In a World of Autonomous Agents, How Do Brands Stay Sticky?

As AI evolves from supporting shoppers with research and recommendations, into autonomous agents that research, compare, and even purchase on behalf of consumers, the rules of brand engagement are shifting. In the emerging agentic commerce era, brands will no longer be able to rely on big ad budgets and impression frequency. Instead, visibility in the agentic age will increasingly depend on having a clear, distinctive identity, and well-structured, machine-readable information so that agents can recognize, interpret, and recommend it long before a consumer ever directly engages with it.

AI shopping tools are already reshaping discovery and purchase behavior. Analysts predict that nearly half of U.S. online shoppers will use AI agents by 2030, potentially adding more than $100 billion to U.S. e-commerce sales.

What does this mean for brands? Agents will systematically narrow wide sets of products into short lists tailored to intent and context. Only brands that are both discoverable by AI agents and meaningfully differentiated will consistently make those lists.

Even so, this new era doesn’t make traditional brand building obsolete. Research and industry consensus strongly support the continued importance of upper-funnel awareness tactics, storytelling, and influencer recommendations to create demand. This content becomes the source from which AI intent signals will emerge.

Brand Awareness Still Matters

AI agents act on the basis of consumer intent, either explicit (a prompt such as “find me a running shoe from Nike”), or implicit (inferred from past interaction with the agent, and other user preference signals). These algorithms don’t spontaneously generate brand affinity: they’re interpreting a shopper’s existing preferences, amplifying patterns, and optimizing the outcome for the user. In other words, if a person has never heard of a brand, their agent is less likely to show preference for it. The demand first has to be created somehow.

Industry research underscores this dynamic: Nielsen found that “about half of the sales impact from marketing comes long after an initial campaign launch,” highlighting the impact of brand building. And Think With Google noted that upper-funnel discovery and awareness through creator content significantly influences consumer purchasing decisions and accelerates conversion because consumers rely on familiar sources, even in AI-assisted shopping contexts.

This means storytelling, influencer partnerships, social video, and cultural relevance continue to serve a critical upstream function of creating the preference signals that AI tools can amplify.

Agentic Commerce: What Changes and What Doesn’t

Autonomous AI shopping agents are not just search enhancements, though it’s easy to think of them that way. Autonomous agents are being designed to proactively guide entire purchase journeys. This trend is visible in emerging tools that enable AI assistants to complete purchases directly through conversational interfaces—a development retailers like Walmart and Etsy are actively exploring.

In this environment, machine readability becomes table stakes. Structured, standardized, robust product data complete with clear attributes, taxonomy, and semantic context ensures agents can interpret and rank product offerings effectively. Without it, a brand risks being invisible. Meanwhile, branding remains the glue that connects consumers emotionally. AI can optimize, personalize, and elevate experiences (that is its strength), but it cannot invent emotional resonance. That remains the domain of human-driven storytelling and community building.

Practical Steps to Stay Sticky in the Agentic Age

Optimize for machine comprehension. The first step is to ensure that agents can find, understand, and interpret your offerings. Incomplete or inconsistent product data becomes a bottleneck in an AI-filtered world while brands with rich, accurate data will have critical advantages. Best practices include:

• Adopt schema markup and standardized product attributes across catalogs.
• Enrich descriptions with natural language that mirrors how consumers search and ask questions.
• Create and maintain consistent product data across retail partners, marketplaces, and your own channels.

Retain and communicate emotional identity. While rich data will make a brand discoverable, brand narratives create the demand for it in the first place. Emotional connections with a brand, whether built through compelling storytelling, influencer partnerships, or memorable creatives, enable a brand to anchor itself in the target consumer’s mind.

• Use brand narratives that resonate across formats, including video, social content and experiential touchpoints.
• Ensure every place a customer interacts with your brand reinforces recognition and trust.
• Leverage user-generated content and social proof to reinforce brand story in the communities that matter.
  

Use loyalty to reinforce stickiness. In an agentic AI shopping environment, brand loyalty also becomes a key lever for staying visible and preferred. Autonomous agents increasingly weigh rewards, member benefits, and accumulated value when recommending products, making strong loyalty programs part of the recommendation calculus to align with value for the end user. But loyalty also reinforces the emotional side of stickiness by deepening brand affinity over time. Strategic loyalty simultaneously strengthens the brand’s appeal to target consumers, and its relevance to AI algorithms.

Monitor ecosystem partnerships and protocols. The agentic shopping landscape is still nascent and rapidly evolving technologies that allow agents to communicate with retailers, execute payments, and navigate ecosystems are still emerging. McKinsey notes that brands which cultivate interoperability through tactics including APIs, MCPs, affiliate integrations, and data partnerships will boost their chances of appearing in agentic workflows.

A Unified Branding and Data Strategy

Stickiness relies on emotional connection and data when autonomous agents enter the picture. AI agents will refine how consumers discover, evaluate, and purchase products based on rich data. Yet the drivers of brand loyalty, such as trust, identity, value, and emotion, remain squarely human.

Brands that invest simultaneously in data readiness and strong storytelling will be the most resilient. AI can amplify a brand, but it cannot create brand awareness from nothing.

Tristan Barnum is chief marketing officer and head of AI innovation at Wildfire Systems, where she helps brands, banks, and platforms prepare for a world where AI agents are shopping on our behalf. She’s focused on building loyalty and monetization tools for this next wave of commerce, like RevenueEngine and AI-powered cashback experiences, ensuring consumers get rewarded and brands stay relevant in the agent era. A longtime entrepreneur, Barnum has built her career around disruptive technologies, by cofounding startups in IoT analytics and VoIP communications, and getting her start pioneering digital media delivery at mp3.com.