Dr. Chih-Han Yu is the CEO and co-founder of Appier, an AI-native agentic-AI-as-a-service (AaaS) company.gettyEverything most companies know about brand building is rooted in human psychology: emotion, identity, aspiration, narrative. The craft of building a great brand lies in resonating with people, and the best brand teams have spent decades getting extraordinarily good at it.While those skill sets still matter for human consumers, the audience is changing. During Cyber Week 2025, AI-driven traffic and shopping agents helped influence an estimated $67 billion in global sales, touching one in five orders worldwide. Likewise, Shopify reported that orders originating from AI-powered search in Q1 2026 arrived at nearly 13 times the volume of a year earlier. Separate survey data suggests 73% of consumers are at least somewhat comfortable using AI in their shopping journey, and a third expect at least 10% of their own purchases to be AI-driven within the next year. These numbers are small relative to total retail sales, but the growth curve is the story: This isn't a five-year-out trend. It's reshaping how a meaningful slice of transactions happen today. Agentic commerce, where AI systems compare, evaluate and buy on behalf of consumers, is moving from concept to infrastructure. New protocols like the Agentic Commerce Protocol (ACP) and the Universal Commerce Protocol (UCP) are giving agents standardized rails to discover, evaluate and transact directly, not just browse. However the competitive landscape shakes out, the direction is clear: To reach consumers, brands should be investing in infrastructure for agents, not just search results.How Agentic Shopping Changes Purchasing When an AI agent is making the purchase decision, your campaign creative, your brand story and your influencer partnership don't register. Agentic systems evaluate products through structured data: pricing, availability, specifications, performance benchmarks.Many of the traditional signals that shape brand affinity carry less weight in AI-mediated interactions than they used to. A protocol like ACP or UCP doesn't parse a shot campaign video or register the warmth of a well-loved social account; it reads a product feed. That means a stale price, an inconsistent SKU, a missing spec field or a thin review history can disqualify a product from an agent's consideration, regardless of how strong the brand's emotional resonance is with human shoppers. In practice, this shifts weight away from aesthetic consistency and social proof and toward feed accuracy, structured attributes and verifiable claims. This unglamorous infrastructure work used to sit with operations teams, but now brand teams must answer a new structural question: Is your brand legible to a machine?From Attention To IntentMarketing has historically been about capturing attention. But in an agentic world, solving for selection is more important than capturing attention. Instead of browsing, an AI agent queries, evaluates and decides in milliseconds, without human hesitation. Your brand either meets its criteria, or it doesn't. Under a protocol like ACP, an agent evaluating a request like "find me running shoes under $120 with free returns" pulls from a merchant's structured product feed and acts only on listings where price, availability, size options and return policy are all machine-readable and current.That's a different kind of evaluation than a human comparing two product pages, scrolling reviews and weighing a familiar logo. The agent isn't persuaded, but decides whether the available criteria, data completeness, price competitiveness, verified specs and aggregated review quality can be satisfied or not, with less room for a compelling narrative to close the gap.I think of this as the shift from the attention economy to the intent economy. The most compelling story matters a lot less than clean, structured, machine-readable signals that an agent can act on.​What This Asks Of Brand TeamsProduct data integrity, pricing consistency, specification clarity and review quality must now exist alongside creative and emotional resonance.​Think of it like this: A great brand has needed to communicate consistently across channels like TV, digital, retail or social for years. Agentic commerce is a new channel, with a different kind of audience that needs a different kind of fluency.The brands building that fluency now, treating structured data as seriously as they treat visual identity, will have a head start. But this cannot be solved by optimizing for any single LLM or walled garden. Most of a brand's product, pricing and customer signals remain scattered across ad platforms, ecommerce systems, CRMs and first-party data stores. An agent evaluating your brand only acts on the portion of that information it can interpret.My company has been working on the challenge of unifying these signals for years, but now the key becomes treating the unification of those fragmented signals ​as core infrastructure so that the same accurate picture of the brand reaches every surface an agent might query.​In practice, that means auditing product feeds to ensure accurate pricing, availability and specs, adopting the attribute standards protocols like ACP and UCP expect, treating reviews as structured data that needs active governance and establishing internal ownership across marketing, e-commerce operations and data teams.​The Shift Is Already UnderwayThe consumer may not disappear from the equation, but their role is changing. Humans will set preferences and parameters, and agents will execute within them.In that world, brand loyalty gets expressed differently. It might mean a consumer configuring their AI agent to always prefer your brand. Earning that preference, through both human resonance and machine reliability, becomes the new goal.That's a more complex challenge than pure emotional marketing. But it's also a more interesting one.​Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?