AI agents that discover, evaluate, and complete purchases on a person’s behalf, moving transactions from manual browsing and checkout to autonomous, agent mediated decisions.
Also known as AI driven checkout, autonomous purchasing, agent led commerce
Agentic commerce describes purchases where an AI agent, not a person clicking through a cart, does the discovering, comparing, and buying. A shopper tells an assistant what they need (a birthday gift, a weekly grocery order, a replacement part) and the agent searches, compares options against stated preferences and budget, and completes the transaction, often through a payment protocol built for machine initiated purchases rather than a human at a keyboard.
In 2026 this moved from pilot to production. Google, Microsoft, and Perplexity all ship agentic checkout inside their assistants, the major card networks support agent initiated payments, and protocols like the Agentic Commerce Protocol standardize how an agent proves it is authorized to buy on someone’s behalf. Routine, repeat purchases are the leading edge: the categories people already buy on autopilot are the ones agents take over first.
For agencies, agentic commerce is not a new channel so much as a new buyer. The audience an ad has to persuade is increasingly a piece of software acting on stated preferences, and that changes what conversion measures.
Product data becomes the ad. An agent does not see your banner, it reads your product feed, reviews, price, and return policy. Structured, accurate data is now a ranking factor the way SEO keywords used to be.
Attribution gets harder before it gets easier. If an agent compares five retailers and buys from one, the losing four may never know a shopper considered them. Agencies need new ways to prove influence earlier in a funnel an agent compresses into seconds.
Brand trust has to be earned upstream. Since a person may not review the final choice, brand reputation, price competitiveness, and policy clarity need to be strong enough that an agent’s default behavior favors you.
A DTC skincare client sells through their own site and three marketplaces. Your team notices agent driven traffic converting differently: no time on page, no scroll depth, a single hit that ends in a completed order confirmation via API. Working with the client’s dev team, you clean up the product feed (accurate ingredient lists, clear return windows, consistent pricing across channels) because an agent comparing options penalizes any inconsistency it can detect. You also negotiate faster shipping SLAs, since agents increasingly filter on delivery speed before price. Within a quarter, agent originated orders go from a rounding error to a measurable line in the client’s revenue report, and the brief for next quarter’s creative work shifts to include structured data audits alongside the usual campaign assets.
The automations and agents module of the workshop teaches you how to build AI workflows that compress the busywork without taking the craft out of the studio.