The Evolution of Fashion Retail
Fashion has always had a unique place in the world of commerce. Unlike other industries where purchases are driven by necessity, fashion is often about desire, influence, and exploration. This makes it an ideal space for technological innovation that can reshape how consumers interact with brands.
The fashion industry operates on cycles—trends come and go, and sales are heavily influenced by these patterns. Much of the sector relies on overproduction, followed by frequent discounts to clear inventory. Sales are not just occasional events; they are built into the very fabric of how the system works.
Now, a new wave of AI technology is beginning to transform this landscape. One of the most significant changes is in pricing strategies.
Dynamic Pricing: A New Era
Dynamic pricing is not a new concept. It’s commonly seen in sectors like travel and ride-sharing, where prices fluctuate based on demand. For example, the more you search for a flight or a ride, the higher the price may become, especially if there’s a clear intent to purchase.
In fashion, however, demand isn’t always tied to necessity. This means that dynamic pricing isn’t just about pushing prices up—it’s about constantly adjusting them to keep products moving. A recent report from Business Insider highlighted how dynamic pricing is already making its mark in the fashion retail sector. Items left in an online cart at a major clothing retailer saw multiple price changes over a few days, sometimes increasing, sometimes decreasing. In some cases, waiting could result in a discount of up to 17%.
As this practice becomes more widespread, shopping will no longer feel like a simple decision but more like timing a complex system.
In Australia, the consumer watchdog does not consider dynamic pricing inherently unlawful. However, data-use guidelines around pricing are still evolving and not yet comprehensive.
The Rise of Shopping Bots
At first glance, new AI tools for online shopping seem focused on convenience. Virtual try-ons, for instance, are becoming increasingly realistic, allowing customers to see how garments fit and drape on their own bodies. This could help reduce returns, which are a costly burden for retailers.
But companies like Google are taking this a step further. Users can now try items on, set the price they’re willing to pay, and the system will track it, notify them when it hits that price, and even complete the purchase if permission is given.
What starts as a tool for convenience quickly evolves into something more profound. You’re no longer actively shopping—you’re letting your bot make purchases on your behalf.
This shift is part of a broader trend known as “agentic commerce,” where an AI agent acts on your behalf based on pre-set preferences.
Who Sets the Price?
Using a shopping agent changes the dynamics of dynamic pricing. Traditionally, brands set prices and adjust them based on factors like demand, inventory, and consumer behavior. But in this emerging model, consumers are also feeding into the system directly by stating what they are willing to pay.
At first, this feels empowering. It sounds like consumers are gaining more control. However, it also introduces a new complexity. Who is truly in control of pricing if both sides are driven by AI?
If someone sets a price they’re comfortable with, the system can complete the purchase as soon as that price is reached. But the price might have dropped even lower if that data wasn’t available. In effect, consumers may be setting their own limits without realizing it.
This creates a feedback loop. Retailers optimize prices using data, while consumers provide their own price thresholds. Both sides are guided by algorithms, and the final outcome sits somewhere in between.
The question is no longer just how prices are set, but who is really influencing them.
Convenience Meets Over-Consumption
There are clear benefits to this shift. Automating purchases could make everyday shopping easier. However, in fashion, where consumption is already high, tech tools that make pricing feel more personalized or within reach are unlikely to reduce consumption. They may even encourage overconsumption.
Consumers should be mindful not to let the apparent convenience of shopping bots and personalized pricing alerts lead to a rise in impulse purchases.
