Everyone's thinking about it. Nobody's really talking openly about how they're approaching it. And I think that silence tells us something. People aren't sure what the right answer is. They're not sure what the industry and consumers expect. And no one wants to be the first to get it wrong.
We're in an awkward spot with AI right now. There's real pressure to adopt it — content is expensive, teams are lean, and the tools keep getting better. But there's this gut-level unease that AI and what we do don't quite fit together. That using it might undermine the thing that makes our brands matter in the first place.
I think that instinct is worth paying attention to.
We all know this, but it's worth stating plainly in this context: authenticity in outdoor isn't a marketing layer you add. It's the foundation. It's how we earn credibility with customers who actually use the gear. It's how we maintain standing in an industry where everyone knows everyone — athletes talk, retailers talk, reputation travels fast. And it's how we attract the talent — the athletes, filmmakers, creators — who choose to work with brands they believe in.
AI threatens all three if you get it wrong.
Think about what makes our content work. A Patagonia film connects because there's a real person on a real mountain telling a real story. The North Face builds credibility through athlete-led storytelling and field-tested product narratives. Arc'teryx's "No Wasted Days" campaign celebrated unconventional adventure stories with striking imagery and narrative depth. You can't generate that.
And the cost temptation is real. A product shoot in Moab can run $15–50K. A more ambitious expedition shoot can hit six figures fast. When AI tools can produce compelling visuals for a fraction of that, it's hard not to consider — especially if you're a smaller brand without a deep content budget.
But "cheaper" and "better" aren't the same thing. And the risk isn't just a bad ad. It's credibility damage with your customers, your peers, and the people you want creating on your behalf.
Here's the thing — this isn't a yes-or-no question. "Are you using AI?" is the wrong framing entirely. The real question is how you're using it. The spectrum is wide, and the risk profile changes dramatically depending on where you are on it.
Operations and supply chain. Demand forecasting, inventory management, logistics optimization. Columbia launched an AI-powered platform to personalize shopping experiences. Brands are using AI dashboards to consolidate regional sales data and make faster decisions. Nobody has a problem with this. It's smart business.
Research and insights. Consumer sentiment analysis, competitive intelligence, trend identification. AI is genuinely useful here, and it's completely invisible to the customer.
Workflow and production support. Using AI to tag and organize thousands of photos from a shoot. Generating rough edits from expedition footage. Writing first-draft product descriptions that a human then rewrites. The human is still steering — AI is just making them faster.
Supporting content. Social captions, email copy, ad variations, SEO content. This is where it starts to get gray. The output touches the customer, but AI is a tool in the process, not the product itself. Most of us are probably here already, whether we talk about it or not.
Brand campaigns and storytelling. Fully generated imagery, video, campaign creative. AI isn't supporting the brand — it is crafting the story. This is where things can break down, and where we have the most to lose.
The line isn't between "using AI" and "not using AI." It's between AI as infrastructure and AI as brand marketer. I think this gets close to the distinction that matters but, in the real world, it’s not this clean-cut.
And then there's the environmental piece — which, for our industry, should be impossible to ignore.
U.S. data centers consumed 183 terawatt-hours of electricity in 2024 — over 4% of the country's total — and that number is projected to more than double by 2030. Cornell researchers estimate that by 2030, AI growth will put 24 to 44 million metric tons of CO2 into the atmosphere annually. That's the equivalent of adding 5 to 10 million cars to U.S. roads.
Then there's water. An average 100-megawatt data center consumes about 2 million liters of water per day — roughly the equivalent of 6,500 households. Two-thirds of data centers built since 2022 are in water-stressed regions. In Arizona, data centers are expanding in counties where the state has restricted new home construction because of groundwater shortages. In Spain, a grassroots movement called "Tu Nube Seca Mi Río" — "Your Cloud is Drying My River" — is pushing for a moratorium on new facilities. Google paused a $200 million data center in Chile after legal challenges during a 15-year drought.
We work in an industry that donates to watershed conservation, builds campaigns around protecting public lands, and asks customers to repair instead of replace. The environmental cost of running AI at scale isn't a footnote, it is emerging as the lead story.
That doesn't mean don't use AI. But it does mean being honest about the tradeoff and that we need more awareness and conversation around the impact of AI on environment. The promise of generative AI is helping to fix the world's biggest problems, hopefully that includes the ones it’s contributing to.
The broader market is already stress-testing the boundary between AI and authenticity — and the results are worth paying attention to.
The Association of National Advertisers chose two words of the year for 2025 — for the first time ever: "authenticity" and "agentic AI." That pairing says everything about where things stand right now.
McDonald's Netherlands pulled a fully AI-generated Christmas ad after viewers called it "AI slop." Coca-Cola doubled down on AI holiday ads two years running and kept taking hits for it. Research from the Nuremberg Institute found that simply labeling content as AI-generated makes consumers view it as less natural and less useful. Researchers are calling this the "authenticity premium" — a measurable trust penalty when people detect AI authorship, especially in emotional contexts.
The perception gap is also worth noting. One study found that 82% of ad executives think younger consumers feel positively about AI-generated ads. The actual number among those consumers? 45%.
And here's the countertrend: Gartner projects that by 2026, 20% of brands will actively position themselves around the absence of AI in their products and campaigns. Aerie, Dove, and Polaroid have made explicit "human-made" commitments. Apple's holiday campaign pointedly featured handcrafted puppets on a real set. One industry observer called it a tipping point where AI-generated content is making human-made work a luxury good.
If any category is built to navigate the "authenticity premium," it's ours. The outdoor industry is set up to lead in this area and represent what it looks like to leverage AI for business and, at the same time, show up as authentic brand by continuing to invest in things that don’t scale. Let’s go to Moab!
We have a real advantage here. Real athletes, real landscapes, real stories, real community. The brands that lean into that — and use AI to support it rather than substitute for it — are the ones that will come out ahead.
Use AI to make the human stuff more efficiently. Don't use it to replace the human stuff entirely.
But I'm curious what you're seeing. How are you using AI to accelerate your brand? Who is using it well? Has the way you’ve thought about AI shifted in the last 6 months?
I want to hear it. Drop some replies in the comments.
