Struggling to predict next season’s bestsellers? Tired of relying on gut instinct? AI is already helping brands call the shots – faster, smarter and without the guesswork.Think you’ve got fashion trends figured out? Not so fast. Social media, shifting consumer habits and viral moments can turn yesterday’s bestsellers into today’s clearance rack.
Miss the signals and you’re stuck with stock no one wants.
From Gut Instinct to AI – The Fashion Forecasting Shake Up
Fashion forecasting used to be controlled by industry insiders – those who attended Paris and Milan fashion weeks, analysed street style and dictated what would be “in” long before garments hit the shelves. Remember how a single decision from a top designer used to set the course for an entire season – what they chose dictated what retailers stocked and what shoppers bought.
That was true – until AI entered the picture.
Now, trend influence is no longer dictated by a select few. A single post from a celebrity or influencer can send demand soaring overnight, leaving brands scrambling.
The challenge? Spotting these shifts before they explode. That’s where AI comes in.
Sticking to Old School Forecasting? Might as Well Read Tea Leaves
Relying on traditional methods is a gamble. You might as well flip a coin – fashion changes way too quickly for guesswork.
Trends are constantly shifting, driven by:-
- Social media and influencers
- Celebrity & pop culture trends
- Weather patterns and seasonal shifts
- Fashion week trends
- Online shopping behavior
- Sustainability concerns
- Changing consumer values
There’s too much data for humans to track manually. Brands that don’t adapt risk stocking the wrong styles while missing out on the real demand.
AI – The Fashion Industry’s Crystal Ball (Minus the Guesswork)
AI removes the guesswork, analysing huge amounts of data to spot patterns and predict trends faster than ever.
Here’s how it’s changing the industry:-
1. Social Media & Influencers – Because TikTok Moves Faster Than You Do
AI tracks social media in real-time, identifying rising trends before they explode. Tools like WGSN and Heuritech analyse what influencers and shoppers are wearing, predicting which styles will take off.
Example: If AI sees a rise in cargo pants across Instagram, Pinterest and TikTok, brands can act fast – adjusting production and marketing before competitors catch on.
2. Celebrity & Pop Culture Trends – The Power of One Viral Moment
AI can track the impact of celebrity outfits, movie wardrobes and viral fashion moments. If a trending look starts selling out, AI can predict related styles that will gain traction next.
Example: AI detects a surge in demand for red carpet inspired satin dresses right after an awards show, allowing brands to pivot quickly.
3. Weather-Driven Demand – When AI Reads the Forecast
AI doesn’t just track trends – it also reacts to weather changes in real-time. Sudden cold snaps, heatwaves or unexpected rain can influence demand for specific items.
Example: If AI detects a heatwave in Europe, it can suggest pushing ads for linen and summer dresses while pausing promotions for knitwear.
4. Fashion Shows – No More Waiting for Reports
AI scans thousands of fashion show images instantly, spotting patterns in styles, fabrics and colours. Platforms like Tagwalk tag trends in real-time, so brands don’t have to wait for trend forecasters to tell them what’s next.
5. Online Shopping Behaviour – If They’re Looking for It, You Should Be Stocking It
AI powered tools like Google Trends and Semrush track what people are searching for. If interest in “denim maxi skirts” jumps 300% in a month, brands can pivot production and marketing accordingly.
6. Sustainability Concerns – AI Helps Brands Stay Ethical
AI can track consumer demand for sustainable fashion, helping brands make smarter sourcing and production decisions. By analysing trends in eco-friendly materials, resale platforms and circular fashion, AI ensures brands align with shifting values.
Example: AI detects rising interest in biodegradable fabrics and suggests adjusting inventory to meet demand.
6. Changing Consumer Values – Understanding What Matters Most
AI analyses sentiment from customer reviews, surveys and social media to understand how values like inclusivity, comfort and personalisation shape shopping habits.
Example: If AI spots a surge in demand for gender neutral fashion, brands can quickly adapt their collections to align with shifting consumer expectations.
7. Generative AI – Catching Trending Terms Before They Cost You Sales
GenAI helps brands stay ahead by picking up on new trend names and viral fashion terms before they go mainstream.
Example: When TikTok coined the term “LumberJane” for oversized plaid shirts – a fabric with a crisscross pattern of lines – shoppers started searching for it. But many retailers didn’t use that term in their product listings, meaning customers couldn’t find the items even though they were in stock. That meant no results, no sales and a missed opportunity. AI now tracks these language shifts in real time, updating product descriptions so brands don’t miss out on viral moments.
Why AI Forecasting Isn’t Just About Trends – It’s About Profits
Using AI for forecasting isn’t just about being ahead of the curve – it’s about better business results:-
- More sales – Stock what people actually want, when they want it.
- Less waste – Reduce overproduction and avoid unsold stock. The fashion industry is already responsible for over 10% of global carbon emissions and that’s expected to rise 50% by 2030 (Fibre2Fashion).
- Happier customers – When inventory matches demand, shoppers find what they want faster – and they keep coming back.
With 73% of fashion executives prioritising AI in 2024 (McKinsey), it’s clear that old school forecasting is on its way out.
AI vs. Humans – Who’s Really in Charge of Fashion’s Future?
Does AI mean fashion forecasters are out of a job? Not quite. AI processes data and predicts trends, but people make the final call – deciding how to turn insights into styles that sell.
Brands using AI have seen major results:-
Brands using AI have seen major results:-
In 2020, Levi’s partnered with Google Cloud to analyse search trends, retail data and social media activity, allowing them to predict the comeback of baggy jeans before demand peaked. AI spotted early signs that looser denim styles were gaining traction, allowing Levi’s to adjust marketing and product focus ahead of competitors. By the time the trend became mainstream, Levi’s was ahead of the game – securing increased sales while competitors scrambled to keep up.
So, will AI take over fashion forecasting?
Let’s just say you don’t want to be the last brand still guessing.
Forecast It. Stock It. Sell It.
But spotting trends is only half the battle.
The real challenge? Managing stock efficiently once you know what’s hot.
That’s where Stok.ly Cloud ERP comes in.
Fashion retail is unpredictable and outdated inventory systems mean missed opportunities. Stok.ly helps brands stay agile with real-time stock tracking, automated reordering and seamless Multi-Channel integration. With demand forecasting and pre-determined stock rules, Stok.ly ensures you’re always in control. It predicts when stock will run low, triggers automated reorders and prevents overstocking – so you don’t get caught with excess inventory or empty shelves.
Whether a viral trend takes off overnight or seasonal demand shifts unexpectedly, Stok.ly ensures you have the right products in the right place – before your competitors do.
Because predicting trends is great, but capitalising on them is what really matters.
Click here for more information about Stok.ly Cloud ERP
Call us on 01432 804333
Author: Iain Coplans CEO Stok.ly