The fashion industry is at a crossroads. Promising a once-in-a-generation technological revolution, artificial intelligence is emerging against the backdrop of an already turbulent macroeconomic landscape, setting the stage for upheaval in the industry this year.
When it comes to technology disruption, this has been clearly announced. AI is already changing the way consumers buy clothes and run fashion businesses, from creating marketing images to compiling insights for merchandising teams to transforming back-office jobs.
This reversal, like other reversals before it, will reward leaders who intervene early and penalize those who sit back too long. History shows this is not a hypothetical risk. See how the Internet has changed the home entertainment business.
When the Internet emerged, Blockbuster, the dominant video rental chain, had every advantage: scale, brand, distribution, and capital. However, the company failed to adapt to what turned out to be major structural changes in the home entertainment market. Blockbuster didn’t understand and embrace how people discover, consume, and pay for video in new technological realities.
Netflix, on the other hand, hasn’t just embraced new technology. The company built and continually reinvented its business, growing from mail-order DVDs to a streaming giant.
Currently, only one Blockbuster store remains (in Bend, Oregon), but Netflix boasts more than 300 million paid subscribers in more than 190 countries and is moving to acquire Warner Bros.
Fashion is currently facing a similar but even more important crossroads, with AI advancing faster than digital video ever has. How fashion leaders respond in the coming months, yes months, will determine which companies are positioned to grow in the years ahead.
Are you a Blockbuster or Netflix person?
If you’ve read this far, chances are you have a sneaking suspicion that you work for or lead a blockbuster company. These companies are taking a wait-and-see attitude toward AI. Executives pay lip service to AI in board meetings and earnings calls, but at best they insert poorly-fitting brand-name tools into outdated processes with shallow integrations, protect legacy workflows, and assume that only scale will save workflows.
Netflix in this story is more than just a startup trying to cannibalize established brands. This includes innovative incumbents who see opportunities to aggressively reshape their businesses around AI and new consumer behaviors. They are redesigning their decision-making, considering new ways to develop and sell fashion, and generally moving faster.
The AI chief executive will not save you.
There is a comfortable illusion in the industry that “hire an AI chief executive and the problem will be solved.” That won’t happen. In this day and age, the CEO must be the chief executive of AI. AI is not a department. It should be the operating system of your business.
But the fashion industry still manages a multibillion-dollar supply chain with what I call “blockbuster energy,” relying on endless email threads, static Excel sheets, disconnected PLM systems, and manual approvals that slow everything down. The short-term value of AI is not just in the creative things that seem to be the focus of industry attention. It’s operational. Eliminate unforced errors, catch bad data before it becomes seven digits wrong, condense weeks of sampling into hours of simulation, predict microtrends early to improve supply and demand alignment, and avoid costly overproduction.
steal this plan
Six months ago, I too was feeling overwhelmed. Investors challenged me to truly master AI and provide them with a concrete roadmap on how to use AI to grow faster and more efficiently. Within 90 days, A-Frame has fundamentally changed.
Here we explain exactly what we did and how we did it.
1. Hire an expert. and become one.
There were no plans to hire a CTO. Our recruitment roadmap focuses on product development, brand and growth. However, it has become clear that without deep technical leadership, any AI effort will stall or remain superficial. So we changed our plans.
We hired a CTO who could design systems, not just tools. Their job was not to “own” AI, but to embed it throughout the company and train employees on how to use it. Within weeks, AI literacy ceased to be abstract and began to shape real-world decisions, including identifying product opportunities, generating designs and specifications, managing communications, forecasting, sampling, and ultimately launching new product lines.
2. Start from the top down and bottom up
We didn’t start with tools, we started with people. We interviewed all of our team members and asked them the same questions.
- Where do you waste your time?
- Where is the expertise locked away?
- Where are mistakes repeated?
- What daily tasks do you think are necessary but don’t require time?
The answers were surprisingly consistent. High-skilled professionals spent 30% to 50% of their time doing low-skilled work. Product developers were overwhelmed with tracking the same data across systems. Distributors were unable to understand sales and demand in real time. Our marketing department was looking everywhere for the right trend data, and our design team couldn’t keep track of all our needs and requirements. Rather than shiny AI demos, these friction points became the focus of our roadmap.
3. When to buy and build tools
We resisted the urge to build everything. If a best-in-class tool already exists, we licensed it. But where our advantage is unique, such as how we identify and evaluate trends, license brands, allocate capital, and manage the complexity of multiple brands, we’ve built custom systems. AI should not commercialize what makes you special. You should protect it.
4. Incorporate AI into your workflow
Chat-based tools like ChatGPT and Claude are great for brainstorming, strategy, and creativity. But the real gains came from what we call hard AI: automated workflows that quietly eliminate manual work and reduce time to market by more than 40%.
If AI lives outside of the workflow, it dies. We embedded it directly into the tools teams already use. The result was an extension, not a replacement. The team’s work did not decrease. They worked faster, smarter, and with fewer costly mistakes.
5. Small-scale automation trumps large-scale models
No moonshot required. We focused on dozens of small, targeted automations placed precisely at friction points. Each one saved me minutes to hours. They worked together to rebuild the entire system. That’s how the speed increases.
It’s time to wake up
The future of AI is not coming. It’s already here. AI will not replace leaders in fashion, but leaders who use AI will replace leaders who do not use AI. The bot does the shopping. The bot will negotiate. Bots discover costly mistakes that humans keep making. Fashion leaders can prepare, learn and build for this moment, or become a case study for the next generation. It’s all real and it’s happening right now.
The only question left is: Will they adapt and embrace technological change like Netflix? Or will it fade away like a blockbuster?
Ari Bloom is the co-founder and CEO of A-Frame Brands.
