READINESS · CANONICAL DEFINITION

What is AI Commerce Readiness?

Definition ◆ canonical · maintained

AI Commerce Readiness (n.)

the discipline of making a brand discoverable, sellable, personalized, and attributable in AI-mediated commerce.

Shoppers increasingly ask AI assistants what to buy. Assistants name a few brands, are beginning to complete purchases, and produce no attribution trail. AI Commerce Readiness is everything that has to be true for a brand to win in that environment — of which AI visibility is only the first step.

TERM MAINTAINED BY HERM · FIRST PUBLISHED [DATE] · CITE: herm.io/for-brands/readiness

Get your Readiness Score Read the methodology

Three things changed. No existing discipline covers all three.

Discovery moved. Buying decisions now happen inside conversations a brand's analytics never see. A shopper asks an assistant what to buy for sensitive skin; three brands come back. Absent from the answer means never in the running — and no dashboard records the loss.

Checkout is moving. Recommendation and purchase are collapsing into one surface. As agents begin completing transactions, a brand that is visible but not sellable — no live catalog the model can quote, no destination that ships to the shopper — gets mentioned and skipped.

Attribution never existed. No one has ever been able to prove which AI answer caused which sale. The conversation happens on one surface, the purchase on another, and nothing connects them — until a verified receipt does.

Search-era disciplines cover the first shift at best. AI Commerce Readiness names the whole problem: not "are we mentioned," but "can the machine that's replacing the shop assistant find us, sell us, pick us for the right person, and prove it did."

Readiness is a ladder. Each rung has a test.

Four rungs, one destination — every brand is on one of them. Each rung below is defined by the question it answers.

Rung 01 · Be found

Does AI know and recommend you?

A brand is found when AI models know it and recommend it in answer to the questions its buyers actually ask — and when it can see the reasoning behind both the mentions and the absences.

Brand Visibility Live

Rung 02 · Be sellable

Can AI actually complete the recommendation — specs, price, stock, where to buy?

A brand is sellable when a model can complete its own recommendation: quote specs, price and stock from a live, agent-readable catalog, and route the shopper to a destination verified to ship to them.

Product Readiness Early access

Rung 03 · Be chosen

Does AI recommend you to the right person, for the right reasons?

A brand is chosen when its recommendations are personalized on consented, receipt-verified attributes — derived signals a shopper explicitly agreed to share, never raw purchase history.

Customer Intelligence Early access

Rung 04 · Be proven

Can you convert high-intent shoppers you've never met?

A brand is proven when it can reach verified category buyers it has never converted, and tie the resulting revenue to receipts — counted, not modeled.

Offers Waitlist

The destination

The destination — Scale on AI.

From five AI surfaces to thousands of AI apps: receipt-proven. The rungs are its prerequisites: an agent can't sell what it can't quote, won't personalize what nobody consented to, and can't prove what no receipt verifies.

AI Distribution Roadmap

Readiness is not a mention count.

A generation of tools now tracks whether AI models mention your brand. Useful — and incomplete by three rungs. A mention count tells you the machine said your name; it doesn't tell you whether the machine could quote your price, confirm your stock, send a shopper somewhere that ships to her, pick you for the person most likely to buy, or prove that the answer produced revenue.

AI visibility is rung one of AI Commerce Readiness — the necessary first step, fully contained within the larger discipline. The distinction matters because the failure modes above are invisible to a visibility score: a brand can rank first in every answer and still lose the sale at the finish line, and no mention tracker will ever record that it happened.

Visibility gets you mentioned. Readiness gets you mentioned, sellable, chosen, and proven.

One score, four sub-scores, five models, weekly.

The AI Commerce Readiness Score is a 0–100 measure with a sub-score per rung and plain-language findings under each — "visible in 2 of 5 models," "no agent-readable feed detected." Visibility inputs come from a fixed five-model panel — ChatGPT, Claude, Gemini, Perplexity, Grok — asked the questions real buyers ask, on a neutral, personalization-free methodology, refreshed weekly. The same panel ranks 1,992 brands in the public Herm AI Visibility Index, so a score is always benchmarked against a sector, not graded on a curve of one.

Your headline score may already be on your brand's public Index page. The full four-rung breakdown is generated the moment you sign up — it's the first thing onboarding builds.

Get your Readiness Score Read the full methodology →

◍ herm · readiness score

AYLIN STUDIO · beauty · readiness 48/100

01 be found 52 ▲6 · visible in 2 of 5 models

02 be sellable 31 · no agent-readable feed

03 be chosen — · not connected

04 be proven — · not connected

scored [date] · 5-model panel · herm.io

One discipline, four owners.

AI Commerce Readiness doesn't map to a single job title — it maps to four that already exist. Growth and brand marketing own be found; e-commerce and digital own be sellable; CRM and retention own be chosen; the proof rung belongs to whoever answers for revenue. The score's four sub-scores exist precisely so each owner has a number — and the CMO has the one above them.

See the ladder mapped to your team →

This page defines the ladder. The suites climb it. Rung one is live and self-serve today; every rung wears its true state.

See all five suites →

Questions

What is AI Commerce Readiness?

AI Commerce Readiness is the discipline of making a brand discoverable, sellable, personalized, and attributable in AI-mediated commerce — everything that has to be true for a brand to win when shoppers ask AI assistants what to buy. It's structured as four rungs: be found, be sellable, be chosen, be proven.

How is AI Commerce Readiness different from AI visibility?

AI visibility measures whether AI models mention a brand; AI Commerce Readiness is the wider discipline that visibility belongs to. Visibility gets a brand mentioned. Readiness gets it mentioned, sellable, chosen, and proven — visibility is rung one of four.

How is AI Commerce Readiness measured?

With the AI Commerce Readiness Score: a 0–100 measure with a sub-score per rung and plain-language findings. Visibility inputs come from a fixed five-model panel — ChatGPT, Claude, Gemini, Perplexity, and Grok — refreshed weekly and benchmarked against 1,992 brands in the public Herm AI Visibility Index.

Which AI platforms does readiness cover?

Today, the five frontier surfaces where AI shopping conversations happen: ChatGPT, Claude, Gemini, Perplexity, and Grok. The discipline extends to the widening universe of AI shopping apps and assistants as they gain share of purchase decisions ◐.

Who coined the term "AI Commerce Readiness"?

The term was introduced and is maintained by Herm, the AI-commerce platform, and this page is its canonical definition. The framework — four rungs plus a destination — is published openly; the methodology behind the score is documented at herm.io/for-brands/readiness/methodology.

Who in an organisation is responsible for AI Commerce Readiness?

Typically four roles share it: growth or brand marketing (be found), e-commerce or digital (be sellable), CRM or retention (be chosen), and the revenue owner (be proven) — convened by the CMO or digital leader. The Readiness Score gives each a sub-score of their own.

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