If you’ve ever watched the cost of a flight jump within a single afternoon, you’ve experienced the shifting world of digital pricing. What once seemed like random fluctuations is now often the result of artificial intelligence quietly calculating what you—specifically—might pay.
AI has pushed pricing far beyond traditional supply-and-demand adjustments. Businesses are increasingly using your online behavior and personal data to tailor prices directly to you, creating a marketplace where identical products may no longer cost the same for everyone. While this technology brings efficiency, it also raises uncomfortable questions about fairness and transparency.
Dynamic Pricing vs. Personalized Pricing
Dynamic pricing has been around for years. Airlines charge more when demand spikes, hotels adjust rates for busy weekends, and ride-sharing apps introduce surge pricing during peak hours.
Personalized pricing, however, shifts the focus from market conditions to individual shoppers. Here, AI examines your browsing patterns, purchase history, location, and even the device you’re using to estimate how much you’re likely to pay. Two people searching for the same hotel room may end up with very different offers. Loyal shoppers could be nudged into spending a bit more, while indecisive customers might be enticed with special discounts.
In simple terms: dynamic pricing responds to the market; personalized pricing responds to you.
How Personalized Pricing Took Over
The roots of this strategy can be traced back to the airline industry in the 1990s. After deregulation, carriers began experimenting with complex fare adjustments based on remaining seats and timing. Eventually, they layered personalized behavior into the mix, using browsing history and customer data to fine-tune prices.
Hotels adopted similar methods, offering exclusive rates to repeat guests or adjusting prices when a user lingered on a booking page. Today, these tactics have expanded far beyond travel. Retailers, streaming platforms, food delivery services, and even grocery chains are using AI to shape prices in real time.
How AI Decides What You’ll Pay
Every digital action—from how long you pause on a product to how often you shop—feeds into an algorithm that builds a portrait of your purchasing habits. Machine learning tools analyze thousands of signals to estimate how sensitive you are to price changes.
Some companies have seen dramatic results. Booking platforms, for example, have used AI to identify which shoppers should receive targeted promotions, leading to significant increases in bookings. That sudden jump in price when you refresh a page may be less coincidence and more calculation.
The Risks Behind Personalized Pricing
While these systems can improve sales and deliver tailored deals, they also introduce serious concerns:
1. Fairness Problems
Basing prices on factors like location or device type can unintentionally discriminate against certain groups. Two people in the same area could face very different costs simply because of their digital footprint.
2. Loss of Consumer Trust
Few things frustrate shoppers more than discovering they paid more than someone else. Once people suspect they’re being singled out, they turn to private browsing modes, cookie-clearing, or alternate devices to avoid being profiled.
3. Blurred Responsibility
If a price is unfair, who is accountable? The company? The engineers? The algorithm? The lack of transparency makes oversight difficult.
Regulators Step In
Authorities around the world are paying closer attention. In Australia, the ACCC issued a major report in mid-2025 highlighting concerns about opaque algorithms, unfair pricing practices, and potential consumer harm. The agency called for stronger platform oversight, clearer rules around digital pricing, and mandatory disclosure of how pricing models work.
As AI-driven commerce accelerates, more countries are expected to introduce their own regulations.
The Bigger Question: Efficiency or Exploitation?
Personalized pricing has the potential to make digital markets more efficient by offering discounts where they’re most effective and helping businesses better understand customer needs. But the same technology can feel intrusive, even manipulative—like being monitored every time you shop.
For companies, the challenge is to use AI responsibly and openly. For regulators, it’s about acting quickly enough to ensure trust doesn’t erode.
Because in today’s digital marketplace, the price you see may say less about the product and more about what the algorithm thinks of you.
