AI Shopping Agents Could Steer Up to $385 Billion by 2030

Agent-influenced shopping could account for $190 billion to $385 billion in U.S. e-commerce spending by 2030 — 10% to 20% of the entire market — according to Morgan Stanley. The most important shopper of the future isn't human, and the gatekeeper deciding which brands get considered is increasingly an AI system that never sees your ad campaign the way a person does.

A shopper asks an AI assistant for sneakers for a 23-year-old. Another Googles a boutique hotel in Rome. Before either sees a picture of a shoe or a room, AI has already helped decide which brands deserve consideration. Mental availability is no longer formed directly by communications and shopper experience; a new intermediary has stepped in, embedded in familiar services like Google, where AI-generated answers appear before people ever visit a brand's website.

What does this change for brand owners?

The uncomfortable answer: humans forgive, machines don't. People can accommodate changing messages within an existing emotional attachment to a brand. Machines share no such attachment. Fragmented messaging or unsupported claims leave AI systems with conflicting information, making them less likely to recommend the brand.

Even the biggest names can't assume they'll appear. Authors writing in Harvard Business Review in 2026 found that Brooks appeared more reliably than Nike in their tests of AI recommendations for running shoes. In another test, when AI was asked to recommend a running shoe for a 23-year-old, Nike didn't feature in the top three — despite owning the Swoosh and "Just Do It."

Why? The research points to two failures. Competitors built stronger associations with emerging buying needs: New Balance on authenticity, Lululemon on wellness. And Nike's own narrative suffers from semantic contradictions: "Just do it," "Believe in something," "Why do it?" Irrespective of how emotionally appealing that is to humans, the machine finds the contradictions and declines to recommend the brand.

Dove shows a subtler version of the problem. Its real beauty message built a powerful position around inclusion. Yet when researchers asked an AI assistant to recommend a good cream for sensitive skin, Dove did not appear. Asked why, the assistant associated the brand with affordability. The broader message hadn't translated into relevance for that specific skincare request.

How do you build for both audiences?

The research into AI and brand magnetism identifies a baseline: brands need at least three ownable distinctive assets and a clear, relevant narrative to build both mental availability and machine awareness. KitKat's "Take a break" is the model — it gives people a reason to reach for the brand beyond chocolate, and it gives the machine a single consistent meaning to validate.

Then comes discipline in execution. A social post may feel fresh in isolation, but if it introduces a conflicting message, it adds confusion to the brand's wider digital footprint. Marketers' impatience gets expensive: your team may be tired of a campaign long before customers have properly registered it, and internal boredom is no reason to discard an association still under construction.

The long game pays off in the machines, too. Research by Charlie Oscar, reported by WARC, analyzed 30 brands across six categories and attributed 63% of LLM visibility to long-term brand equity. AI pulls from everything, so years of brand building matter — Volvo's long-settled association with safety being the textbook case.

Heinz illustrates the value of continuity. Years ago, there was discussion about removing its keystone logo because it seemed old-fashioned. The surrounding communications could be refreshed without discarding the symbol that made the brand recognizable. The rule for practitioners: be clear about what must not change — ownable visual assets and core narrative — and what can: executions. Change the shirt, change the earrings, but remain recognizably yourself.

The same discipline applies to promises. Claims must reflect what the business actually does, with evidence to support them — because the machine checks.

Brands are racing into SEO, GEO and Reddit strategies, but that landscape keeps evolving. The durable play is structural: emotional appeal for people, plus information machines can use to understand that relevance. It's a sharper brief for creativity, and brands that master both early will be harder to displace.