AI-powered personalized pricing making waves among shoppers: is it fair?

Delta Air Lines announced recently it would expand its use of AI to provide individualized prices to customers. This move has sparked concern among consumers. Even if personalized pricing has been here for ages, it’s technology deciding what you’re gonna pay this time – and that might translate into digital discrimination.

In July, three Democratic senators pressed Delta Air Lines CEO Ed Bastian to answer questions about the airline’s planned use of AI to set ticket prices, raising concerns about the impact on travelers.

“Delta’s current and planned individualized pricing practices not only present data privacy concerns, but will also likely mean fare price increases up to each individual consumer's personal ‘pain point’ at a time when American families are already struggling with rising costs,” Senators Ruben Gallego, Mark Warner, and Richard Blumenthal wrote in a letter.

Delta had indeed disclosed plans to deploy AI-based revenue management tech across 20% of its domestic network by the end of 2025 in partnership with Fetcherr, an AI pricing company.

In response to the Senators’ letter, though, the company called its content “misinformation.” Delta said it “had zero tolerance for discriminatory or predatory pricing” and had no plans to target flyers with individualized prices based on personal data.

It remains to be seen what’s the deal here. But it seems impossible for firms eager to make as much money as possible to not try and weaponize AI in their pricing processes.

Furthermore, dynamic pricing, in which it fluctuates based on a variety of factors like customer demand, has been used for decades anyway.

Still, at least officially, pricing can’t be affected by a specific customer’s personal information. But here’s the catch: when AI technology is used, it gobbles up every possible bit of data about you. It just has to be somewhere on the web.

Already in January, another group of US Senators asked Frontier Airlines and Spirit Airlines to disclose whether they were manipulating seat fees by using flyers’ personal information to charge different fees to passengers on the same flight.

AI weaponizes your information

To begin with, personalized, or custom, pricing is nothing new. For centuries, this was the way things happened. As a business owner, you used to size up your customer and bargain face-to-face. In the end, a more skilled haggler won out.

According to Jay L. Zagorsky, associate professor of markets, public policy, and law at Boston University, customized pricing – where each customer receives a different price for the same product – is a holy grail for businesses because it boosts profits.

“With customized pricing, free-spending people pay more while the price-sensitive pay less. Just as clothes can be tailored to each person, custom pricing fits each person’s ability and desire to pay,” Zagorsky wrote in The Independent recently.

Uniform pricing is simple for customers to understand, plus, it simply looks fair and non-discriminatory. There’s a price tag, and at least that day, it’s not going to show a different number.

Nowadays, of course, we mostly see set prices. Retailers purchase a product and add a, say, 10-15% markup to make money.

Uniform pricing is simple for customers to understand, plus, it simply looks fair and non-discriminatory. There’s a price tag, and at least that day, it’s not going to show a different number.

But personalized pricing still exists. Car dealerships often negotiate a different price for each vehicle, essentially charging every customer the maximum amount they’re willing to pay, upfront or monthly.

To that, add AI, its hunger for data, and the fact that the shift from cash to electronic payments has enabled businesses to constantly collect a gold mine of information.

The formula, according to some experts, is or at least has the potential to be particularly invasive. You’re not gonna be too happy when personalized prices change based on your income, browsing history, or even location, are you?

“Predictive pricing is one AI use case that almost every consumer and regulator can unite against. It chafes against everyone’s idea of what’s fair or ethical. The problem isn't only that companies are using our browsing habits, location data, or demographic info to charge us more, it's that most of us have zero clue it's happening,” Ron De Jesus, field chief privacy officer at data privacy infrastructure company Transcend, told Cybernews.

“When a sneaker company can advertise the same pair of shoes to one family member for $80 and another for $120 based on algorithmic profiling, it's both discrimination and a serious privacy violation.”

Another form of progressive taxation?

In fact, already in 2024, the Federal Trade Commission (FTC) issued civil subpoenas to Mastercard, JPMorgan Chase, and other financial companies demanding to know “how artificial intelligence and other technological tools may allow companies to vary prices using data they collect about individual consumers’ finances and shopping habits.”

