Q UA RT E R _ 0 2 _ 2 0 2 6 137 - - For these reasons, the model is best under stood as a curve rather than a ladder. Higher levels of automation are not inherently better or more advanced, and the goal is not maximum autonomy but optimal delegation. - LEVEL 0: Program Convenience (‘Set and Forget’) This level is the pre-agentic baseline: Recurring replenishment for things that run out—coffee pods, detergent, diapers, shampoo—is handled through subscriptions, scheduled refills, and recurring shipments. At this point on the curve, automation is rules-based: useful but brittle and largely blind to context. When needs change, it breaks, and the human steps back in. Still, level 0 proves a foundational point at which consumers delegate when automation is reliable and reversible. For example, around 23 percent of US Amazon shoppers had at least one active Sub scribe & Save order in 2024. AI agents could mediate $3 trillion to $5 trillion of global consumer commerce by 2030. - LEVEL 1: Assist (‘The Cognitive Sidekick’) At level 1, agents help shoppers think and make decisions, but they do not execute. A shopper might ask, “Find four gifts under $75 that can ship by Friday; prefer sustainable brands; and summarize trade-offs.” Or, in a more complex category, “Compare three noise-canceling head phones, and explain how they differ on sound quality, battery life, and comfort.” The agent’s role is analytical. It scans catalogs, parses reviews, compares features, and synthesizes options into short lists or recommendations. Crucially, it does not commit to a configuration or resolve opera tional constraints. There is no cart, no basket, and no readiness to transact. The human evaluates the options, weighs trade-offs, and decides what to do next. In other words, level 1 replaces search and com parison but leaves assembly and execution entirely with the shopper. - Implications for retailers: Verifiable data beats marketing gloss. Agents require information they can parse and compare—structured attributes, clear eligibility rules, sizing and fit certainty, and claims that can be substantiated. LEVEL 2: Assemble (‘The Personal Shopper’) Level 2 marks a qualitative shift: Agents move from analysis to orchestration. Here, the shop per expresses an intent, and the agent returns a purchase-ready basket. “Build a cozy winter out fit under $150.” “Stock a pantry for a vegan guest arriving tomorrow and staying for three days.” Or, more complex, “Put together a home office setup under $2,000 that supports dual 4K monitors and quiet video calls and has next-day delivery.” Unlike level 1, the agent is tasked with resolving trade-offs and constraints rather than merely surfacing them. It selects specific items, ensures technical com patibility, and balances performance against price, availability against delivery speed, and promotions against eligibility. Taxes, shipping windows, loyalty benefits, and substitutions are handled by default. The output is not a list of options; it is a coherent configuration that is ready to check out. The shop per’s role shifts accordingly from comparing options to approving or adjusting a proposed solution. - - Implications for retailers: Success at level 2 requires API-first merchandising. Inventory, pricing, shipping promises, promotions, and returns logic must be exposed cleanly so agents can assemble baskets with human-level fidelity. - -