a discipline of persuasion, becomes a discipline of alignment between human values and machine intermediaries.

Risk of “Invisible Agreements”

If AI agents prioritize certain products for commercial rather than functional reasons, the market may drift toward a dark optimization where neutrality is replaced by monetized preference shaping.

Asymmetry of Power

Consumers rely on AI to simplify complexity; AI systems rely on data from institutions and corporations.
This creates a structural asymmetry:
the more convenience increases, the more invisibility of influence grows.

Toward a Theory of AI-Mediated Consumption

From this emerging scenario, a new academic framework may be articulated:

Agentic Intermediation Theory (AIT)

Markets evolve from human-to-product interactions to agent-to-system interactions. Consumers supervise decisions rather than initiate them.

Predictive Commerce

Purchases are triggered by predictions rather than desires. Needs are inferred, not expressed.

Synthetic Choice Architecture

Choices are shaped by synthesized explanations, not by human exploration. The format of decision-making shifts from exploration to validation.

Trust as the Currency of AI Agents

Human trust in AI becomes more important than loyalty to brands.

Implications for Marketing and Society

Marketing Must Redefine Its Role

If products choose the customer, marketing becomes the art of being:

• interpretable,

• verifiable,

• trustworthy,

• semantically consistent.

New Skills for Organizations

Companies must master:

• machine-readable positioning,

• narrative consistency,

• ethical signaling,

• data transparency.

Consumer Education

Society must cultivate literacy not in search, but in oversight. Consumers don’t need to know how to find; they need to know how to evaluate decisions made for them.

Conclusion: When Convenience Becomes Destiny

The arrival of AI-driven selection systems marks a watershed moment in the history of markets. For the first time, humans may no longer initiate consumption.

Products, through AI agents, will seek out the individuals who best match their use case, price point, and contextual needs.

The future of marketing is not outreach—it is alignment with intelligent intermediaries capable of choosing on behalf of humans.

In this future, convenience will deepen, friction will vanish, and decision-making will become anticipatory rather than active.

The fundamental question is no longer “What will people choose?” but rather: “What kind of world emerges when choices are made before we know we need them?”

A world where the perfect suitcase arrives, perhaps too perfect—revealing not only what we want, but what we are becoming.