The Complete Agentic Commerce Glossary: 110+ Key Terms You Need to Know

TLDR: This glossary defines over 110 agentic commerce terms across categories including product data, payments, protocols, authority, governance, and measurement. Key protocols covered include ACP, UCP, MCP, and AP2, alongside concepts like delegated authority, prompt injection, and audit logging that underpin safe and accountable agent-led transactions.

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Agentic commerce is the use of AI agents to research, compare, recommend, and sometimes buy products or services on behalf of a person or business.

This glossary explains the terms that merchants, ecommerce teams, marketers, product teams, and AI adoption leads need to understand, organised by category.

For the operational detail behind several of these terms, my seven-part agentic commerce series covers execution, infrastructure, preferences, judgement, authority, liability, and governance in depth, alongside a dedicated piece on agentic commerce tax and current statistics and benchmarks.

Agentic commerce terms

Agentic commerce

Agentic commerce is a form of buying and selling where AI agents act on behalf of consumers or business buyers. The agent may search for products, compare sellers, apply stated preferences, check policies, build a basket, request approval, and complete a purchase.IBM defines agentic commerce as an approach in which intelligent agents research, negotiate, and complete purchases, often without direct human intervention. For a full walkthrough of what agent-readable stores look like in practice, see Agentic Commerce: How to Make Your Store Readable to AI Agents.

AI shopping agent

An AI shopping agent is software that helps a buyer find, compare, and buy products from a machine-readable product catalog. A basic shopping assistant answers questions. A stronger shopping agent makes choices, calls tools, remembers preferences, and acts across several systems without constant prompting.

Agentic checkout

Agentic checkout is a checkout flow built for AI agents rather than human shoppers alone. It lets an approved agent pass basket details, buyer context, payment information, and consent records directly into a merchant’s checkout process, leading to a much faster customer experience compared to traditional ecommerce.

Agentic storefront

An agentic storefront is the version of a merchant that an AI agent can read and use. It includes product data, feed quality, availability, returns information, delivery details, checkout access, and brand information formatted for machine consumption rather than human browsing.

Agent-ready commerce

Agent-ready commerce describes a merchant with the technical, commercial, and policy infrastructure AI agents need to discover products, understand offers, build baskets, and complete or prepare purchases.

Agentic commerce optimisation (ACO)

Agentic commerce optimisation, or ACO, is the work of making a merchant’s products and systems easier for AI shopping agents to find, understand, recommend, and transact with. It includes product feed optimisation, structured data, checkout readiness, returns data, accurate attributes, and agent-facing policies.

See the comparison table for how ACO sits next to SEO, AEO, and GEO within the wider digital marketing sphere.

ACO is important for traditional ecommerce brands looking to benefit from online shopping mediated by agentic payments and transactions.

SEO, AEO, GEO, and ACO overlap, but each optimises for a different output and a different reader.

Discipline

What it optimises

Reader

Typical output

SEO

HTML pages and rankings

Human searcher on Google or Bing

Copy rewrite, link building

AEO

Citation inside AI-generated answers

ChatGPT, Perplexity, AI Overviews

Clear, retrievable answer content

GEO

Visibility across all generative AI outputs

Any generative AI system

Broader content and source strategy

ACO

Product feeds, attributes, and protocol coverage

AI shopping agents (ChatGPT, Rufus, Gemini)

Feed enrichment, schema, protocol compliance

Most retailers need all four running at once for full agentic commerce readiness. Agentic Commerce Optimisation (ACO) is the narrowest and the newest, and is the one most directly tied to revenue, since it determines whether an agent can recommend and transact a specific product rather than simply mention a brand.

AI commerce

AI commerce is the broader use of artificial intelligence across buying and selling. It includes product recommendations, customer support, search, personalisation, dynamic pricing, content generation, demand forecasting, and agentic shopping as one subset.

Conversational commerce

Conversational commerce means buying through chat, voice, or messaging interfaces. It can involve human agents, scripted chatbots, and an AI assistant facilitating a purchasing decision.

Agentic commerce goes a step further: the software takes independent action rather than only responding to a prompt.

This has implications for product discovery.

Autonomous shopping

Autonomous shopping is buying with little or no step-by-step human involvement. The buyer states a goal, rule, or budget, and the autonomous AI agent handles the search, comparison, and transaction flow on its own.

Zero-click buying

Zero-click buying describes a buying pattern where the shopper never visits a merchant site or manually works through checkout. The personal or business agent finds the item, checks the terms, requests approval when its mandate requires it, and completes the order through a connected payment or checkout system.

Machine customer

A machine customer is a non-human economic actor, an AI agent or automated system, that researches, selects, and purchases on behalf of a person or organisation. Gartner coined the term to describe this emerging buyer class, distinct from the consumer it represents.

AI search and visibility terms

AI visibility

AI visibility measures how often a brand, product, or source appears in AI-generated answers, shopping recommendations, and agent responses. It is the AI-era equivalent of search discoverability in digital marketing.

Answer engine optimisation (AEO)

Answer engine optimisation, or AEO, is the practice of structuring content so it gets cited inside AI-generated answers. AEO focuses on clear answers, definitions, source credibility, and retrievable content fragments.

Generative engine optimisation (GEO)

Generative engine optimisation, or GEO, is the broader practice of improving visibility inside generative AI systems, including AI search, chat assistants, and answer engines.

AI search

AI search is search where the system produces a generated answer, recommendation, comparison, or summary rather than only a list of ranked links. Google AI Overviews, AI Mode, ChatGPT Search, and Perplexity all fall under this umbrella.

AI shopping surface

An AI shopping surface is any place where a user can discover, compare, or buy products through an AI system.

Current examples include ChatGPT Shopping, Google AI Mode, Gemini, Perplexity Shopping, Amazon Rufus, Microsoft Copilot Shopping, retailer-built assistants, and voice agents.

Coverage varies sharply by surface, so a merchant visible on one may stay invisible on another without separate integration work.

Found rate

Found rate is the share of tested prompts where an AI system finds or recommends a brand, product, or seller. It tells a merchant whether intelligent agents can discover their products at all, before recommendation quality enters the picture.

AI share of voice

AI share of voice is the share of AI-generated recommendations, mentions, or citations a brand receives compared with competitors, measured across a defined set of prompts.

Citation rate

Citation rate is the share of AI answers where a brand, page, report, or product appears as a cited source. This metric matters most for publishers, analysts, and B2B sites that compete on authority rather than product listings.…