In 2016, Andy Dunn published "The Book of DNVB" and gave a name to something that had been building for years. Digitally native vertical brands. Born online, own the customer relationship, cut out the middleman.
Bonobos, Warby Parker, Glossier, Allbirds. I co-founded one of them (Koio, a luxury footwear brand we built over 10 years and recently sold). Hundreds of brands launched on this thesis. It reshaped retail.
A decade later, every brand sells online. Every brand has a Shopify store, runs Meta ads, and sends Klaviyo flows.
What was once a structural advantage became a distribution channel. The playbook that built these brands stopped being a differentiator and started being table stakes.
Now there's a new term gaining traction: "AI native."
So far, it's mostly being used in the software world. VCs like Antler use it to describe founders who build with AI from day one. a16z has written about "AI-native workflows." IBM defines an AI-native company as one where removing the AI would make the product stop working entirely.
Nobody is really talking about what AI native means for consumer brands. I think that's about to change. And there's a question underneath it that most people aren't asking yet: what happens when the customer isn't even the one shopping?
What does an AI-native consumer brand actually look like?
The DNVB era had a clear definition: born online, vertical, direct to consumer.
AI native is harder to pin down because AI touches every part of how a brand operates. It's less about one channel and more about the entire operating model.
At Koio, we built an AI agent that reconciled our 3PL invoices line by line. It found 10-20% overbilling rates. Money that had been walking out the door every month for years, caught in minutes. We used four different 3PLs over the life of the business and got overcharged by every single one. That's one AI agent doing one job. Now multiply that across customer service, ad creative, product development, demand forecasting, and email marketing.
An AI-native consumer brand is one where AI is embedded in the core of how the business runs. How it develops products. How it acquires customers. How it manages operations. Remove the AI, and the business fundamentally changes.
The team is smaller. The margins are structurally higher. The speed of iteration is faster.
A brand doing $50M in revenue with five people and AI-native operations is a completely different business than one doing $50M with 50 people and traditional infrastructure. We ran Koio with a fraction of the team our revenue would have required three years earlier. Across the industry, founders are getting more comfortable running leaner. The teams are shrinking, and the output isn't.
Same revenue, completely different economics. That's where this is heading.
Every AI-native brand will look the same. Just like every DNVB did.
The DNVB wave had an unintended consequence: it made every brand look and feel the same.
Same Shopify theme. Same unboxing experience. Same "our story" page. Same influencer playbook. Digital-native brands were structurally identical. The only real differentiation was the product itself and the founder's story.
AI-native brands could go the same way.
If every brand uses AI for customer service, product development, ad creation, and email marketing, what actually differentiates them? When AI can generate the product photography, write the copy, optimize the targeting, and personalize the emails, what's left that's uniquely yours?
What AI can't replicate
AI can generate a brand identity in minutes. It can produce content at scale. It can match your pricing, your targeting, your messaging cadence.
So what can't it replicate?
Taste. Point of view. Lived experience. The reason someone started the brand in the first place.
Take Faherty for example. Mike Faherty spent seven years at Ralph Lauren learning fabric mills and pattern construction before launching Faherty with his twin brother Alex, who emptied his Wall Street savings to fund the first production run. That brand exists because of a specific upbringing, a specific obsession with coastal style, and a decade of learning how clothes are actually made.
AI can optimize how you tell those stories. It can't create them.
I think AI-native brands will need to be more human, not less. The operational layer can be AI. The customer acquisition can be AI. The back office can be AI.
But the brand itself (the reason it exists, the taste behind the product, the perspective it brings to the market) has to be deeply human. Otherwise you're just an algorithm selling commodities.
What happens when the customer isn't even shopping?
There's a split coming. For everyday purchases (toothpaste, batteries, paper towels), customers won't care whether a brand is AI-native. They'll care about speed, price, and convenience. The brand that delivers fastest and cheapest wins.
For luxury and identity purchases (the sneakers you wear, the bag you carry, the watch on your wrist), they'll still want to know there's a person behind the brand. They're buying taste, not logistics.
That split matters. But it's not the most interesting part of what's changing.
AI agents are starting to shop on behalf of customers. Not just recommending products, but evaluating options, comparing prices, checking reviews, and making purchases. McKinsey is already calling it "agentic commerce." The customer sets preferences, and the agent handles the rest.
Think about what that means for brands.
Today, you build a brand to appeal to a person. You tell a story. You create an aesthetic. You build an emotional connection.
When an AI agent is the one making the purchase decision, none of that matters in the same way. The agent doesn't care about your Instagram grid or your founder story. It cares about product specs, return policies, price, reviews, and whether the data it can find about your brand matches what the customer asked for.
You're building for two audiences at once: the human who defines what they want, and the AI agent that goes and finds it.
This creates a strange tension for AI-native brands.
On the operations side, you're building for efficiency and speed. On the brand side, you still need to be meaningful to humans, because the human is the one who sets the preferences the agent acts on.
If a customer tells their AI agent "find me high-quality Italian leather sneakers from a brand I can trust," the agent needs to find enough signal online (real reviews, real press, real community) to identify your brand as the answer.
The brands that win in this world will be genuinely worth choosing (for the human) and easy to understand (for the agent). Clean product data. Clear brand positioning. Real customer advocacy that shows up in the places AI looks.
The brands built on paid acquisition and polished aesthetics with nothing underneath? Invisible. An AI agent can see right through a brand that looks good but has thin reviews, no organic mentions, and a generic product.
Where this goes
The DNVB thesis played out in about a decade. Born in the early 2010s, peaked around 2018-2020, became table stakes by 2024.
I think AI native will move faster because the underlying technology is improving faster than the internet did.
Within two to three years, "AI native" will be the expected operating model for any new consumer brand. The same way having a website and Instagram presence is expected today.
The brands building this way now will have a head start. The ones that wait will find themselves trying to retrofit, which is possible but harder. That's exactly what we did at Koio. I can tell you firsthand: layering AI onto a business that wasn't built for it works, but it's messy.
The more interesting question is what happens after AI native becomes table stakes too.
If every brand can operate with AI-level efficiency, what's left? The same thing that's always been left. The brands with a reason to exist that goes beyond the algorithm.
Technology changes how brands are built. It never changes why they're built.
If you're building an AI-native consumer brand, or figuring out what that even means for your category, I'd love to hear what you're seeing.