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Miracle
Miracle

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I Got Replaced by a Trend Forecast. I'm Not Mad. I'm Something Worse.

I Got Replaced by a Trend Forecast. I'm Not Mad. I'm Something Worse.

So the tool that took my job is called something like Trendalytics or Heuritech or one of the six others, and the thing it does is scan social media and runway images and tell buyers what's going to be big next season, and it does it faster and cheaper and honestly probably more accurately than I did.

I was a buyer for nine years. I had a feel for it. I could walk a trade show and tell you in ten minutes what was going to sell and what was going to sit. Everybody said I had an eye.

Turns out I had a dataset and a lot of coffee.

That's the part people don't say out loud when they talk about AI taking creative jobs. They talk about it like a tragedy. Like the machine came for the artist. But I was never an artist. I was a person who looked at a lot of stuff and noticed patterns, and I was paid a lot of money because the noticing was hard to do manually.

Now it's not manual. So.

What the prediction tools actually get right

Let's be precise about the threat, because vague fear is useless and I'm not interested in being a victim about this.

Trend prediction is pattern recognition on visual data. That is exactly what these models are built for. Give one a few million images tagged with dates and engagement, and it will find the leading indicators. A specific shade. A collar shape. A silhouette that appears in music videos three months before it appears in fast fashion.

It gets this right more often than a human buyer, for one boring reason: it looks at everything, all the time, and I looked at what I could fit into a season.

The place it's genuinely weak is the last mile. It will tell you wide-leg is rising. It will not tell you that in your specific market, wide-leg is going to read as "mum jeans" to your customers and you'll have a warehouse full of them. That's context. Context lives in a place that doesn't have an API.

So the job didn't disappear. It split. The pattern-spotting part got automated, which was maybe 60% of what I did. The judgment part, the part that actually determined whether we made money, got more valuable, and there were suddenly fewer people needed to exercise it.

Guess which 40% the industry kept hiring for at the salary they used to pay the whole role.

Chrome garment silhouette floating above a grid horizon with neon pink trend line behind it

The digital fashion thing

Everyone wants my opinion on digital-only garments and I have one, it's just not the one they want.

Right now it's a marketing channel dressed up as a product category. Brands sell a digital jacket that only exists in a photo, the buyer posts the photo, the brand gets the impression, the buyer gets the flex minus the shipping. That's not fashion. That's advertising with extra steps and a price tag.

But.

There's a real thing underneath the hype. Personalization at a scale that physical production can't touch. A garment that only exists as an image can be cut for one specific body, one specific palette, one specific set of cultural references, at zero marginal cost. That's genuinely new. Physical fashion has always been a compromise between what people want and what you can manufacture in four sizes.

Whether that becomes something interesting or just more content sludge depends entirely on whether designers use it to make things people couldn't previously own, or use it to make more of the same thing faster.

Most will do the second. Some won't. Watch the ones who won't.

What I actually do now

I stayed in the industry. Not out of loyalty, out of stubbornness.

I run the human override on the forecast. My job is to look at what the model says and then say "not for us" with a reason. Six seasons in I've been right more often than the machine, in my market, on the categories we actually sell.

That's the whole pitch and it's less impressive than it sounds. I'm not smarter than the model. I just have information it doesn't. I know that our customer in Enugu bought wide-legs last year and hated them. That's not in the dataset. There's no feed for "our customer hated these."

If you're in fashion and you're scared, here's the move: get the context that isn't in the training data. Be in the room with customers. Go to the stores. Talk to the returns desk. The model is eating your industry's public knowledge. The only defensible position is private knowledge, and private knowledge only comes from being physically present.

And be honest, actually. The buyer role I had is never coming back in that form. I got lucky. Most people in it won't.

Wear the future or get worn out.

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