Anthropic has blueprints for building e-commerce bots that shop on behalf of clients. That's not something many consumers want at the moment, but the AI biz this week published a set of templates for Claude-based shopping agents and merchant agents in the hope of encouraging more e-commerce businesses to implement automated purchasing. Its blueprint "contains the harnesses, patterns, and guardrails an engineering team needs to get a commerce agent running in days, with reference implementations of a shopping agent and a merchant agent for retail, travel, telecom, and ticketing platforms," the company said. Large retailers and ecommerce platforms, Anthropic observes, are using Claude to build AI agents to simplify online shopping by allowing customers to pose natural language queries to find, compare, and buy items. The buying bit may be wishful thinking: A recent Gartner survey found that while consumers use AI to find products and conduct research, they're not ready to delegate purchasing authority to AI agents. The survey found just 11 percent of consumers are willing to let AI make purchase decisions. A recent Accenture survey [PDF] is a bit more optimistic, noting, "Three in four (74 percent) consumers would let an AI agent handle routine tasks; one in three (32 percent) are ready to hand over purchase decisions; and 9 percent are open to fully autonomous shopping, before the technology is fully operational." Either way, at least AI-assisted product finding and comparison appear to be plausible activities. Anthropic's GitHub repo contains functional shopping and merchant agents that can be built with the Messages API, Agent SDK, or Claude Managed Agents. The biz's shopping agent blueprint comes with ways to connect to product catalogs, online shopping carts, checkout systems, preference databases, and purchase history databases. "A customer can say 'I need a tent, sleeping bag, and stove for a weekend trip with two kids,' and the agent can take it from there," Anthropic suggests, noting that its code supports guardrails "designed to constrain prices and products to actual catalog data, and avoids manipulative upsell patterns." Why might prices need constraint? Well, beyond the possibility of hallucinated pricing, there's considerable concern about how AI agents have the potential to compound the problems with dynamic pricing – where customers are charged different amounts for the same goods. "The rise of agentic AI, where algorithms monitor online behavior to customize costs, will likely exacerbate dynamic pricing," said the Brookings Institution earlier this year. "These agents can assess individual behavior and tailor prices based on a consumer’s shopping and purchasing history." Concerns about AI surveillance pricing were discussed last month at a Senate Judiciary subcommittee hearing. In prepared remarks, Lindsay Owens, president and CEO of Groundwork Collaborative, a Washington, DC-based advocacy group, noted that already half of those using the Walmart app use "Sparky," the company's AI assistant. Those shoppers spend about 35 percent more than those who don't, Owens said. "These agents have access to swaths of data on customers – what shoppers tell them, what they’ve purchased in the past, and in some cases, what they’ve hovered over with their mouse or even what other websites they’ve visited," she said. "All of that can be used to infer exactly how much they’re willing to pay for a product and set the price tag accordingly." Even if shoppers can be assured of getting a fair deal using AI agents, there's another concern. Monica Eaton, founder and CEO of Chargebacks911, told The Register in an emailed statement that agentic commerce looks likely to create fraud problems for merchants. There isn't yet a framework for merchants to deal with AI purchases that consumers claim they didn't authorize. "Merchants cannot become the insurer of every misunderstanding between a consumer and their AI," she said. Anthropic's templates may prove helpful for AI agent design, but the real challenge isn't technical. It's about trust – consumers have to trust that AI will act in their best interest and merchants have to trust that AI will be accountable. That may take time. ®
