AI agents are shopping without you—will your brand still win?
In May 2025, MasterCard and Visa launched a new way to shop online. With AI. Two of the world’s largest payment networks have introduced autonomous agents that can perform online purchases on behalf of their customers.
Welcome to agent-to-agent (A2A) commerce, where generative AI agents transact directly with retailer platforms or other agents, without human intervention.
Imagine a shopper saying, “Buy the best face cream under $40,” and never touching their screen again. That purchase is now a negotiation between two digital minds.
This shift redefines the front lines of brand competition. You’re no longer selling to people. You’re selling to their algorithms.
What is agent-to-agent commerce?
A2A commerce, also known as agentic commerce, refers to digital transactions between autonomous AI agents acting on behalf of people or businesses, with minimal or no human interaction. These agents can search, filter, compare, and buy—end to end—based on the user’s goals and constraints.
Compared to today’s Large Language Models (LLMs), these AI agents are active rather than passive. LLMs respond to prompts, but A2A agents proactively initiate actions and make decisions with increasingly less need for a human to guide every step.
With A2A commerce, businesses need to evolve. You’re not just optimizing your PDP layout or your checkout UX anymore. You’re optimizing to be the one product that gets recommended to the AI when it executes the task.
Why customers are letting AI shop for them
Consumers are skipping search engines and turning to AI chatbots and voice assistants. Over 8.9 million people have already bought health and beauty products through voice interfaces. This year, spending through conversational commerce is projected to hit $290 billion.
Beyond voice, AI tools are increasingly integrated into e-commerce platforms to offer personalized recommendations. A growing portion of users rely on ChatGPT and other AI chat platforms for shopping advice, product comparisons, and reviews.
One reason is obvious: convenience. Customers don’t want to browse 20 tabs anymore. They want an answer, fast. That's where AI agents come in.
Amazon’s new “Buy for Me” tool skips websites entirely. It lets users say what they want and the AI executes the purchase directly from third-party retailers without ever leaving Amazon. Many consumers are happy to outsource decisions to a machine, so long as they trust it.
When AI owns the transaction, where does your brand fit?
The rise of AI shopping agents raises a pivotal question for brands: Who wins when an algorithm curates the options? Traditionally, brands invested heavily in marketing to influence human shoppers, like SEO, paid ads, and promotions. But when an AI assistant intermediates the purchase, the rules change.
For instance, Amazon’s Alexa tends to recommend a user’s past purchase or an “Amazon’s Choice” product first. In other words, if your brand isn’t the top result or a trusted favorite, it might not be heard at all.
Similarly, chat-based agents like Bing Chat or Siri will synthesize the “best” options for the user, potentially bypassing traditional advertising influence. This concentrates rewards for the top-performing or most AI-optimized brands, while others may see their visibility evaporate.
AI platforms (whether Amazon, Google, OpenAI, or others) could become the gatekeepers of consumer demand. If shoppers get used to saying “Hey Google, get me X,” the tech platform mediating that request might “own” the customer more than any particular brand does.
This has enormous implications: brands might find themselves competing to be the recommendation an AI gives (a bit like scrambling for the #1 spot in search engine results, but with even higher stakes).
AI-driven shopping may also cause customer loyalty to shift. What this means is, instead of being loyal to a brand, a consumer might become loyal to whichever product their trusted AI suggests.
GUIDE
Designing AI-powered shopping experiences for the next generation of commerce
The biggest risks brands face in an AI-first marketplace
Even as AI takes over the mechanics of shopping, customers still expect experiences that feel personalized and emotionally smart.
People want their assistant to remember their preferences, but not in a creepy way. They want convenience, but with transparency.
Here are the top challenges brands face:
- Confusion on where to start: Retail leaders know AI is key, but many don’t know which features will actually enhance the customer journey.
Solution: Use rapid user feedback to test prototypes before launch. Let real customers show you what works. - Fear of AI backlash: One bad chatbot interaction can tank your brand perception.
Solution: Run scenario-based tests to uncover confusing, robotic, or untrustworthy interactions before going live. - Pressure to innovate quickly, but blindly: Teams often rush AI deployments without knowing if they’re solving real problems.