From the shareholder point of view it is a dream come true, where the organization would be able to extract the maximum from each individual customer. Corporations then would basically institute a form of progressive taxation.

Vaclav Vincalek.

Experiments at the FTC have also shown that AI programs can even collude among themselves to raise prices without human intervention. It’s all a little uncanny to some.

Vaclav Vincalek, founder of Hiswai.com, an AI-powered research and insights platform, told Cybernews that the AI-seasoned drive to create modern personalized pricing reminded him of a famous Karl Marx quote, which says: “‘From each according to his ability, to each according to his needs.”

“From the shareholder point of view it is a dream come true, where the organization would be able to extract the maximum from each individual customer. Corporations then would basically institute a form of progressive taxation,” said Vincalek.

When pricing is influenced by highly personal data, consumer trust can quickly plummet, adds Afshin Yazdian, CEO at Electronic Merchant Systems.

The mere perception of “different prices for different people” can feel inherently unfair to customers – even though, again, companies have long used dynamic pricing for ride-sharing apps, airline tickets, and concert tickets, adjusting the price based on certain conditions like demand. And AI helps massively.

According to Yazdian, it’s technically possible for AI-driven systems to adjust prices based on very personal information because the tech can correlate signals to inform pricing models, and some could reveal sensitive details.

Businesses like airlines can extend their monitoring capabilities by buying additional customer data from third-party brokers that collect extensive profiles of millions of people around the world.

Steve Morris, founder and CEO of marketing agency NEWMEDIA, says we shouldn’t blindly trust official statements or denials because his personal experience has indeed shown that AI pricing engines use personal data much more often than people think.

“Over the past year we’ve worked with companies and watched as AI systems have figured out things like how expensive your device is and what your household income might be, all from tiny clues like your search habits, ZIP code, and even the times you’re online,” Morris told Cybernews.

“The market is built to squeeze every dollar from customers, and AI is only making it better at doing that every day.”

It’s a two-way street

Quite surprisingly, personalized pricing isn’t illegal, Yelena Ambartsumian, a New York lawyer and founding attorney of AMBART LLC, an art, IP, and information privacy law firm, tells Cybernews.

For example, under a New York law on “Personalized Pricing Transparency and Anti-Discrimination” that took effect in July, companies using your browsing or shopping history to set prices for you must have have the following disclaimer: “This price was set by an algorithm using your personal data.”

However, the law does not prohibit the use of personalized algorithmic pricing in all cases. “Protected class data” such as national origin, disability, sex, orientation, gender identity and expression, pregnancy outcomes, and reproductive healthcare, cannot be used to set prices if the use of that data would result in certain groups missing out on “accommodations, advantages, or privileges.”

If there aren’t any missed benefits, companies can use this “protected class data” to personalize algorithmic pricing, Ambartsumian said.

Sure, in a dream world, AI pricing would be regulated and transparent enough to work properly. Algorithms would be regularly audited and updated to ensure fairness.

De Jesus thinks that the most effective approach would be for firms to offer opt-in programs where users explicitly consent to data-driven pricing in exchange for benefits like digital coupons or rewards points.

As of now, the burden is on the consumer. Sure, they shouldn’t have to be detectives to figure out whether they’re getting a fair deal – but they can always take their business elsewhere.

The most effective approach would be for firms to offer opt-in programs where users explicitly consent to data-driven pricing in exchange for benefits like digital coupons or rewards points.

Plus, AI is a two-way street, some experts say. If the dislike for AI-powered surveillance pricing grows, so will the opportunity for the AI shopping agents to step in on behalf of the buyer.

“Just as buyers pay for programs like Amazon Prime to save on shipping and gain other benefits, buyers will be open to using aggressive AI buying agents to get the best price from potential suppliers,” said Mitch Ashley, technology executive at The Futurum Group.

Finally, according to Victor Horlenko, head of AI innovations at Devart, AI can actually improve pricing policies and could in the near future personalize the models for use value rather than just for profit.

“Why do you need to pay for 100 features of the product if you need only 10? AI can help to determine your demand in seconds and offer you a fair price for the features you need. That means a customer gets the product he needs, and the business still gets its revenue,” explained Horlenko.