AI pushes dynamic pricing into fashion; Australia’s watchdog says it’s not inherently unlawful

The price of a dress in your online cart may no longer be fixed. As a new layer of artificial intelligence moves into fashion retail, dynamic pricing is adjusting what shoppers pay — sometimes up, sometimes down — turning checkout into a game of timing. Fashion has long relied on cycles of trends and volume.

Overproduction is common, with constant waves of discounting built into how the industry clears stock. Dynamic pricing has existed for years in sectors like flights and ride sharing, where prices often increase the more you search, especially when there is a clear intention to pay.

In fashion, though, demand is not always tied to necessity. That means pricing does not just reward urgency; it can also reward patience. The goal is less about ratcheting prices up than keeping products moving. A recent report from Business Insider in the United States illustrates how quickly this is taking hold.

At a major clothing retailer, the prices of items left in an online cart shifted multiple times over a few days — sometimes rising, sometimes dropping. In some instances, waiting delivered a discount of up to 17 per cent. As this becomes more common, shopping will feel less like a simple decision and more like timing a system.

In Australia, the consumer watchdog does not consider dynamic pricing inherently unlawful. Broader data-use guidelines around pricing are not yet comprehensive, underscoring how quickly these tools are evolving compared with existing frameworks. At first glance, many of the new AI shopping tools promise convenience.

Virtual try-ons are becoming more realistic, helping people see how garments might fit and drape on their own bodies — a development that could reduce costly returns. Companies like Google are taking this a step further: shoppers can try items on, set the price they are willing to pay, and have the system track it, notify them when it hits that price, and even complete the purchase if they give permission.

That convenience marks a shift toward what is being called “agentic commerce”, in which an AI agent acts on a consumer’s behalf based on pre-set preferences. Traditionally, brands set prices and adjusted them according to demand, inventory and observed behaviour.

In the emerging model, consumers feed into the process directly by stating what they are willing to pay. It may feel empowering, but it alters the dynamic between buyer and seller. Consumers should be mindful not to let shopping bots and personalised pricing alerts prompt impulse buys.

Without scrutiny, agent-led shopping risks quietly reconfiguring consumer behaviour in ways that are difficult to detect — and even harder to reverse.