Solution: Shorten the feedback loop. Use tools like UserTesting to validate every sprint with actual user reactions. - Privacy and personalization trade-offs: Customers want tailored suggestions, but not at the cost of their data comfort.
- Solution: Test for emotional response to personalization. Find the line between helpful and invasive.
- Internal chaos: Different teams pulling in different AI directions.
- Solution: Use customer evidence as a unifying lens. When everyone sees the same user pain points, alignment follows.
The silent failure of “almost-good” AI
Here’s a risk few brands talk about: the AI that works 70% of the time.
When an AI shopping agent mostly performs well but occasionally makes odd suggestions, drops context, or misreads intent, it causes them to slowly lose trust in the brand. Which could trigger abandonment.
You’ll see it in the data: lower repeat purchases, unexplained drop-offs, shrinking conversion rates. But the AI didn’t break. It just didn’t click.
This is the trap of silent failure. And it’s dangerous because it can go undetected for months. Unless you’re watching actual users interact with the experience, you’ll never know why they left.
Testing helps surface these micro-breakdowns, like the awkward phrasing, the irrelevant picks, or the uncanny valley moments. They’re small, but they matter.
Winning in the agentic era
So how do you win when AI is the new storefront? The answer: make AI your brand’s best customer advocate, not a faceless middleman.
Here are the essentials:
- Humanize the experience: Build empathy into your AI. Does your shopping assistant sound friendly, not robotic? Does it mirror your brand tone? Test until it feels like a conversation, not a script.
- Be transparent: Show users why the AI made a decision. A simple line like “Chosen because it matches your past purchases and price range” builds trust.
- Give control back: Let users opt out, fine-tune preferences, or talk to a human. That safety valve increases comfort.
- Test constantly: AI isn’t a one-and-done. Gather feedback, iterate, and re-test. What worked last quarter might not work next week.
- Align with your brand values: If your brand is all about curated expertise, your AI should feel like a digital concierge. Use technology to deepen your unique value, not dilute it.
- Educate your customers: Let them know how your AI works, how their data is used, and how they can benefit. Informed users are loyal users.
Algorithms buy fast, humans build trust
AI agents might finalize the purchase, but your brand still owns something AI can’t replicate: emotional resonance. The brands that thrive in A2A commerce won’t just be technically optimized. They’ll be trusted, familiar, and aligned with the customer’s personal values, because the customer is still setting the rules for their agent.
This is your chance to shape what those AI agents prefer. You can either be a silent casualty of invisible shopping… or the brand that machines and humans alike choose again and again.
Want to design AI shopping experiences that earn trust? See our guide to see how leading brands do it, with real customer insight.
Key takeaways
- AI agents are the new decision-makers. They don’t browse, they act. And they often return only one or two product choices.
- If your product isn’t top-ranked, it may not be seen at all. Agentic commerce compresses choice. Visibility is a winner-takes-most game.
- Traditional marketing tactics won’t cut it. SEO, ads, and visual merchandising lose power when AI intermediates the purchase.
- Silent AI failures can quietly damage your brand. When AI is “almost good,” users lose trust without you ever seeing the drop-off.
- Customer feedback is your most valuable insurance. Testing reveals what the data misses, like hesitations, confusion, and emotional responses.
FAQ
Q: What is agent-to-agent (A2A) commerce?
A: A2A commerce refers to transactions completed autonomously between two AI agents, usually one representing a consumer and the other representing a business or retail platform. It’s shopping, but with humans out of the loop.
Q: Will AI replace human decision-making completely?
A: Not entirely. Consumers still set preferences, constraints, and goals. But AI agents increasingly handle execution—search, compare, checkout—especially for routine or low-stakes purchases.
Q: How does this affect traditional marketing?
A: Most marketing is still aimed at human attention. But when AI intermediates the purchase, that attention is redirected. Brands need to optimize for AI visibility and trustworthiness, not just visual appeal.
Q: What’s the best way to prepare?
A: Test everything. Use platforms like UserTesting to prototype your AI features, simulate AI-agent behavior, and uncover how real users respond to your digital experiences. Then iterate with speed and clarity.
GUIDE
