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You鈥檝e just moved into a new house. It鈥檚 unfurnished; the walls are bare. Ten years ago, you might have loaded up and started searching for furniture that you like, consulting interior design magazines and looking for offers on retailers’ websites. In 2026, however, there鈥檚 an entirely different option at your fingertips. You could take a photo of the empty room, upload the image to an AI agent, share your budget and style, and get a list of furniture that suits your preferences. You could even have the agent purchase on your behalf.

Instead of just selling to one customer base 鈥� humans 鈥� brands are now selling to two.

This second audience of AI agents makes decisions on different criteria than humans. Often, in fact, AI agents will make purchasing decisions before a human ever sees the product page. There鈥檚 a real chance that all the emotive copy marketers have so carefully crafted will get broken down and reconstituted by a machine. Just relying on the human touch isn鈥檛 enough anymore.

Leave humans in the equation

A word of caution, though: Marketers shouldn鈥檛 forget the human entirely in the rush to prepare for AI agents. It鈥檚 easy to get carried away with visions of an entirely agentic future. But at the end of the day, each agent is still catering to a human with their own preferences, and personalization will only get more granular over time. The trick is to optimize for both audiences simultaneously, not just one.

Newer startup founders have the advantage here. Established brands have to retrofit decades of copy, guidelines and approval processes to make themselves agent-ready. New brands, on the other hand, can build in copy and a brand voice that鈥檚 legible to humans and agents from the very start.

But what does this look like in practice?

To start, brands should work out a distinct voice 鈥� and write it down. In most early-stage companies, the brand voice solely exists in the founder鈥檚 head. This might work if the copy鈥檚 written by a handful of people who work with the founder, but it doesn鈥檛 work well when the writer 鈥� or reader 鈥� is a machine.

AI tools follow explicit rules and drift without them. I’ve spent years at my startup, , working out how to get AI agents to write better content, but it’s only now that we’re seeing agents on the other side of the process too 鈥� and that makes the rules matter even more.

What a brand sounds like matters, but what it doesn鈥檛 sound like matters just as much. Brands should note words never to use and the claims never to make. Often these instincts don鈥檛 get written down; they feel obvious to the team who already know them. But if you take the time to spell them out before you have a team 鈥� or a machine 鈥� producing your copy, you鈥檒l save yourself from running into issues further down the line.

Verify your brand

Marketers also need to realize that product descriptions aren’t just administrative: they鈥檙e now core brand assets. In an agent-mediated world, they may be the most-read brand copy you own, since agents read them when looking for a product to recommend or purchase. If two personalized AI agents look for furniture for two different people, they may surface the same chair for both, but with the description tweaked for each user. The source description needs to carry the brand intact.

Where possible, brands need to test channels for both readers. Email inboxes are the clearest current example of the 鈥渟econd reader.鈥� Both Gmail and now summarize messages before the recipient opens them and offer summaries above the body of the email 鈥� which may be read before the email itself.

So before sending, check what the AI summary says your email is about. Does the offer survive? Does it maintain what makes you unique? It鈥檚 not time-intensive, and it鈥檚 a small habit any marketing team can adopt today with no tooling.

Brands also need to ensure they鈥檙e measuring the outcome of their marketing 鈥� not just the volume. Marketers who measure the success of their materials only by the amount produced will find their data meaningless as AI makes content production easier and easier. Focus instead on business outcomes, conversions and revenue. These are the metrics that will show if your marketing team is really doing their job.

And finally, don鈥檛 lose sight of the human. No one knows how fast AI purchasing will scale. Humans are still predominantly the ones reading copy and making purchasing decisions. Even AI agents, the second audience, cater to their users鈥� preferences.

New founders and brands are best positioned to take advantage of the transition to a dual-audience economy. Though it鈥檚 hard to say exactly how, the retail landscape will look very different in five or 10 years. Building these decisions into your brand now is easy.

Retrofitting them later is expensive.

is chief product and growth officer at, an AI platform that helps brands generate and optimize bespoke messaging at scale.

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