“Others built the roads of the agentic city. I designed its physics.”
These frameworks form one connected programme, not a scatter of topics. They begin from a single rupture, the Shopper Schism, and develop across three moments: the theoretical foundations of what is happening to commerce, the disciplines an organisation must build in response, and the governance architecture required when algorithms become the primary commercial counterparty.
Each framework is a citable, standalone construct, anchored to a body of academic research and to the foundational manuscript, The Algorithmic Shopper: Rethinking Growth, Strategy, and Brand Power in an AI-First World.
Movement I: Diagnosis
What is happening, and why it is irreversible.
The Shopper Schism®
The permanent separation, in the history of commerce, of the consumer who uses the product from the shopper who executes the transaction, completed by the arrival of autonomous AI agents that now perform search, evaluation, and purchase on behalf of human principals. When the shopper is no longer human, a century of marketing built to persuade human minds no longer reaches the decision-maker.
The Great Decoupling
The historical process by which the consumer-shopper fusion that underpinned a century of marketing is dissolved by agentic AI. For most of commercial history, the person who wanted a product and the person who bought it were the same individual. Agentic commerce ends that equation permanently: discovery, evaluation, and transaction migrate to machine execution while human experience remains on the consumption side.
The Trust Paradox
The phenomenon by which an AI agent's ability to reduce search risk for consumers simultaneously renders invisible the brand's traditional trust-building signals. Consumers delegate purchasing to agents precisely because they trust the agent more than their own search; but the signals brands have used for decades do not translate to the machine making the selection. The higher the delegated trust, the less effective traditional brand investment becomes.
The Automaton Economy
The macro-economic system that emerges when autonomous AI agents transact at scale, reshaping pricing dynamics, supply signals, and demand formation. Volume and velocity of machine-executed transactions alter the feedback loops markets depend on: prices clear differently, demand signals arrive compressed in time, and supply chains must respond to algorithmic ordering rather than human seasonal rhythms.
The Shopper Has No Eyes
Branding in a world without human perception. When the selecting agent has no eyes, the visual and emotional cues brands spent a century perfecting no longer reach the decision-maker. Brand equity must be rebuilt as machine-legible signal rather than human impression.
AI Shoppers Are Psychologically American
Evidence of a measurable WEIRD bias in large language models, which makes AI shopping agents psychologically American by default. A structural risk for global commerce, where an agent's defaults may not reflect local consumer realities.
Movement II: Action
What organisations must build to compete when the customer is code.
Algorithmic Readiness and the Four Ds Framework
The organisational capability to compete when the customer is code: the degree to which a brand's products, data, and commercial infrastructure are fit to be chosen by machine agents. The Four Ds Framework, Data Quality, Discoverability, Decision Clarity, and Delivery Reliability, is the diagnostic architecture for measuring it. Together they form the Algorithmic Readiness Audit, available through The AI Praxis.
Agent Intent Optimisation (AIO)
The discipline that succeeds search engine optimisation when the audience is a machine rather than a human: optimising a brand's presence, data, and commercial signals for algorithmic selection rather than human attention. Where SEO asked how to attract human eyes, AIO asks how to attract algorithmic choice.
The Retail Schism
The structural reorganisation of brand-to-retailer relationships forced by algorithmic intermediation. When AI agents become the primary shopper, the joint-planning, pricing, and execution models built between brands and retailers across three decades must be redesigned for a buying side that is no longer human.
Working paper, forthcoming on SSRN
Algorithmic Joint Business Planning
A twelve-dimension framework for reshaping supplier-retailer commercial relationships in agent-mediated trade. The successor to the traditional joint business plan, rebuilt for a buying side that is algorithmic: how brands and retailers will plan, price, and execute together when agents sit between them.
Working paper, forthcoming on SSRN
The Algorithmic NPS
An agent-side counterpart to the Net Promoter Score for agent-mediated commerce: a measure of how readily AI agents select, trust, and re-select a brand, when human recommendation is no longer the signal that drives growth.
Working paper, forthcoming on SSRN
Loyalty in the Age of Agents
Can algorithms be loyal? A re-examination of loyalty when the repeat purchaser is a machine optimising for its principal, and the emotional and habitual levers that built human loyalty no longer apply.
Movement III: Governance
The accountability architecture for a world where algorithms are the primary commercial counterparty.
The Governance Gauntlet
The multi-layer risk framework for organisations in which AI agents have become the primary commercial counterparty, covering legal accountability, ethical exposure, and systemic risk at market scale. It identifies three risk layers, transaction, system, and values, that must be navigated at once; failure in any one invalidates safe passage.
The Three Layers of Trust
How consumer trust is restructured under agentic commerce. Traditional brand trust was a single bilateral relationship between consumer and brand. Agentic commerce inserts two further relationships: the consumer trusts the agent (delegated trust), and the agent must trust the brand's data and signals (machine trust).
From Corporate Misalignment to Market Failure
How misaligned objectives inside the firm propagate, through agentic intermediation, into market-level failure. A governance parallel for AI in sales and marketing systems, and the controls required to prevent local incentives from producing systemic harm.
Information Asymmetry and Moral Hazard
A principal-agent analysis of AI-mediated commerce: where information asymmetry and moral hazard arise when an agent transacts on a human's behalf, and the governance mechanisms required to close the gap between principal intent and agent action.
The Category and the Field
Agentic commerce: defined, extended, and measured.
Agentic Commerce
The emerging mode of exchange in which autonomous AI agents, operating on delegated authority from human principals, execute the shopper function of search, evaluation, and purchase through computational logic rather than psychological persuasion. Paul F. Accornero was first to define agentic commerce as an academic discipline, ahead of the industry commentary that followed.
AI Agents as Technological Innovation
Managing the transition to autonomous economic intermediaries. How firms should treat agentic AI not as a tool but as a new class of economic actor, with its own adoption dynamics, governance needs, and competitive consequences.
Agentic Commerce in Professional Services
Agentic commerce theory applied to legal services selection, evidence that the buying-side shift reaches professional and advisory services, not only consumer goods, and that delegated selection is becoming a universal logic.
Algorithmic Commerce Measurement
Beyond impressions: defining the performance-measurement architecture for agent-mediated commerce. The metrics that replace reach and impressions when the audience is an algorithm, and the foundation for measuring algorithmic visibility and choice.
From framework to advantage.
